Reecap Merci

Marie Lassalas

Mathilde Fromage

Julia Jouan

Chantal Le

Françoise Auffray

Cécilia

Ahmet Candemir

Charlotte Chemarin

Julia Denantes

Esther Devilliers

Jean-François Dewals

Francesco Guerra

Lucile Henry

Victor Kieffer

Abdel Osseni

Mathilde Roignant

Romaric Sodjahin

Lucille Steinmetz

Jochen Kantelhardt De M'avoir Accueilli

Merci

Laura Eckart

Michael Eder

Michaela Grötzer

Sabine Muhr

Andreas Niedermayr

Sarah Oberdorfer

Verena Scherfranz

Fritz Wittmann

Julian Zeilinger

Je voudrais remercier Pierre Dupraz et Elodie Letort qui ont encadré cette thèse. Merci de votre confiance et de m'avoir laissé beaucoup d'autonomie dans mon travail. C'était un grand moteur de ma motivation au quotidien. Pierre, merci pour tes conseils bienveillants et ton enthousiasme à partager tes connaissances. Même s'ils se sont parfois fait rares, nos échanges m'ont toujours fait beaucoup progresser. Elodie, merci pour ta réactivité, ton enthousiasme et ta franchise. Tes intuitions m'ont souvent aidé à prendre des décisions et me relancer en période de doute. Je te remercie aussi de m'avoir encouragé à postuler à cette thèse (encore une fois, ton intuition) ! Je remercie Douadia Bougherara, Philippe Bontems et Thomas Poméon pour leur intérêt, leurs encouragements, et leur bienveillance lors des comités de suivi de thèse. La préparation et le déroulé de ces points d'étapes annuels ont été décisifs dans la construction progressive du fil directeur de la thèse. Je suis également très reconnaissante à Pierre Courtois, Laure Kuhfuss, Bettina Matzdorf, Damien Rousselière, Mary Ryan et Lionel Védrine d'avoir accepté de faire partie de mon jury de thèse. Merci à Sabine Duvaleix, Alice Issanchou, et Carole Ropars-Collet, avec qui j'ai eu le plaisir de travailler sur les chapitres 3 et 4 de cette thèse. Je souhaite remercier Marie Laporte pour sa participation aux travaux préliminaires sur le programme Eco-Méthane dans le cadre de son stage de M1, et Florian Martial pour son investissement dans la préparation et la conduite de l'expérience de choix dans le cadre de son stage de M2. Un grand

Synthèse Chapitre 1. Introduction générale

L'agriculture est intrinsèquement reliée aux ressources naturelles et aux écosystèmes. Pour produire de la nourriture, les activités agricoles prélèvent des ressources des écosystèmes naturels, et utilisent des intrants dérivés de l'extraction de ressources naturelles. L'agriculture bénéficie également de services écosystémiques de support (photosynthèse, cycles des nutriments et de l'eau, formation et fertilité des sols, biodiversité génétique) et de régulation (pollinisation, lutte contre les maladies et les ravageurs, purification de l'eau, décomposition, climat). En outre, l'agriculture contribue à façonner les paysages et à modifier les habitats naturels, et libère des gaz à effet de serre (GES), des produits chimiques et des nutriments dans l'environnement (eau, air, sol) [START_REF] Heal | Agriculture and ecosystem services[END_REF][START_REF] Lichtenberg | Agriculture and the Environment[END_REF]Millennium Ecosystem Assessment, 2005;Therond et al., 2017). Ces perturbations des cycles du carbone, de l'azote, du phosphore et de l'eau affectent le climat et les habitats en entraînant une pollution et une vulnérabilité accrue aux risques naturels [START_REF] Hatab | Agriculture, Forestry and Other Land Uses[END_REF][START_REF] Bezner Kerr | Food, Fibre and Other Ecosystem Products[END_REF][START_REF] Eea | EEA Signals 2019. Land and soil in Europe: Why we need to use these vital and 200 finite resources sustainably[END_REF]. En Europe, le secteur agricole est le deuxième contributeur aux émissions de GES [START_REF] Eea | Annual European Union greenhouse gas inventory 1990-2020 and inventory report[END_REF], le premier contributeur à la pollution diffuse des eaux (EEA, 2021), et souvent la principale source de pression sur les habitats et les espèces (EEA, 2020a;IPBES, 2019). En retour, les effets à court et long termes de la dégradation des écosystèmes et du changement climatique affectent les capacités de production agricole (Bezner [START_REF] Bezner Kerr | Food, Fibre and Other Ecosystem Products[END_REF].

Les multiples interactions entre les activités agricoles et les écosystèmes naturels font du secteur agricole à la fois un producteur de denrées alimentaires et un fournisseur de biens (et de maux) publics, dont les bénéfices (et les dommages) sont disponibles et accessibles à de nombreuses personnes au-delà des limites de l'exploitation [START_REF] Cooper | The Provision of Public Goods through Agriculture in the European Union[END_REF]. Ces biens publics comprennent des habitats pour une diversité d'espèces (flore et faune des milieux agricoles), le stockage à long terme du carbone dans les sols et les éléments paysagers, et la protection de la qualité des sols et de l'eau des bassins versants. Depuis la montée des préoccupations environnementales mondiales dans les années 1970, les scientifiques ont accumulé des connaissances approfondies sur les interactions entre les systèmes agricoles et l'environnement, et sur les pratiques des agriculteurs qui atténuent les pressions sur les écosystèmes [START_REF] Altieri | Agroecology: the Science of sustainable agriculture[END_REF]. Les préoccupations environnementales et les solutions étant bien identifiées, le défi consiste aujourd'hui à généraliser leur adoption et à financer la transition. v Les paiements pour services environnementaux (PSE) sont des instruments aidant financièrement les agriculteurs à adopter des pratiques plus respectueuses de l'environnement.

Ils reconnaissent les interventions volontaires des agriculteurs contribuant aux biens publics

tels que l'atténuation du changement climatique, la qualité de l'eau et la préservation de la biodiversité, comme des services environnementaux (SE), pour lesquels ils peuvent recevoir un paiement. Les SE sont fournis jointement avec les produits agricoles (production jointe). Dans un contexte de dégradation générale de la fourniture de biens publics par l'agriculture, il existe un consensus sur le fait que les SE sont soumis à une défaillance du marché. Les PSE vient à corriger cette insuffisance. Les systèmes de PSE introduisent des mécanismes de financement pour mobiliser le consentement à payer (CAP) pour les SE, d'une part, et des mécanismes de paiement pour encourager les agriculteurs à fournir des SE, d'autre part [START_REF] Pagiola | Payments for Environmental Services[END_REF]. Les PSE sont des transactions volontaires entre fournisseurs de SE et des contributeurs, conditionnées à la mise en oeuvre d'un ensemble de règles convenues pour générer des services (biens publics) au-delà des limites de l'exploitation agricole (S. Wunder, 2015). Les PSE sont des outils permettant de répondre à l'offre et à la demande de biens publics agroenvironnementaux et climatiques, et visent à accompagner une transition agroécologique à grande échelle vers une meilleure fourniture de ces biens par le secteur agricole.

Trois problèmes principaux d'inadéquation entre l'offre des agriculteurs et la demande sociale ont été identifiés avec les PSE dominants actuels, que sont notamment les mesures agroenvironnementales et climatiques (MAEC) de la politique agricole commune (PAC) (dispositifs publics dédiés). Premièrement, les mécanismes de financement ne permettent pas de capturer suffisamment de CAP pour répondre à la demande des agriculteurs et favoriser une adoption à grande échelle par les agriculteurs (faible demande des contributeurs) [START_REF] Cullen | Agri-Environment Scheme Design: Past Lessons and Future Suggestions[END_REF][START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF][START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF][START_REF] Zimmermann | European farms' participation in agri-environmental measures[END_REF]. Deuxièmement, les mécanismes de paiement tendent à conditionner le paiement à la mise en place de pratiques imposées au sein d'une exploitation individuelle (obligation de moyens), souvent peu ambitieuses, ce qui ne favorise ni l'efficacité environnementale, ni le dépassement des effets de seuils permettant la fourniture de bénéfices publics (faible offre de biens publics) [START_REF] Cullen | Agri-Environment Scheme Design: Past Lessons and Future Suggestions[END_REF][START_REF] Dupraz | Threshold effect and co-ordination of agrienvironmental efforts[END_REF][START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF][START_REF] Zavalloni | Agri-environmental Policies and Public Goods: An Assessment of Coalition Incentives and Minimum Participation Rules[END_REF]. Troisièmement, les règles actuelles des aides publiques contraignent le paiement à être une compensation plutôt qu'une incitation, ce qui rend l'adoption des PSE non rentable pour de nombreux agriculteurs (faible offre de SE) [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF]. vi De nouveaux types de PSE laissent entrevoir des leviers potentiels d'amélioration. Une demande plus forte de la part des contributeurs peut être exprimée en consacrant davantage de fonds publics aux aides environnementales (renforcement des dispositifs publics dédiés) [START_REF] Dupraz | Environment and climate in the common agricultural policy[END_REF][START_REF] Matthews | Greening agricultural payments in the EU's common agricultural policy[END_REF], et/ou en développant des mécanismes de financement qui captent un CAP privé (PSE privés dédiés ou intégrés dans la chaîne de valeur) [START_REF] Duval | Favoriser le déploiement des paiements pour services environnementaux en agriculture: Guide à destination des acteurs privés[END_REF][START_REF] Eichhorn | Deliverable 2.6: Catalogue of updated factsheets of European in-depth case studies[END_REF]. En outre, la fourniture de biens publics et l'efficacité environnementale des PSE peut être améliorée en conditionnant le paiement à la réalisation de dynamiques collectives au sein des agriculteurs d'un même ensemble paysager (approche paysagère), et/ou à la réalisation d'un résultat environnemental [START_REF] Burton | Result-oriented agri-environmental schemes in Europe and their potential for promoting behavioural change[END_REF][START_REF] Chaplin | Developing payment-by-results approaches for agri-environment schemes: Experience from an arable trial in England[END_REF][START_REF] Eichhorn | Deliverable 2.6: Catalogue of updated factsheets of European in-depth case studies[END_REF][START_REF] Matzdorf | How cost-effective are result-oriented agri-environmental measures?-An empirical analysis in Germany[END_REF][START_REF] Westerink | Collaborative governance arrangements to deliver spatially coordinated agrienvironmental management[END_REF].

L'objectif de ma thèse est d'analyser avec des approches théoriques et empiriques, l'efficacité de deux cas polaires de PSE : (i) la rémunération par les pouvoirs publics des SE volontaires des agriculteurs (dispositifs publics dédiés), (ii) la création d'un label sur un produit agricole visant à rémunérer un SE par les consommateurs (dispositifs intégrés dans la chaîne de valeur).

Dans ma thèse, j'évalue différents leviers permettant d'accroître l'adoption des PSE par les agriculteurs, en abordant spécifiquement les limites et les inefficacités des mécanismes actuels identifiés dans la littérature : (i) augmenter le budget alloué aux instruments publics actuels de PSE dans la PAC (chapitre 2), (ii) introduire des incitations favorisent une dynamique collective dans les mécanismes de paiement ciblant des biens publics avec des effets de seuils écologiques (chapitre 3), (iii) concevoir des mécanismes de paiement basés sur les résultats (chapitre 4).

Pour compléter le financement public limité et les contributions volontaires insuffisantes des acteurs privés, je propose de capter davantage de contributions de la part des consommateurs en développant des labels officiels contenant des informations sur les bénéfices privés (ex : santé) de la consommation de denrées agricoles produites conjointement aux SE (chapitre 5).

Je défini une grille d'analyse des PSE selon deux dimensions (Figure S1) : (i) le ciblage du mécanisme de paiement, (ii) le mécanisme de financement mobilisant le CAP des contributeurs. viii Le premier axe permet de situer un PSE selon que le paiement est conditionné par les moyens mis en oeuvre par les exploitations individuelles (ciblage des pratiques sur l'exploitation) ou par le bénéfice environnemental hors exploitation (ciblage du bien public environnemental au-delà de l'exploitation). Par exemple, il différencie les PSE à obligation de moyens (ex : paiement à l'hectare pour ne pas retourner une prairie) des PSE à obligation de résultat (ex : Eco-Méthane avec un paiement proportionnel à la réduction des émissions de méthane entérique par litre de lait). Je situe les approches paysagères au centre de cet axe, car elles sont ciblées sur des réalisations impliquant plusieurs agriculteurs et vont au-delà des limites de l'exploitation individuelle, mais peuvent inclure des exigences de pratiques ou de résultats environnementaux selon la conception du dispositif. Le deuxième axe classe les PSE selon qu'ils sont financés par le contribuable (mobilisation d'un CAP agrégé au nom des bénéficiaires du bien public) ou par des contributeurs volontaires suivant leur CAP individuel (mobilisation du CAP d'un agent selon ses propres préférences). Ce deuxième axe différencie les deux cas polaires de PSE, à savoir les MAEC financées par la PAC et la prime de prix payée par les consommateurs d'un produit labellisé dont la production est jointe à des SE. Sur la base de cette grille de lecture, je formule quatre questions de recherche que je développe dans quatre articles de recherches.

Question de recherche 1 : Les MAEC peuvent-elles être renforcées en ciblant davantage de fonds publics vers la fourniture de biens publics ?

Le premier mécanisme de PSE analysé est le soutien public dédié aux engagements environnementaux volontaires des agriculteurs dans le cadre de la politique agricole commune (PAC). Les données empiriques montrent qu'il existe un écart entre les priorités déclarées de la PAC et leur budget relatif. En particulier, le budget consacré au soutien des pratiques agricoles respectueuses de l'environnement est faible par rapport au budget des paiements directs aux agriculteurs qui ne sont pas ou peu conditionnées à des exigences environnementales.

Le chapitre 2 se concentre sur un scénario d'évolution de répartition du budget de la PAC afin de cibler davantage l'argent des contribuables vers la fourniture de biens publics. Notre hypothèse est qu'un transfert de budget des paiements directs vers les paiements environnementaux augmenterait l'adoption volontaire des SE sans nécessiter de financement supplémentaire de la part du contribuable. En utilisant les données françaises du Réseau d'information comptable agricole (RICA), nous simulons l'effet d'un transfert de 7,5% des paiements directs vers les MAEC et le soutien à l'agriculture biologique. ix Question de recherche 2 : Un bonus conditionnel pourrait-il renforcer l'engagement des agriculteurs et les inciter à dépasser les seuils écologiques ? Lorsque l'objectif d'un PSE est la protection de la qualité de l'eau ou la biodiversité, une masse critique et une continuité spatiale des engagements à l'échelle du paysage sont nécessaires pour observer des améliorations environnementales. Des études montrent que les agriculteurs sont réticents lorsque des exigences collectives conditionnent l'ensemble du paiement, mais qu'ils sont plus favorables à un bonus récompensant une action collective en plus d'un paiement individuel [START_REF] Ben-Othmen | Farmers' preferences for grassland restoration: Evidence from France. 172nd EAAE Seminar 'Agricultural policy for the environment or environmental policy for agriculture?[END_REF][START_REF] Kuhfuss | Nudging farmers to enrol land into agrienvironmental schemes: The role of a collective bonus[END_REF][START_REF] Coent | Compensating Environmental Losses Versus Creating Environmental Gains: Implications for Biodiversity Offsets[END_REF][START_REF] Villamayor-Tomas | Bringing the neighbors in: A choice experiment on the influence of coordination and social norms on farmers' willingness to accept agro-environmental schemes across Europe[END_REF][START_REF] Villanueva | Heterogeneity of farmers' preferences towards agri-environmental schemes across different agricultural subsystems[END_REF]. L'introduction d'une conditionnalité liée à l'approche paysagère sous la forme d'un paiement bonus pour déclencher une plus grande agglomération et un résultat environnemental limite les risques pour un agriculteur de ne recevoir aucune compensation pour ses SE si l'effort et les surfaces agrégés sont insuffisants.

A partir d'une expérience de choix réalisée lors d'enquêtes auprès d'agriculteurs du nord-ouest de la France, le chapitre 3 vise à mesurer les préférences des agriculteurs pour un contrat PSE avec un paiement dont une partie serait conditionnée par le parrainage d'autres agriculteurs sur le territoire éligible (bonus de parrainage) et/ou un résultat environnemental collectif (amélioration de la qualité de l'eau). Deux hypothèses sont sous-jacentes : (i) la prime de parrainage permet de recruter plus d'agriculteurs sur un même territoire et d'augmenter les engagements ES à l'échelle du paysage, et favorise donc la fourniture de biens publics seuils, (ii) l'effet collaboratif de la prime de parrainage peut être renforcé par une récompense collective pour l'atteinte d'un résultat environnemental sur le territoire.

Question de recherche 3 : Quels sont les éléments techniques à prendre en compte pour définir un paiement proportionnel au résultat environnemental ?

Les règles de conditionnalité des PSE à obligation de résultat définissent un paiement basé sur la réalisation d'un résultat environnemental, plutôt que sur la mise en oeuvre de pratiques prescrites. En théorie, ils présentent les mécanismes de paiement les plus ciblés sur la fourniture de biens publics. Elle favorise également l'efficacité des agriculteurs, qui sont libres de choisir les pratiques les moins coûteuses adaptées à leur situation pour satisfaire aux exigences contractuelles [START_REF] Herzon | Time to look for evidence: Results-based approach to biodiversity conservation on farmland in Europe[END_REF]. Des difficultés techniques se posent quant à la manière de capter et de mesurer précisément l'effort environnemental des agriculteurs, et de définir le niveau de paiement [START_REF] Massfeller | Farmers' acceptance of resultsbased agri-environmental schemes : A German perspective[END_REF][START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF]Zabel and Roe, 2009a).

x Sur la base d'un PSE existant à obligation de résultat, le PSE Eco-Méthane (Le [START_REF] Gloux | Cost of changing dairy cows' diet to reduce enteric methane emissions in livestock farms[END_REF], le chapitre 4 explore l'adoption de pratiques permettant de réduire les émissions de méthane entérique des vaches laitières par la mise en place d'un paiement conditionné aux unités d'équivalents CO2 atténuées par litre de lait. En particulier, nous étudions l'importance de prendre en compte la place de l'herbe dans l'alimentation du troupeau (i) dans le choix de l'indicateur d'émissions définissant l'unité de paiement, (ii) dans la définition du niveau de paiement par rapport au surcoût d'un changement de régime alimentaire des vaches laitières.

Question de recherche 4 : L'étiquetage sur la fourniture complémentaire de bénéfices privés augmente-t-il l'efficacité des écolabels ?

Pour compléter le financement public limité, il devient important de s'intéresser à la demande en biens publics, notamment d'identifier des outils permettant de capter davantage de CAP.

Fournir aux consommateurs des informations sur les SE fournis par les agriculteurs par le biais de l'étiquetage des produits alimentaires leur permet d'exprimer leurs préférences pour l'environnement et d'envoyer un signal prix aux agriculteurs pour encourager les SE. Des études empiriques ont montré que les préoccupations en matière de santé sont souvent les principaux motifs d'achat de produits respectueux de l'environnement [START_REF] Aldanondo-Ochoa | The private provision of public environment: consumer preferences for organic production systems[END_REF][START_REF] Brécard | Determinants of demand for green products: an application to eco-label demand for fish in Europe[END_REF][START_REF] Verhoef | Explaining purchases of organic meat by Dutch consumers[END_REF].

Dans le cinquième chapitre de la thèse, nous nous intéressons au cas spécifique où la technologie de production jointe est telle que la fourniture de SE est complémentaire à la production d'une denrée agricole fournissant des bénéfices pour la santé. Notre hypothèse est que des contributions plus élevées et la fourniture de SE pourraient être atteintes en fournissant des preuves scientifiques de leurs effets positifs sur la santé aux consommateurs. Nous Nos résultats montrent que ce mécanisme augmente la participation (de 11% à 24% pour les MAEC, de 7 à 17% pour le soutien à l'agriculture biologique). Ce résultat s'explique par deux incitations combinées favorisant l'adoption. Un effet direct de l'augmentation des fonds publics disponibles permet de financer de nouveaux engagements environnementaux. Un effet indirect d'une diminution des paiements directs tend à réduire les paiements acceptables déclenchant la participation des exploitations, permettant de financer encore plus d'exploitations. L'effet du transfert budgétaire diffère selon la spécialisation de l'exploitation. L'adoption des MAEC par les élevages bovins est favorisée, tandis que les exploitations spécialisées dans les cultures permanentes, l'élevage de granivores et des vaches laitières ont tendance à adopter davantage de soutien à l'agriculture biologique (maintien ou conversion). Une des limites à la généralisation de nos résultats et que les modèles d'adoption estimés ne parviennent pas à saisir suffisamment l'hétérogénéité des exploitations pour reproduire avec précision le comportement observé, en particulier pour les MAEC. xii Chapitre 3. Paiements pour services environnementaux en présence de seuils écologiques : préférences des agriculteurs pour un bonus de parrainage L'une des principales limites des PSE développés depuis le début des années 1990, est leur inefficacité lorsqu'il s'agit d'augmenter la fourniture de biens publics avec des effets de seuil.

En particulier, la conditionnalité basée sur des obligations de moyens, qui consiste à prescrire des pratiques agricoles aux agriculteurs individuels sans tenir compte de ce qui est fait dans les exploitations voisines, semble inadéquate pour remédier à leur sous-production. Dans ce chapitre co-écrit avec Pierre Dupraz, Alice Issanchou et Carole Ropars-Collet, nous étudions l'introduction d'un mécanisme de paiement combinant une conditionnalité basée sur des obligations de moyen avec un bonus récompensant une démarche collective.

Au travers d'expérience de choix réalisée auprès de 130 agriculteurs en Bretagne, Normandie et Pays de la Loire, nous proposons un bonus de parrainage en complément d'un paiement individuel à l'hectare pour promouvoir une plus grande participation dans la zone cible d'un PSE. Nous mesurons les préférences ex ante des agriculteurs pour un tel mécanisme de bonus dans un PSE fictif visant à améliorer la qualité de l'eau des rivières. Les 4 attributs du contrat étaient une couverture minimale du sol tout au long de l'année, une densité minimale de haies anti-érosives, un paiement individuel à l'hectare et une option de bonus à trois niveaux : (i) aucun bonus, (ii) un bonus de parrainage de 450€ chaque fois que l'agriculteur convainc un pair d'adopter le PSE, (iii) le bonus de parrainage combiné à un bonus de résultat collectif de 50€/ha distribué à tous les participants si l'état de la rivière atteint un échelon supérieur de l'échelle de qualité de l'eau.

Les résultats suggèrent qu'en moyenne, les répondants préfèrent les contrats avec un bonus de parrainage aux contrats sans bonus. Ceteris paribus, cela correspondant à une réduction du consentement à recevoir de 40€/ha en moyenne pour un contrat avec un bonus de parrainage par rapport à un contrat sans. Les répondants sont en revanche moins favorables à la possibilité de cumuler le bonus de parrainage et le bonus pour le résultat collectif dans un même contrat.

Derrière ces résultats se cachent une hétérogénéité des agriculteurs. Une des limites à la généralisation des résultats est le biais d'échantillonnage en faveur de la population déjà la plus susceptible de souscrire un PSE et de mettre en oeuvre des SE ambitieux. Inspirés par une étude de cas française, nous étudions deux éléments de conception des PSE visant la réduction des émissions de méthane entérique dans les exploitations laitières qui sont cruciaux pour leur efficacité : le choix de l'indicateur d'émissions capturant l'effet des pratiques des agriculteurs, et le montant du paiement par rapport aux coûts supplémentaires de production de lait encourus. En utilisant les données publiques du RICA 2016-2018, nous comparons les émissions entériques calculées avec une méthode Tier2 telle que classifiée par le Groupe d'experts intergouvernemental sur l'évolution du climat (GIEC) aux émissions de références de la méthode utilisée dans le PSE Eco-Méthane tenant compte des effets du régime alimentaire.

Nous quantifions également les coûts de production laitière supplémentaires liés à l'intégration de plus d'herbe (un des leviers pour réduire les émissions par litre de lait) dans les systèmes fourragers en estimant des fonctions de coûts variables pour différents systèmes laitiers en France selon le bassin de production et le système fourrager.

Nos résultats montrent la pertinence de l'utilisation d'un indicateur d'émissions sensible aux effets du régime alimentaire, en particulier pour ne pas surestimer les émissions des exploitations avec une part importante d'herbe dans leur assolement fourrager. Nos estimations suggèrent que la plupart des exploitations présentent des surcoûts importants et élevés, en particulier les exploitations de plaine avec une part importante de prairies et les exploitations de montagne. Pour soutenir une transition à grande échelle, le niveau de paiement devrait être suffisamment élevé pour dépasser ces coûts, ou modulé en fonction du système laitier. Une des limites à la généralisation de nos résultats est que nous ne caractérisons l'hétérogénéité des coûts supplémentaires des exploitations pour réduire les émissions entériques que pour le levier spécifique de la place de l'herbe dans l'assolement fourrager, sans prendre en compte (par manque de données), des actions complémentaires telles que l'apport de compléments tels que le lin extrudé dans la ration. xiv Chapitre 5. Comment l'étiquetage santé peut-il améliorer la fourniture de biens publics environnementaux ?

Ce chapitre co-écrit avec Elodie Letort et Pierre Dupraz, s'intéresse à la question de la sousprovision des biens publics environnementaux par le marché. Les PSE inclus dans la chaîne de valeur visent à capter la CAP pour les SE des parties prenantes le long de la chaîne alimentaire, en différenciant les biens produits avec des pratiques respectueuses de l'environnement de ceux produits avec des pratiques dites "conventionnelles" et en introduisant une prime de prix.

Contrairement aux systèmes dédiés, les PSE inclus dans la chaîne de valeur peuvent non seulement mobiliser le CAP pour les SE, mais aussi pour le type de denrée agricole produit de manière jointe et toute autre caractéristique attachée à ce produit agricole pour laquelle les consommateurs peuvent avoir des préférences. Par conséquent, le développement de ce canal de paiement représente une opportunité d'obtenir des contributions supplémentaires (indirectes) des consommateurs à la fourniture de SE.

Cette étude se concentre sur le cas particulier où une jointure de production existe entre la fourniture d'un bien public environnemental global et l'amélioration de la qualité nutritive d'une denrée agricole, de manière à ce qu'il prodigue également des bienfaits supérieurs pour la santé par rapport à son substitut conventionnel. Nous adaptons un modèle de bien public impur inspiré de [START_REF] Kötchen | Impure public goods and the comparative statics of environmentally friendly consumption[END_REF] pour comparer un label environnemental, un label de santé et un label promouvant à la fois la santé et l'environnement, toujours sous l'hypothèse de cette jointure santé/environnement. Nous modélisons comment le degré d'information sur les caractéristiques publiques et privées fournies aux consommateurs affecte la fourniture de bien public à l'équilibre de marché. Une simulation est effectuée pour illustrer l'impact des préférences des consommateurs sur la fourniture de bien public.

Nous montrons que la fourniture de bien public est plus élevée avec un label de santé qu'avec un label environnemental dans la plupart des situations. L'ampleur de ce résultat dépend des préférences des consommateurs et de la taille du marché. Du point de vue d'un planificateur social, le bien public reste insuffisamment fourni dans tous les contextes de marché. Cependant, sous certaines conditions, un label de santé et un label de santé et d'environnement conduiront à la fourniture optimale du bien public du point de vue d'une agence environnementale. Une des limites à la généralisation de nos résultats est cette hypothèse de jointure forte et linéaire entre pratiques respectueuses de l'environnement et amélioration nutritionnelle de la denrée agricole. [START_REF] Heal | Agriculture and ecosystem services[END_REF][START_REF] Lichtenberg | Agriculture and the Environment[END_REF]Millennium Ecosystem Assessment, 2005;Therond et al., 2017).

List of abbreviations

Those carbon, nitrogen, phosphorus and water cycle disruptions affect climate and habitats with pollution and increased vulnerability to natural hazards (arrows A5-A6 in figure 1.1) (Abu [START_REF] Hatab | Agriculture, Forestry and Other Land Uses[END_REF][START_REF] Bezner Kerr | Food, Fibre and Other Ecosystem Products[END_REF][START_REF] Eea | EEA Signals 2019. Land and soil in Europe: Why we need to use these vital and 200 finite resources sustainably[END_REF]. In Europe, the agricultural sector is the second contributor to GHG emissions (EEA, 2022), the first contributor to diffuse water pollution (EEA, 2021), and often the main source of pressure on habitats and species (EEA, 2020a;IPBES, 2019). In return, both short and long-term effects of ecosystem degradation and climate change affect agricultural production capacities (Bezner [START_REF] Bezner Kerr | Food, Fibre and Other Ecosystem Products[END_REF].

The multiple interactions between farming activities and natural ecosystems make the agricultural sector both a producer of food commodities and a provider of public goods (and bads), for which the benefits (and damages) are available and accessible to many beyond the farm gates [START_REF] Cooper | The Provision of Public Goods through Agriculture in the European Union[END_REF]. Public goods include habitats for a diversity of species (farmland flora and fauna), long-term storage of carbon in soils and landscape features, and the protection of river catchments' soil and water quality (arrows A7-A8 in figure 1.1). Since the rise of global environmental concerns in the 1970s, scientists have built extensive knowledge of the interactions between farm systems and the environment, and on farmers' practices mitigating pressures on ecosystems [START_REF] Altieri | Agroecology: the Science of sustainable agriculture[END_REF][START_REF] Bezner Kerr | Food, Fibre and Other Ecosystem Products[END_REF]. With environmental concerns and solutions well identified, the challenge today is to upscale their adoption and to finance the transition. In addition, the EC aims at 25% of agricultural land under organic farming by 2030 (EC, 2020a[START_REF] Ec | EU Biodiversity Strategy for 2030[END_REF]. To meet these targets, one can build on existing regulations (ex: Directives) defining baseline standards of agricultural practices and protected areas for biodiversity since the 1970s.

They are the legal requirements farmers must comply with. In addition, incentive tools can be developed. The latter has been introduced in some of the Common Agricultural Policy (CAP)

instruments since the 1990s (Table 1.1). In particular, the CAP offers support payments to farmers adopting environment-friendly practices, including organic farming, beyond legal requirements and standards of good practices (Council of the European Communities, 1992a).

In addition, part of the direct payments per hectare farmers receive as income support depends on crop diversification and maintaining permanent grasslands and ecological focus areas since 2013 (EU, 2013a). So far, the regulations and the CAP have been insufficient in securing the delivery of the climate, biodiversity and water quality targets ( [START_REF] Pagiola | Payments for Environmental Services[END_REF]. PES are tools for meeting the supply and demand of agri-environment-climate public goods and aim at accompanying a largescale agroecological transition towards reaching better provision by the agricultural sector. Communities, 1979Communities, , 1986Communities, , 1991Communities, , 1992bCommunities, , 1992a;;EC, 2021a;EEA, 2020a[START_REF] Eea | Drivers of and pressures arising from selected key water management challenges. A European overview[END_REF][START_REF] Eea | Annual European Union greenhouse gas inventory 1990-2020 and inventory report[END_REF][START_REF] Eu | Directive 2000/60/EC establishing a framework for Community action in the field of water policy[END_REF][START_REF] Eu | Directive 2009/128/EC establishing a framework for Community action to achieve the sustainable use of pesticides[END_REF][START_REF] Eu | Directive 2009/147/EC on the conservation of wild birds[END_REF]EU, , 2013aEU, , 2013bEU, , 2013c[START_REF] Eu | Regulation (EU) 2021/1119 establishing the framework for achieving climate neutrality (European Climate Law)[END_REF]European Court of Auditors, 2021;United Nations, 2015).

In this introductory chapter, I present the main concepts and definitions around PES and provide a short literature review of the different types of PES mechanisms implemented in the European Union (EU). The review identifies some of the efficiency issues of current PES and which mechanisms could be implemented to overcome them. I then present the way I apprehend PES, and the research questions I develop throughout my PhD thesis.

Background

Characteristics of agri-environment-climate public goods

The public benefits provided by agriculture exhibit the intrinsic characteristics of public goods.

The utility individuals derive from their provision is interdependent [START_REF] Marmolo | A constitutional theory of public goods[END_REF].

The first axis for which one can differentiate public goods from other types of goods is that the consumption of one unit by an individual does not affect the consumption opportunities of other individuals of that same unit of good [START_REF] Samuelson | The Pure Theory of Public Expenditure[END_REF]. This characteristic is referred to as non-rivalry of consumption or indivisibility of benefits [START_REF] Cornes | Council Regulation (EC) No 73/2009 establishing common rules for direct support schemes for farmers under the common agricultural policy and establishing certain support schemes[END_REF]. A second axis differentiates the nature of goods according to whether some individuals can be excluded from the possibility of consumption. Excludability distinguishes two categories of goods with non-rivalry: non-excludable pure public goods and excludable club goods [START_REF] Sandler | Club Theory : Thirty Years Later[END_REF]. With complete non-excludability, consumption is mandatory for all individuals, while full excludability distinguishes a population with access to non-rival consumption and a population with no access to it [START_REF] Cornes | Council Regulation (EC) No 73/2009 establishing common rules for direct support schemes for farmers under the common agricultural policy and establishing certain support schemes[END_REF].

Typically, climate stability and biodiversity conservation to which agriculture contributes are pure public goods. Individuals enjoy the same level of availability (joint consumption), and cannot be prevented from accessing those benefits. Moreover, they are pure public goods at the global level (global public goods), as benefits have no geographical limit [START_REF] Stiglitz | Overcoming the Copenhagen Failure with Flexible Commitments[END_REF]. Some other public goods provided by agriculture are closer to club goods. It is the case of water quality or farmland landscape aesthetics, for which the distance to the provision site is a barrier excluding some individuals from its benefits (local public goods) [START_REF] Cooper | The Provision of Public Goods through Agriculture in the European Union[END_REF].

The special characteristics of public goods make them unlikely to be sufficiently provided through a competitive market. As demonstrated by [START_REF] Samuelson | The Pure Theory of Public Expenditure[END_REF], non-rivalry makes the conditions for the optimal provision of public goods to differ from private goods. Let us consider the objective function (1.1) of a social planner who wishes to determine the optimal amount of a public good 𝑌 maximising the social welfare of 𝐼 individuals. Each individual 𝑖 exhibits a utility functions 𝑈 𝑖 (𝑋 𝑖 , 𝑌) depending on the consumption level of a private good 𝑋 and benefits from the level of public good 𝑌. The economy is constrained by its production possibility representing how the production of 𝑋 and the provision of 𝑌 are related

(transformation function F). max 𝑌 𝑊[𝑈 1 (𝑋 1 , 𝑌), … , 𝑈 𝑁 (𝑋 𝑁 , 𝑌)] 𝑠. 𝑡 𝐹(∑ 𝑋 𝑖 𝑁 𝑖=1 , 𝑌) = 0 (1.1)
The first-order-conditions gives the Bowen-Lindahl-Samuelson (BLS) condition:

𝛼 𝑁 = ∑ 𝜕𝑈 𝑖 𝜕𝑌 𝜕𝑈 𝑖 𝜕𝑋 𝑖 = 𝜕𝐹 𝜕𝑌 𝜕𝐹 𝜕𝑋 𝑁 𝑖=1 (1.2)
At optimal provision, the marginal social benefit of providing the public good equals the sum of the marginal benefits received by all individuals, or the sum of the marginal rates of substitutions between the public good and the private good of all agents equals the marginal rate of transformation between the private and public goods. The economic theory identifies several reasons why intervention is required to meet equation (1.2) [START_REF] Tietenberg | Environmental and Natural Resource Economics[END_REF]. First, free access (absence of clear property rights) leads to the absence of the formation of a price through a competitive market (missing market). Second, the financing of public good provision suffers from free-riding. Unless constrained by a mandatory contribution, any individual 𝑖 voluntarily financing public good provision has the incentive to pay up to his or her marginal utility derived from 𝑌,

𝜕𝑈 𝑖 𝜕𝑌 𝜕𝑈 𝑖 𝜕𝑋 𝑖
, which is less than the optimal amount 𝛼 𝑁 as soon as 𝑁 ≥ 2. Hence, even if a market exists, the public good is underprovided.

To correct market failures, one needs to know the benefits and costs of public good provision and develops mechanisms to send a price signal to public good providers (farmers) and contributors aiming at satisfying equation (1.2). It requires understanding the supply and demand of agri-environment-climate public goods.

Characteristics of agri-environment-climate public good supply

Before the introduction of a correcting mechanism, the supply of public goods by agricultural activities is an externality associated with food production. An externality arises when "the effect of production […] imposes costs or benefits on others which are not reflected in the prices" (OECD, 2003). Typically, a farmer does not bear all the costs of pollution damages from farming activities, nor all the benefits of their amenities [START_REF] Coase | The problem of the Social Costs[END_REF][START_REF] Tietenberg | Environmental and Natural Resource Economics[END_REF]. The impacts of off-site (outside the farm gate) pollution and public benefits are not necessarily integrated into farmers' decisions. Sending a price signal supposes to translate public good provision in a way that it can be internalised by the producer. One way is to characterise and recognise the interactions between on-site farming practices and offsite public good provision.

Environmental services (ES) refer to human interventions contributing to the preservation of ecological functions (maintaining or developing ecosystem services) [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF].

According to the analytical framework of [START_REF] Puydarrieux | L'évaluation française des écosystèmes et des services d'écosystèmes[END_REF] [START_REF] Wunder | Payments for environmental services: some nuts and bolts[END_REF]. Moreover, while some ecosystem services (provisioning services) can directly be charged by suppliers in competitive markets, the notion of ES applies to externalities (FAO, 2007;[START_REF] Wunder | Revisiting the concept of payments for environmental services[END_REF]. ES are related, but also different from public goods. One can differentiate ES provided by farmers, and the offsite benefits they contribute to. Those offsite benefits are the agri-environment-climate public goods from which individuals derive utility. In simple terms, ES represent the supply by farmers, while public goods are what society ultimately demands.

The contribution of ES to public good provision is based on biological processes that are often spatially dependent and characterized by threshold effects [START_REF] Dupraz | Threshold effect and co-ordination of agrienvironmental efforts[END_REF][START_REF] Zavalloni | Agri-environmental Policies and Public Goods: An Assessment of Coalition Incentives and Minimum Participation Rules[END_REF]. This "transformation" depends on many factors: the type of ES itself and the intensity of environmental effort it represents, the continuity of ES in time and space, and more generally on external drivers (climate, natural conditions…) [START_REF] Alston | Payment for Environmental Services: Hypotheses and Evidence[END_REF][START_REF] Dupraz | Threshold effect and co-ordination of agrienvironmental efforts[END_REF]. [START_REF] Dupraz | Threshold effect and co-ordination of agrienvironmental efforts[END_REF] define a transformation function f such that:

𝑌 = 𝑓(∑ 𝑠 𝑗 𝐽 𝑗=1 , 𝑒) (1.3)
With 𝑌 the offsite environmental benefit (public good provision), 𝑠 𝑗 the surface dedicated to ES by farmer 𝑗 and e the environmental effort of the ES.

The existence or absence of threshold effects is linked to the concept of separability of public good provision. Public goods with a high degree of separability can be easily and efficiently provided by isolated farmers while the level of public good provision with a low degree of separability is strongly dependent on the practices of other farmers [START_REF] Falconer | Developing Co-operative Approaches to Agri-environmental Policy[END_REF][START_REF] Franks | The collective provision of environmental goods: A discussion of contractual issues[END_REF]. Examples of a high degree of separability are carbon storage or sequestration, and GES emissions reduction contributing to climate change mitigation [START_REF] Alston | Payment for Environmental Services: Hypotheses and Evidence[END_REF] Similarly, when a farmer maintains set aside areas and hedgerows, biodiversity gains are spatially limited and will depend on complex landscape arrangements and the existence of ecological corridors, as well as continuous effort over time (arrows A10 and A12 in figure 1.1) [START_REF] Alston | Payment for Environmental Services: Hypotheses and Evidence[END_REF]. For those public goods, [START_REF] Dupraz | Threshold effect and co-ordination of agrienvironmental efforts[END_REF] consider there is a critical effort 𝑒 0 and a critical cumulated area 𝑆 0 below which 𝑌 = 0.

In the microeconomic literature on agricultural production, ES are considered as a noncommodity output of the farm joint to the production of food commodities [START_REF] Shumway | Allocatable Fixed Inputs and Jointness in Agricultural Production: Implications for Economic Modeling: Reply[END_REF][START_REF] Vatn | Policies for Multifunctional Agriculture, the Trade Off between Transaction Costs and Precision[END_REF]. There is jointness in production when 'a firm produced two or more outputs that are interlinked so that an increase or decrease of the supply of one output affects the levels of the others' (OECD, 2001). For instance, some ES contributing to protecting water quality involves reducing nutrients and pesticide use, and can compete with crop yields [START_REF] Romstad | Multifunctional agriculture: implications for policy design[END_REF]. Grassland biodiversity tends to be complementary to grass-fed livestock products, at least over a certain range of production intensity [START_REF] Havlík | Joint production under 204 uncertainty and multifunctionality of agriculture: Policy considerations and applied analysis[END_REF]. Moreover, when ES involve putting some land out of production (ex: landscape features such as flower strips or hedgerows), their provision can compete with food production. Dedicating land to ES activities reduces the amount available for producing food [START_REF] Havlík | Joint production under 204 uncertainty and multifunctionality of agriculture: Policy considerations and applied analysis[END_REF]OECD, 2001).

The type of jointness defines whether joint production of agricultural commodities and ES can be implemented with or without additional costs for the farmer. In many cases, ES provision implies extra production costs, in particular opportunity costs [START_REF] Van Huylenbroeck | Multifunctionality of Agriculture: A Review of Definitions, Evidence and Instruments[END_REF].

Opportunity costs are defined as the "net benefit forgone because the resources providing the service can no longer be used in their next most beneficial use" [START_REF] Tietenberg | Environmental and Natural Resource Economics: sixth edition[END_REF]. As a result, market-led or policy-driven price signals affecting the production of food will affect ES provision and vice versa (OECD, 2001).

Characteristics of agri-environment-climate public good demand

Demand for agri-environment-climate public goods can arise from multiple sources and from local to global levels [START_REF] Madureira | Feasibility Study on the Valuation of Public Goods and Externalities in EU Agriculture[END_REF].

First, this demand can arise from citizens expressing their environmental preferences, for instance when voting. In this case, securing public good provision is delegated to a government, on behalf of the citizens (centralised demand at the national or local level) [START_REF] Samuelson | The Pure Theory of Public Expenditure[END_REF][START_REF] Tiebout | A Pure Theory of Local Expenditures[END_REF]. Second, there can be demand arising from voluntary initiatives of economic agents with diverse environmental preferences. These decentralised demands take the form of organisations willing to finance ES on behalf of citizens or interest groups, or individual or sectorial environment-friendly ventures following private interests [START_REF] Besley | Retailing public goods: The economics of corporate social responsibility[END_REF][START_REF] Gosal | Exploring ecosystem markets for the delivery of public goods in the UK[END_REF]. Third, customers with environmental preferences also express demand directly to farmers when purchasing food products produced jointly with ES. In the latter case, the expression of this demand depends on the information on joint production made available to consumers. To differentiate a food commodity produced with an environment-friendly production technology jointly providing ES from a conventional food substitute, microeconomic models of consumption consider it an impure public good [START_REF] Kötchen | Impure public goods and the comparative statics of environmentally friendly consumption[END_REF]). An impure public good exhibits both a private characteristic (food) and a public characteristic (ES provision) affecting the utility of consumers (arrows A13-A15 in figure 1.1) [START_REF] Cornes | The comparative static properties of the impure public good model[END_REF].

Payments for environmental services

Different instruments correct environmental externalities, from command and control measures to incentives ranging from Pigouvian taxation to Coasian private bargaining [START_REF] Vatn | An institutional analysis of payments for environmental services[END_REF]. In particular, [START_REF] Coase | The problem of the Social Costs[END_REF] suggests that under certain conditions, a contractual solution between the parties involved can efficiently solve a problem of externality [START_REF] Coase | The problem of the Social Costs[END_REF]. PES aim to put into practice the Coasian solution by issuing property rights to farmers for their provision of environmental services [START_REF] Engel | Designing payments for environmental services in theory and practice: An overview of the issues[END_REF]. They are part of the family of positive environmental incentives, based on the beneficiary-pays rather than the polluter-pays principle [START_REF] Engel | Designing payments for environmental services in theory and practice: An overview of the issues[END_REF][START_REF] Wunder | Payments for environmental services: some nuts and bolts[END_REF]. In particular, PES aims at meeting the demand and supply of agri-environment-climate public goods. Wunder (2015) defines PES as "voluntary transactions between service users and service providers that are conditional on agreed rules of natural resource management for generating offsite services". The most innovative feature of PES is the conditionality principle, making sure that the ES is delivered. It differentiates PES from subsidies. In many cases, the transaction involves an intermediary acting on behalf of (voluntary) service beneficiaries.

The literature gave rise to several alternative definitions. Some are very close to Wunder's (FAO, 2007;[START_REF] Karsenty | Payments for environmental services and development. Combining conservation incentives with investment[END_REF], while others add new conditions for PES qualification, such as environmental additionality [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF][START_REF] Tacconi | Redefining payments for environmental services[END_REF]. Additionality implies that the introduction of a PES leads to an observed improvement of public good provision compared with a scenario without a defined baseline [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF].

The aim of introducing a PES is to make privately unprofitable but socially desirable practices become profitable to farmers [START_REF] Engel | Designing payments for environmental services in theory and practice: An overview of the issues[END_REF]. A PES can only be implemented if the willingness to pay (WTP) of the transacting party(ies) paying for the service is higher than the willingness to accept (WTA) of the farmer(s), otherwise maintaining socially-undesirable practices would remain the most profitable option for farmers [START_REF] Engel | Designing payments for environmental services in theory and practice: An overview of the issues[END_REF]. The voluntary participation of the provider is an important criterion to reach an efficient outcome and gives the possibility to farmers who would be worse-off to opt out or renegotiate [START_REF] Engel | Designing payments for environmental services in theory and practice: An overview of the issues[END_REF][START_REF] Tacconi | Redefining payments for environmental services[END_REF]. In theory, the payment should be set between the WTA and the WTP (Alston et al., 2013) (Figure 1.2.). The WTP of a scheme financer is the value she or he attaches to the ES, and depends in particular on the level of underprovision and scarcity of the agrienvironment-climate public good it contributes to [START_REF] Engel | Designing payments for environmental services in theory and practice: An overview of the issues[END_REF][START_REF] Wunder | Payments for environmental services: some nuts and bolts[END_REF]. The WTA of a farmer is made of several components including opportunity costs, transaction costs, fixed costs, environmental awareness… [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF]. Depending on the conditionality rules of the PES, it can also include a risk premium for not meeting requirements despite high efforts (Zabel and Roe, 2009b). Due to jointness in production, ES provision often involves trade-offs with food production, and the PES should compensate for that [START_REF] Alston | Payment for Environmental Services: Hypotheses and Evidence[END_REF][START_REF] Wunder | Payments for environmental services: some nuts and bolts[END_REF]. The WTP should cover both the WTA of farmers and PES transaction costs (negotiation, monitoring, enforcement) [START_REF] Alston | Payment for Environmental Services: Hypotheses and Evidence[END_REF].

Source: [START_REF] Engel | Designing payments for environmental services in theory and practice: An overview of the issues[END_REF].

Review of existing PES in the EU and identification of inefficiency issues

In the next section, I review some existing PES in the EU, aiming at matching the supply and demand for public good provision by agriculture. To identify PES schemes from the literature, I use Wunder 2015's definition with the following adaptation to my research topic:

1) A transaction

2) Aiming at generating identified offsite services (agri-environment-climate public goods)

3) Between service users (that I call contributors) 4) To voluntary service providers (farmers)

5) Conditional on agreed rules

Similarly to Wunder, I do not add additionality as a condition. According to Wunder (2015), a PES definition must remain "robust to intertemporal variations in implementation".

Additionality means the successful provision of public goods by the PES, and can only be observed ex-post. Nevertheless, securing additionality is crucial for environmental effectiveness [START_REF] Tacconi | Redefining payments for environmental services[END_REF]. In addition, [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF] consider that a PES must create an incentive and the payment amount should go beyond compensation for the extra-costs of ES provision. As such a criterion rules out most of the existing public PES, I do not include it.

In the literature, one can alternatively read payment for environmental services and payment for ecosystem services. In reviewing the literature, I considered payment for ecosystem services as a synonym for payment for environmental services. However, following [START_REF] Puydarrieux | L'évaluation française des écosystèmes et des services d'écosystèmes[END_REF] and [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF], I systematically use the term environmental services to clarify that I refer to payments associated with human interventions and avoid any confusion.

I start my review by focusing on the main PES currently implemented in EU countries: the agrienvironment-climate measures (AECM). I summarise the main limits making them inefficient PES. I then characterise other types of PES that could allow for better matching of social demand and farmers' supply of agri-environment-climate public goods. [START_REF] Pagiola | Payments for Environmental Services[END_REF] distinguish two parts in a PES mechanism: the financing mechanism, which is how money is collected from contributors, and the payment mechanism, which is how the money is distributed to service providers. In reviewing the literature, I paid attention to these two dimensions in particular. Overall, the PES mechanism describes how the transmission of the payment is channelled, flows from contributors to farmers, and becomes a price signal.

Agri-environmental (-climatic) measures under the CAP

Since the major reforms of 1992, the CAP of the EU has dedicated parts of its funds to dealing with environmental issues through an agri-environmental policy [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF]. Agrienvironmental measures, agri-environment-climate measures since 2014 (AECM), are defined as "incentive-based instruments […] that provide payments to farmers for voluntary environmental commitments related to preserving and enhancing the environment and maintaining the cultural landscape" (EU, 2013c; [START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF]. AECM are a type of PES governed by public law [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF].

To participate, a farmer must voluntarily commit to change or maintain some agricultural practices for a period of 5 to 7 years (EU, 2005). In exchange, he or she receives an annual payment per unit of element engaged in the contract (surface, linear or point feature… The literature shows that the policy has had unsatisfactory results with regards to its objectives and expectations. Generally, but particularly in the areas with important public good underprovision, the participation rate in AECM is too low [START_REF] Desjeux | Les biens publics en agriculture, une voie vers l'écologisation de la PAC. Public goods in agriculture[END_REF][START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF]. In 2020, only 13% (excluding support to organic farming) of the EU utilised agricultural area (UAA) was under an AECM contract (EC, 2020c). The conditions (participation and effort) to reach ES provision thresholds and observe positive effects on the environment are therefore not met [START_REF] Zavalloni | Agri-environmental Policies and Public Goods: An Assessment of Coalition Incentives and Minimum Participation Rules[END_REF].

Payments are based on farmers' average forgone profits (opportunity costs) compared with local references of usual good farming practices for the considered geographical zone, and a small part of the private transaction costs for implementing AECM [START_REF] Dupraz | Effets des mesures agri-environnementales. Effects of agrienvironmental measures[END_REF].

They do not consider the variability of opportunity costs among farms, nor the uncertainties (prices volatility, yield variability). Moreover, most of the transaction costs such as social and human capital costs are not covered [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF]). Yet, the lack of know-how and transaction costs are an important adoption barrier [START_REF] Espinosa-Goded | Identifying additional barriers in the adoption of agri-environmental schemes: The role of fixed costs[END_REF].

Hence, one main factor of low participation in AECM is that the payment is a compensation, rather than an incentive, and the amount offered is below the WTA of most farms [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF]. Farmers with low opportunity and compliance costs are more likely to participate [START_REF] Cullen | Agri-Environment Scheme Design: Past Lessons and Future Suggestions[END_REF][START_REF] Zimmermann | European farms' participation in agri-environmental measures[END_REF]. In addition, bigger farms are advantaged as they can make economies of scale with transaction costs [START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF].

To sum up, a selectivity effect rules out potential AECM participants and areas. The payments do not include a component beyond the extra-costs of providing positive externalities (ES) that would also remunerate the intrinsic social value of ES. The main reason for that is that AECM were designed as green-box measures with no trade-distorting effects to comply with the World Trade Organisation regulations of the Uruguay round (1994). Therefore, AECM payments, as public policy instruments, can only include profit foregone and additional costs [START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF]. As a result, the compensation levels are sub-optimal and make the policy socially inefficient. [START_REF] Espinosa-Goded | Identifying additional barriers in the adoption of agri-environmental schemes: The role of fixed costs[END_REF] remind that taking a supply-side approach to determine the payment without considering social demand for ES can only lead to a sub-optimal allocation. The demand considered to decide of the relevance of implanting a specific measure in a specific area, estimate the budget allocated to the policy instrument and the payment level to farmers is not defined according to a target of socially optimal public good provision (Equation (1.2)). Rather, it is defined according to a target of improving a non-optimal provision, towards a state that likely remains sub-optimal [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF]). Yet, the overall budget allocated to AECM is particularly low in comparison with the CAP income support instruments with no or little environmental conditionality [START_REF] Dupraz | Environment and climate in the common agricultural policy[END_REF]European Court of Auditors, 2017;[START_REF] Grethe | For an EU Common Agricultural Policy serving the public good after 2020: Fundamental questions and recommendations[END_REF][START_REF] Matthews | Greening agricultural payments in the EU's common agricultural policy[END_REF].

Due to the selectivity effect, the environmental additionality of AECM is also hindered.

According to a review by [START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF], the main ecological effects evaluated were on biodiversity and often case-specific [START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF]. Most of the reported benefits were maintenance effects, rather than improvements. Moreover, 24% of the agrienvironmental measures evaluated by the European Court of Auditors in 2008 had no positive environmental effect demonstrated (European Court of Auditors, 2011).

Among the set of contracts farmers can uptake, the AECM chosen by the farmers are often the ones with relatively lower transaction costs, which also tends to prescribe ES with low environmental effort [START_REF] Dupraz | Effets des mesures agri-environnementales. Effects of agrienvironmental measures[END_REF]. In addition, there is a lack of connected network of plots under the same measure: lack of landscape scale results [START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF].

The lack of geographical targeting of the policy has been denounced [START_REF] Cullen | Agri-Environment Scheme Design: Past Lessons and Future Suggestions[END_REF]. There was an attempt to improve targeting by limiting some measures to specific areas. This change was mostly motivated by public expenditure savings and was accompanied by a decrease in compensation amounts, leading to no improvement (Dupraz et al., 2007). Scholars point out that while it is less costly to reach ecological thresholds in extensive agricultural landscapes, triggering the agroecological transition of intensive agricultural landscapes is more urgent to avoid more public bads [START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF]. Participation is particularly low in intensive production systems due to higher opportunity costs, while it is where ES are the most underprovided [START_REF] Zimmermann | European farms' participation in agri-environmental measures[END_REF].

A final criticism of AECM concerns the set of requirements (the ES farmers must provide) conditioning the delivery of the payment. The policy has been criticized for being too top-down in the design of its requirements [START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF]. Today, most AECM are prescriptions of a set of management activities (action-based payment) [START_REF] Cullen | Agri-Environment Scheme Design: Past Lessons and Future Suggestions[END_REF].

The contracts do not give incentives for dynamic adaptation of practices, hence there are no incentives for entrepreneurial creativity and the implementation of the most efficient ES for providing the desirable agri-environment-climate public goods [START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF].

The experience of AECM over the last 30 years highlighted key points regarding PES design.

Poorly designed instruments lead to low and scattered participation, and insufficient effort to reach environmental thresholds [START_REF] Dupraz | Threshold effect and co-ordination of agrienvironmental efforts[END_REF][START_REF] Zavalloni | Agri-environmental Policies and Public Goods: An Assessment of Coalition Incentives and Minimum Participation Rules[END_REF]. Low financing leads to self-selection of farms with low compliance costs and environmental additionality [START_REF] Cullen | Agri-Environment Scheme Design: Past Lessons and Future Suggestions[END_REF][START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF][START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF][START_REF] Zimmermann | European farms' participation in agri-environmental measures[END_REF]. Nevertheless, AECM are the CAP instruments the most targeted towards public good provision and with the best potential of providing environmental benefits [START_REF] Batáry | The role of agri-environment schemes in conservation and environmental management[END_REF][START_REF] Dupraz | Environment and climate in the common agricultural policy[END_REF]European Court of Auditors, 2020;[START_REF] Matthews | Greening agricultural payments in the EU's common agricultural policy[END_REF].

Diversity of payment for environmental services financing mechanisms

The financing mechanism of PES describes how contributions to finance PES are collected [START_REF] Pagiola | Payments for Environmental Services[END_REF].

The AECM from the CAP illustrate the first (and the main) observed type of public PES financing mechanism in the EU. Contributions are collected from EU taxpayers, and an intermediary public authority (EC and Member States) decides how to allocate the budget to policy instruments targeting agri-environment-climate public goods on behalf of the citizens.

Beyond AECM, organic farming support (OFS) (maintaining or converting to organic farming) follows the same mechanism [START_REF] Stolze | CAP 2014-2020: organic farming and the prospects for stimulating public goods[END_REF]. In addition, some of the contributions from taxpayers can be indirectly channelled towards PES through other CAP instruments, for instance through the LEADER programme [START_REF] Duval | Favoriser le déploiement des paiements pour services environnementaux en agriculture: Guide à destination des acteurs privés[END_REF]). Yet, the money allocated to finance environmental incentives is too low relative to the total CAP budget and its ambitions [START_REF] Dupraz | Environment and climate in the common agricultural policy[END_REF][START_REF] Matthews | Greening agricultural payments in the EU's common agricultural policy[END_REF].

Other types of financing mechanisms are developing in parallel to CAP instruments, and capture the willingness to pay of other contributors.

A second type of public financing mechanism involves local authorities and government agencies as intermediaries, collecting fees and taxes from whom Wunder (2015) [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF]. Due to their voluntary nature, the contributions collected through this mechanism are low. The certification of some carbonrelated PES and the official recognition of units of compensated GHG emissions (ex: Label Bas Carbone in France) might encourage more contributions in the future.

Private financing initiatives also arise without an intermediary. Some producer cooperatives developed their own PES (ex: Vignerons de Buzet paying voluntary vine growers for reducing insecticides use) [START_REF] Duval | Favoriser le déploiement des paiements pour services environnementaux en agriculture: Guide à destination des acteurs privés[END_REF]. Examples also exist from companies for which the business depends on natural resources and well-functioning ecosystem services (ex: Nestlé Waters having financed the transition of farmers to extensive practices) [START_REF] Perrot-Maitre | The Vittel payments for ecosystem services: a "perfect[END_REF].

Finally, a last type of private financing mechanism is purchasing agricultural commodities with the joint provision of ES in the market [START_REF] Wunder | Payments for environmental services: some nuts and bolts[END_REF]. The financing mechanism is a price premium charged to end consumers, while the initiator of the payment can be any operator of the value chain (retailer, distributor, brand owner…). In particular, there are now more and more eco-certified food products, although most remain niche markets. Some are official certifications (organic), while others are private brands (BBC, LU Harmony, La Nouvelle Agriculture, Haiecobois) [START_REF] Bottega | Public, private and nonprofit regulation for environmental quality[END_REF][START_REF] Duval | Favoriser le déploiement des paiements pour services environnementaux en agriculture: Guide à destination des acteurs privés[END_REF].

The main types of financing mechanisms identified from the literature are summarised with an example from France in Table 1.2. Other examples in the EU and beyond are available in [START_REF] Eichhorn | Deliverable 2.6: Catalogue of updated factsheets of European in-depth case studies[END_REF] and on the website of the CONSOLE H2020 project (https://consoleproject.eu/).

Purchasing budget

Price premium, based on the market price 13 billion € of sales revenue of the organic market in 2021. Source: own elaboration, using data from (Agence bio, 2022; Agences de l 'eau, 2022;Bleu-Blanc-Coeur, 2022a;DDT Ariège, 2020;[START_REF] Déprés | Contracting for environmental property rights: The case of Vittel[END_REF][START_REF] Perrot-Maitre | The Vittel payments for ecosystem services: a "perfect[END_REF].

Diversity of payment for environmental services payment mechanisms

The payment mechanism of PES describes how the money collected from contributors is distributed to farmers [START_REF] Pagiola | Payments for Environmental Services[END_REF]. In addition, some rules may frame how much farmers can receive. Following the identification of the main limits of AECM which are the absence of an incentive component in the payment and the dominance of action-based payments, I focus my review on the definition of the payment amount and the conditionality rules describing the type of ES farmers commit to provide to receive the payment in existing payment mechanisms.

With public PES, the payment is often an annual payment dedicated to ES provision fixed by an assessment of opportunity costs, during the length of a contract between a public authority and a farmer [START_REF] Espinosa-Goded | Identifying additional barriers in the adoption of agri-environmental schemes: The role of fixed costs[END_REF]European Court of Auditors, 2011;[START_REF] Illes | Innovative mechanisms for financing biodiversity conservation: experiences from Europe, final report in the context of the project[END_REF].

The payment amount is constrained by public law and cannot go much beyond profit foregone and extra-costs (cost-based approach) nor be differentiated from one farmer to another in the same local context [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF]. When the public budget is low, eligibility criteria to target recipients based on the likelihood of additionality are introduced (European Court of Auditors, 2011). It is the case for AECM participation in France, for which only farms from pre-defined areas are eligible (MAA, 2021a). Auction mechanisms are also implemented to select farmers offering the highest environmental benefits for a low WTA [START_REF] Klimek | Rewarding farmers for delivering vascular plant diversity in managed grasslands: A transdisciplinary case-study approach[END_REF][START_REF] Latacz-Lohmann | Auctions for Conservation Contracts: A Review of the Theoretical and Empirical Literature[END_REF].

Private PES have more flexibility for negotiation between the contributor (or the intermediary) and the farmer. Reaching a mutual agreement favours a payment amount which would go beyond a simple compensation, and include the covering of fixed costs and transaction costs [START_REF] Duval | Favoriser le déploiement des paiements pour services environnementaux en agriculture: Guide à destination des acteurs privés[END_REF]. In the case of the PES implemented by Nestlé Waters dedicated to the protection of water quality, the payment mechanism included a negotiation farm per farm [START_REF] Perrot-Maitre | The Vittel payments for ecosystem services: a "perfect[END_REF]. The bargaining power of farmers is facilitated by the definition of a collective supply of ES [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF]. Hence, some local initiatives emerge from bottomup approaches led by farmer groups proposing a collective supply of ES and a payment based on their WTA, to be met by potential financers [START_REF] Bailly | Se lancer dans une démarche de PSE avec des collectifs d'agriculteurs: enseignements méthodologiques du projet LabPSE. Starting a PES approach with farmers' collectives: methodological lessons from the LabPSE project[END_REF]. When the incentive is joint product market differentiation (value chain included PES), the payment mechanism is a price premium. What the farmer receives depends on the market equilibrium of supply and demand, and the distribution of the premium within the value chain. For instance, the premiums of the French "Bleu-Blanc-Coeur" (BBC) and the Dutch "On the way to planet proof" private labels distributed to dairy farmers are on average 20€/1000L (6-10% above standard milk price) [START_REF] Boadi | Mitigation strategies to reduce enteric methane emissions from dairy cows: Update review[END_REF][START_REF] Vermunt | Five mechanisms blocking the transition towards 'natureinclusive' agriculture: A systemic analysis of Dutch dairy farming[END_REF]. Similarly to dedicated PES, collective initiatives of farmers also increase the bargaining power of ES providers in the negotiation of the price premium with distributors and retailers in the value chain (ex: organic honey from the Stara Planina Mointain in Bulgaria) [START_REF] Eichhorn | Deliverable 2.6: Catalogue of updated factsheets of European in-depth case studies[END_REF].

The conditionality rules of the PES define how ES and their offsite public good provision benefits are assessed [START_REF] Muradian | Reconciling theory and practice: An alternative conceptual framework for understanding payments for environmental services[END_REF]. In current schemes, one can distinguish PES with obligations of means or action-based (the vast majority), and PES with obligations of results or result-based. In addition, PES can include obligations to individual farmers (individual approaches) or to a group of farmers (collective or landscape approaches).

Most PES contracts dedicated to ES (not included in the value chain), in particular public schemes, are action-based, and paid on a per-hectare basis for the implementation of specific prescribed practices or land use (Duval et al., 2019a;[START_REF] Grolleau | Designing watershed programs to pay farmers for water quality services: Case studies of Munich and New York City[END_REF][START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF]. Action-based PES have been criticized for their low environmental effectiveness (lack of a clear link between implemented ES and expected off-farm public good provision) (European Court of Auditors, 2011), low cost-effectiveness (farmers are paid regardless they provide public goods), and low attractiveness [START_REF] Burton | Exploring farmers' cultural resistance to voluntary agri-environmental schemes[END_REF][START_REF] Quillérou | Adverse selection in the environmental stewardship scheme: Does the higher level stewardship scheme design reduce adverse selection[END_REF].

Following recommendations from scholars and field-practitioners [START_REF] Pe'er | Action needed for the EU Common Agricultural Policy to address sustainability challenges[END_REF], resultbased payments are developing with promising outcomes [START_REF] Burton | Result-oriented agri-environmental schemes in Europe and their potential for promoting behavioural change[END_REF][START_REF] Chaplin | Developing payment-by-results approaches for agri-environment schemes: Experience from an arable trial in England[END_REF][START_REF] Klimek | Rewarding farmers for delivering vascular plant diversity in managed grasslands: A transdisciplinary case-study approach[END_REF][START_REF] Matzdorf | How cost-effective are result-oriented agri-environmental measures?-An empirical analysis in Germany[END_REF]. The conditionality rules of resultbased PES are such that farmers are paid for offsite environmental outcomes (actual environmental results), or an intermediary indicator of that outcome, and are left free to decide their farming practices [START_REF] Russi | Result-based agri-environment measures: Market-based instruments, incentives or rewards? The case of Baden-Württemberg[END_REF]. They present several advantages compared with action-based, reviewed by [START_REF] Herzon | Time to look for evidence: Results-based approach to biodiversity conservation on farmland in Europe[END_REF]. Result-based PES are particularly relevant when too little is known about the relationship between management practices and public good provision and/or when this information is expensive to get [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF]. Yet, a resultbased PES value farmers' ES on the condition that it is possible to attribute a change in the measured result to farmers' action [START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF]. The main obstacles to the implementation of result-based PES are increased risks for farmers and the difficulty to find a good environmental result indicator [START_REF] Massfeller | Farmers' acceptance of resultsbased agri-environmental schemes : A German perspective[END_REF]Zabel and Roe, 2009a). Public result-based PES were mostly developed for grassland biodiversity, with a payment per hectare meeting an environmental objective [START_REF] Andreoli | Deliverable D4.1: Modelling land tenure and land dynamics in AECPGs provision[END_REF][START_REF] Bartkowski | Payments by modelled results: A novel design for agri-environmental schemes[END_REF][START_REF] Eichhorn | Deliverable 2.6: Catalogue of updated factsheets of European in-depth case studies[END_REF][START_REF] Herzon | Time to look for evidence: Results-based approach to biodiversity conservation on farmland in Europe[END_REF][START_REF] Klimek | Rewarding farmers for delivering vascular plant diversity in managed grasslands: A transdisciplinary case-study approach[END_REF]. In the private sector, some PES targeting climate mitigation propose a payment proportional to reduced or stored tCO2eq, which is an internationally-recognised convention unit [START_REF] Duval | Favoriser le déploiement des paiements pour services environnementaux en agriculture: Guide à destination des acteurs privés[END_REF][START_REF] Eichhorn | Deliverable 2.6: Catalogue of updated factsheets of European in-depth case studies[END_REF].

Indicators for result-based PES for general biodiversity are more difficult to generalise and must be adapted to the local context [START_REF] Alston | Payment for Environmental Services: Hypotheses and Evidence[END_REF][START_REF] Landell-Mills | Silver bullet or fool's gold? A global review of markets for forest environmental services and their impact on the poor[END_REF]. Existing schemes use intermediate measures on umbrella species indicating a good state of conservation of the ecosystem or habitat [START_REF] Andreoli | Deliverable D4.1: Modelling land tenure and land dynamics in AECPGs provision[END_REF][START_REF] Bartkowski | Payments by modelled results: A novel design for agri-environmental schemes[END_REF][START_REF] Klimek | Rewarding farmers for delivering vascular plant diversity in managed grasslands: A transdisciplinary case-study approach[END_REF].

As for the organic label, value-chain included PES typically rely on obligations of complying with strict requirements on input-use and management practices (standards) which can be controlled and eventually certified by a third party [START_REF] Bruce | The production of eco-labels[END_REF][START_REF] Duval | Favoriser le déploiement des paiements pour services environnementaux en agriculture: Guide à destination des acteurs privés[END_REF][START_REF] Erickson | Ecolabels: The Link Between Environmental Preferences and Green Practices?[END_REF][START_REF] Van Amstel | Eco-labeling and information asymmetry: a comparison of five eco-labels in the Netherlands[END_REF]. While they are dominantly action-based, some operators of the supply chain include result-based top-ups to the farmer price premium if environmental indicators are improved [START_REF] Eichhorn | Deliverable 2.6: Catalogue of updated factsheets of European in-depth case studies[END_REF].

Similarly to result-based approaches, collective approaches have been tentatively emerging as a way to improve the environmental-effectiveness of PES. Currently, most PES are defined at the individual plot or farm scale. For public goods for which the provision is site-specific (biodiversity, water quality), landscape approaches favour reaching ecological thresholds. In the 2014-2020 CAP programming period, several collective AECM have emerged, mostly in the Netherlands [START_REF] Franks | The collective provision of environmental goods: A discussion of contractual issues[END_REF][START_REF] Verhulst | Direct and indirect effects of the most widely implemented Dutch agri-environment schemes on breeding waders[END_REF], but also, more scarcely, in other Member States such as in France, Germany, England or Wales [START_REF] Eichhorn | Deliverable 2.6: Catalogue of updated factsheets of European in-depth case studies[END_REF][START_REF] Franks | An assessment of the landscape-scale dimensions of land based environmental management schemes offered to farmers in England[END_REF][START_REF] Prager | Agri-environmental collaboratives for landscape management in Europe[END_REF]. The conditionality rules are such that the payment is delivered if a group of farmers from the same area (cooperative or association) meets the contract requirements rather than individual farmers. Beyond collective contracting, collective approaches can take various forms from coordination to collaboration in the implementation of ES (see review by [START_REF] Prager | Agri-environmental collaboratives for landscape management in Europe[END_REF]. In particular, those initiatives aim at ensuring spatial coordination of ES, such as continuity over adjacent plots to form ecological corridors, or over all the upstream lands of a watershed [START_REF] Alston | Payment for Environmental Services: Hypotheses and Evidence[END_REF][START_REF] Prager | Encouraging collaboration for the provision of ecosystem services at a landscape scale-Rethinking agri-environmental payments[END_REF][START_REF] Villamayor-Tomas | Types of collective action problems and farmers' willingness to accept agri-environmental schemes in Switzerland[END_REF][START_REF] Westerink | Collaborative governance arrangements to deliver spatially coordinated agrienvironmental management[END_REF]. Apart from pilot projects [START_REF] Bailly | Se lancer dans une démarche de PSE avec des collectifs d'agriculteurs: enseignements méthodologiques du projet LabPSE. Starting a PES approach with farmers' collectives: methodological lessons from the LabPSE project[END_REF], examples from the private sector are difficult to find. In the case of the PES by Nestlé Waters for its mineral water brand Vittel, the farm by farm negotiation process aimed at ensuring spatial agglomeration of environmental commitments, even though there was no collective incentive per se [START_REF] Perrot-Maitre | The Vittel payments for ecosystem services: a "perfect[END_REF]. The main obstacles to collective PES are increased risks for farmers whose payment depends on others' compliance, and the difficulties to create and maintain a group dynamic [START_REF] Prager | Agri-environmental collaboratives for landscape management in Europe[END_REF].

The review of the literature on PES mechanisms shows the diversity of financing mechanisms and payment mechanisms. Three main issues of mismatch between farmers' supply and social demand were identified with the current dominant PES (dedicated public schemes). First, the financing mechanisms do not capture enough WTP to meet farmers' WTA and favour a largescale adoption by farmers (low demand from contributors). Second, the payment mechanisms tend to focus on paying for individual on-farm practices, and do not favour environmental effectiveness and result in a low supply of public goods. Third, current public payment rules constrain the payment to be a compensation rather than an incentive, which makes the adoption of PES unprofitable to many farmers (low supply of ES). Some new types of PES let us foresee potential levers for improvements. Higher demand from contributors can be expressed by dedicating more public money to environmental instruments (upscaling dedicated public schemes), and/or developing financing mechanisms capturing private WTP (dedicated private PES or integrated into the food value chain). Moreover, the supply of public goods by farmers can be enhanced by integrating more result-based and collective approaches, to improve the environmental effectiveness of PES by conditioning the delivery of the payment to an off-farm environmental benefit (the public good provision for result-based, or a landscape achievement facilitating public good provision for collective).

Problem statement, objective and research questions

The general objective of my thesis is to analyse with theoretical and empirical approaches, the efficiency of two polar cases of PES: (i) the remuneration by public authorities of voluntary ES by farmers (dedicated public schemes), (ii) the creation of a label on an agricultural commodity aiming at remunerating an ES by consumers (schemes integrated in the value chain).

In my thesis, I decided to define an analysis grid according to two dimensions: (i) the targeting of the payment mechanism, and (ii) the financing mechanism mobilising the WTP of contributors. As seen previously from the literature review, more result-based approaches are encouraged to increase the environmental effectiveness of PES. The first axis allows us to situate a PES according to whether the payment is conditional on the means implemented by individual farms (targeting on farm practices) or on off-farm environmental benefit (targeting off-farm environmental public good) (Figure 1.3). For instance, it differentiates action-based AECM (ex: payment per hectare for not ploughing a grassland) from result-based PES (ex: Eco-Methane with a payment proportional to reduced enteric methane emissions per litre of milk).

I situate landscape approaches in the middle of this axis, as they are targeted towards off-farm achievements to favour reaching ecological thresholds for public good provision, but can include requirements of practices or environmental results depending on the scheme design.

The second axis classifies a PES according to whether it is financed by the taxpayer (mobilisation of an aggregated WTP on behalf of public good beneficiaries) or by voluntary contributors following their individual WTP (mobilisation of agent-oriented WTP directly by the agent itself) (Figure 1.3). In theory, for the former, public authorities intervene to aggregate individual WTP for the public good and define the payment to ES providers to reach optimal provision according to the BLS condition. In practice, the WTP and the payment set by the public authority may strongly differ from the optimum, because of budget constraints, other competing priorities, and the lack of information on environmental processes, consumers' WTP for public goods and farmers' WTA to provide ES. For the latter, the WTP of an individual agent (consumer) is financing the PES, suboptimally because of non-rivalry and the possibility of free riding. For public goods set aside by public policy, capturing the WTP of consumers might be better than nothing. For public goods insufficiently supported by public policies, it might complement poor funding. This second axis differentiates between the two polar cases of PES, which are the AECM financed via the CAP and the premium paid by consumers of a labelled product for the joint provision of ES. I summarise public dedicated PES that are not CAP instruments under "public PES", and private dedicated PES under "private PES". Based on this reading grid, I formulate four research questions I tackle in my PhD thesis.

In the next three chapters of the thesis, I evaluate different levers to upscale PES adoption by farmers, specifically addressing the limits and inefficiencies of current mechanisms identified in the previous sections: (i) increase the budget allocated to current public dedicated PES instruments in the CAP (chapter 2), (ii) introduce incentives for collective dynamics in the payment mechanisms when targeting public good provision with ecological thresholds effects (chapter 3), (iii) design result-based payment mechanisms (chapter 4). To complement limited public funding and insufficient voluntary contributions from private actors, I propose to capture more contributions from consumers by developing official labels with information on the private benefits (ex: health) from consuming agricultural commodities produced jointly with ES (chapter 5).

Research Question 1: Can AECM be upscaled by targeting more public money towards the provision of public goods?

Chapter 2 focuses on a scenario of changing the allocation of the CAP budget to target more taxpayers' money towards the provision of public goods. Today, environmental incentives are severely underfunded relative to income support payments (direct payments in the CAP), which limits their attractiveness to farmers. The hypothesis is that a shift in budget from direct payments to environmental payments would increase the voluntary adoption of ES without requiring additional funding from the taxpayer. Two effects are envisaged: (i) a direct effect of the increase in the budget allocated to environmental instruments, (ii) an indirect effect of the decrease in direct payments. Using French data from the Farm Accountancy Data Network (FADN), we simulate the effect of a transfer of 7.5% of direct payments to OFS and AECM.

The type of PES studied is located at the bottom left of the analysis grid, as the vast majority of PES financed by the CAP in France are action-based. Results suggest this mechanism increases participation in environmental schemes with decreasing returns relative to the budget increase.

The methodological approach can be adapted to evaluate different budget allocation scenarios and provides ex-ante elements on farmers' response to more targeted public support towards the provision of ES.

Another lever for better allocating contributions is the payment mechanism. One source of inefficiency in individual PES with action-based is that they pay for practices with no environmental additionality if the ES requested are not ambitious enough and/or not adapted to the public good targeted. Making all or part of the payment conditional on a relevant landscape approach including several farms when the targeted public good has threshold effects, or directly on an obligation of result, would allow greater environmental effectiveness.

I first focus on PES with a collective or landscape approach, which may be publicly and/or privately financed. Their performance in securing more public good provisions depends in particular on their acceptability by farmers. Introducing landscape-approach conditionality in the form of a bonus payment to trigger higher agglomeration and an off-site environmental result has the advantage of limiting the risks for farmers.

Research Question 2: Could a conditional bonus increase farmers' commitment and encourage them to exceed ecological thresholds?

Elaborating on [START_REF] Kuhfuss | Nudging farmers to enrol land into agrienvironmental schemes: The role of a collective bonus[END_REF], chapter 3 applies a choice experiment approach and aims at measuring farmers' preferences for a PES contract with a payment for which part of it is conditional on the sponsorship of other farmers on the territory (sponsorship bonus) and/or a collective environmental result (water quality improvement). Two hypotheses are underlying:

(i) the sponsorship bonus allows to recruit more farmers on the same territory and to increase ES commitments at the landscape scale, and therefore favours the provision of threshold public goods, (ii) the collaborative effect of the sponsorship bonus can be reinforced by a collective reward for the achievement of an environmental result on the territory. We propose higher levels of payment than what is currently proposed in AECM, considering that the involvement of other contributors (water bodies, municipalities, companies...) would allow financing beyond opportunity costs and get closer to farmers' WTA. Results show respondents prefer contracts with a sponsorship bonus to no bonus, but lower and heterogeneous preferences for the combined sponsorship/collective bonus for environmental achievement. We identify three behavioural patterns regarding the bonus option: indifference, acceptance and non acceptance.

We find the sponsorship bonus option can improve PES cost-effectiveness, and suggest the combined bonuses can be cost-effective insofar as the individual per-hectare payment remains high enough to secure an environmentally effective participation level.

I then explore the design of result-based dedicated PES. In theory, paying for results is the most targeted payment mechanism towards public good provisioning. Nevertheless, the environmental effectiveness of the payment is only assured if the result is precisely measured and properly remunerated.

Research Question 3: What are the technical elements to consider when defining a payment proportional to the environmental outcome?

Based on an existing PES with a result obligation, the Eco-Methane PES (Le [START_REF] Gloux | Cost of changing dairy cows' diet to reduce enteric methane emissions in livestock farms[END_REF], Chapter 4 explores the adoption of practices that reduce enteric methane emissions from dairy cows through the implementation of a payment conditional on the units of CO2 equivalents reduced per litre of milk. We show the importance of taking into account the herd's grass feed intake (i) in the choice of the emissions indicator defining the unit of payment to accurately measure the ES, (ii) in the definition of the level of payment to take into account the difference in the additional cost of a change in dairy cow diet. Our results show the relevance of using an emission indicator sensitive to diet effects, and that French dairy systems in mountains and plain areas with already a large share of grasslands would face high and significant extra-costs for adding more grass to the feed ration. We stress the importance of developing PES with welldefined environmental indicators and funding requirements accounting for the technical problem addressed.

Finally, I turn towards PES integrated into the value chain to capture consumers' WTP. Since consumer contributions are voluntary, economic theory shows that eco-labels (and other private schemes) are inefficient instruments because individuals finance up to their own individual marginal utility without considering the utility of other non-rival consumers. However, the opportunity offered by labels is that consumers can express their WTP for all product characteristics. Some practices providing ES also improve the quality of the joint agricultural product (ex: enriching dairy cow rations with grass fodder both reduces enteric methane emissions and enriches milk in omega-3 fatty acids), for which consumers also have a WTP.

Research Question 4: Does labelling on the complementary provision of private benefits increase the effectiveness of ecolabels?

In the fifth chapter of the thesis, we focus on the case where the provision of ES is complementary to the production of an agricultural product providing health benefits. We develop a theoretical model of impure public goods adapted from [START_REF] Kötchen | Impure public goods and the comparative statics of environmentally friendly consumption[END_REF] to study the provision of a global public good through three labels (environmental label, health label, health and environment label), and derive the optimality conditions according to the objectives of a social planner, an environmental agency or a health agency. We show that higher public good provisioning occurs through a health label than an environmental label in most situations. The extent of this result depends on the consumers' preferences and the market size. The public good remains underprovided in all market settings from the perspective of a social planner.

However, under certain conditions, a health label and a health and environment label will lead to the optimal provisioning of the public good from the perspective of an environmental agency.

Outline of the PhD thesis

My PhD thesis is organised into six chapters. Chapter 1 is this general introduction.

Chapter 2. Upscaling environmental incentives in the Common Agricultural Policy: an ex-ante evaluation method applied with the Farm Accountancy Data Network

In this chapter, I assess the adoption of environmental incentives in the framework of the Common Agricultural Policy (CAP). Agri-environment-climate measures (AECM) and support to organic farming (OFS) are the two main instruments supporting environmental services in the European Union (EU) since the early 1990s. They have been insufficient in reaching significant environmental improvements, in particular, because they are under-funded in comparison with income support instruments with no or little environmental conditionality (direct payments).

In this study, I aim at evaluating the lever of better targeting the CAP public budget towards instruments for public good provision. Using France's panel data of the farm accountancy data network (FADN), I develop an ex-ante evaluation method at the national scale describing farms' AECM and OFS adoption and simulate a change of budget allocation between direct payments and environmental incentives. First, I apply a generalised Tobit model estimating the probability of environmental contract adoption and the minimum farm level payment triggering adoption (acceptable payment) using 2015-2019 panel data. Second, I simulate a 7.5% shift in budget from direct payments to OFS and AECM in 2019.

This chapter was co-authored with Pierre Dupraz (INRAE, SMART), and involved the following individual contributions: Fanny Le Gloux: conceptualisation, formal analysis, investigation, methodology, validation, original draft; Pierre Dupraz: conceptualisation, methodology, supervision, validation. A preliminary version of the model was used to simulate a scenario for the new CAP 2023-2027 for which the results were published in [START_REF] Chatellier | The sensitivity of the income of French farms to a reorientation of aid under the future post-2023 CAP[END_REF]. Preliminary results were also presented at the 9th Annual Conference of the French Association of Environmental and Resource Economists (8th-9th September 2022 in Rouen, France). The analyses contributed to the deliverables D3.1 [START_REF] Dupraz | Deliverable D3.1: The participation of farmers in innovative contract solutions based on secondary data analyses[END_REF] of the CONSOLE H2020 project (https://console-project.eu/).

Introduction

The European Union (EU) adopted ambitious environmental targets by 2030 and 2050, in particular on the development of organic farming to reach 25% of organic agricultural land by 2030. Following the definition of the Biodiversity Strategy for 2030 and the Farm to Fork Strategy for the agricultural and food sectors, rethinking the design of the Common Agricultural Policy (CAP) and its instruments is central to trigger the large-scale agro-ecological transition of farming systems (EC, 2020a[START_REF] Ec | EU Biodiversity Strategy for 2030[END_REF].

The agricultural sector accounted for 10% of the EU's greenhouse gas (GHG) emissions for the period 1990 to 2018 and is the second largest contributor after the energy sector (EEA, 2020b).

The continuous intensification of agricultural activities also contributed to natural habitat degradation and dramatic biodiversity decline [START_REF] Dasgupta | The Economics of Biodiversity: the Dasgupta Review[END_REF]. Behind the concept of agroecological transition lies the idea of moving away from agricultural practices harming ecosystem services, in particular the systematic use of chemical inputs, towards farming systems maintaining or supporting them (Millennium Ecosystem Assessment, 2005). Many levers at various scales can foster this transition. An important one is a better targeting of agricultural support to make agro-ecological farming more profitable than conventional farming (FAO et al., 2021).

The CAP represented 36% of the 2019 EU's budget (58.4 billion euros) (EC, 2019) and is the main EU policy supporting environment-friendly farming practices. Environmental incentives are offered in two voluntary 5-year contractual schemes of the rural development pillar of the CAP: (i) support to organic farming (OFS), and (ii) agri-environment-climate measures (AECM). OFS are area-based payments to eligible farms undertaking a conversion towards OF, or to eligible certified organic farms for maintaining their organic practices. This instrument has proven to be effective in maintaining the relative competitiveness of organic farming and is a major driver of the sector development [START_REF] Casolani | Evaluating the effects of European support measures for Italian organic farms[END_REF][START_REF] Sanders | Use and efficiency of public support measures addressing organic farming[END_REF]. AECM are area-based payments to eligible farms complying with a set of management requirements targeting an environmental objective such as the maintenance of biodiversity or the improvement of water quality. They are the CAP instrument the most targeted towards public good provision [START_REF] Batáry | The role of agri-environment schemes in conservation and environmental management[END_REF][START_REF] Dupraz | Environment and climate in the common agricultural policy[END_REF]European Court of Auditors, 2020;[START_REF] Matthews | Greening agricultural payments in the EU's common agricultural policy[END_REF]. The literature shows that after 30 years of existence, the voluntary environmental schemes of the CAP are unsatisfactory to improve the state of the environment.

The lack and unbalanced funding, as well as poorly designed instruments, led to insufficient participation and effort to reach environmental thresholds [START_REF] Dupraz | Threshold effect and co-ordination of agrienvironmental efforts[END_REF][START_REF] Dupraz | Effets des mesures agri-environnementales. Effects of agrienvironmental measures[END_REF][START_REF] Espinosa-Goded | Identifying additional barriers in the adoption of agri-environmental schemes: The role of fixed costs[END_REF][START_REF] Zavalloni | Agri-environmental Policies and Public Goods: An Assessment of Coalition Incentives and Minimum Participation Rules[END_REF]. In 2020, only 13% of the EU's UAA was under an AECM contract, and 6% under an OFS contract (EC, 2020c[START_REF] Ec | Environment and Climate Action (Summary)[END_REF].

The budget allocated to environmental contracts is low in comparison to income support payments (direct payments), the latter including little restrictions on agricultural practices [START_REF] Dupraz | Environment and climate in the common agricultural policy[END_REF]European Court of Auditors, 2017;[START_REF] Grethe | For an EU Common Agricultural Policy serving the public good after 2020: Fundamental questions and recommendations[END_REF][START_REF] Matthews | Greening agricultural payments in the EU's common agricultural policy[END_REF]. In 2019, direct payments accounted for 69% of the CAP budget (40.5 billion euros), while 8.6% (3.5 billion euros) was allocated to OFS, AECM and Natura 2000 sites altogether [START_REF] Ec | Definitive adoption 2019/333 of the European Union's general budget for the financial year 2019[END_REF].

Environmental benefits imply high uptake of environment-friendly practices. This can be done by more targeted support and less "untargeted" support. Rather than increasing the CAP budget to raise environmental incentives, many argue in favour of rebalancing the budget allocation [START_REF] Dupraz | Environment and climate in the common agricultural policy[END_REF][START_REF] Matthews | Greening agricultural payments in the EU's common agricultural policy[END_REF]. Since the 2014-2020 CAP programming period, Member States have the flexibility to transfer up to 15% of their direct payments budget to increase support to rural development measures, including OFS and AECM (EU, 2013a). In France, 7.5% of direct payments have been redirected since 2017 (MAA, 2021b). In this study, we aim at simulating further reorientation specifically towards the environmental contracts of the rural development pillar in France. It has been one of the scenarios for the CAP 2023-2027, preliminarily evaluated by [START_REF] Chatellier | The sensitivity of the income of French farms to a reorientation of aid under the future post-2023 CAP[END_REF]. Although the negotiations ruled out this option for the CAP 2023-2027, a similar mechanism will dedicate 25% of direct payments to finance a new instrument (eco schemes) open to all farmers and supporting the voluntary implementation of environment-friendly measures (generally less ambitious than OFS or AECM contract requirements) (EC, 2021b;[START_REF] Runge | Implementation of Eco--schemes in Fifteen European Union Member States[END_REF].

Our first contribution is an ex-ante evaluation method of the transfer mechanism from direct payments to environmental contracts. In particular, we model the impact on adoption. To our knowledge, the effect of such a budget transfer has not yet been assessed at the farm level and for an allocation targeting environmental contracts specifically. Previous ex-ante evaluations of the reorientation of direct payments used the CAPRI (Common Agricultural Policy Regionalised Impact) partial equilibrium model [START_REF] Himics | Setting Climate Action as the Priority for the Common Agricultural Policy: A Simulation Experiment[END_REF][START_REF] Schroeder | Quantitative modelling of the Rural Development Programs of the Common Agricultural Policy -EU-wide and region-specific effects[END_REF][START_REF] Schroeder | The Impact of Pillar II funding: Validation from a Modelling and Evaluation Perspective[END_REF], or linear programming [START_REF] Giannakis | Modelling the impacts of alternative CAP scenarios through a system dynamics approach[END_REF] Beyond a direct positive effect on the participation of an increased budget available to finance environmental contracts, one can expect an indirect effect of lower income support on farmers' response to environmental incentives. Monetary aspects from different sources, including direct payments, are important drivers of the decision to adopt AECM and organic farming [START_REF] Darnhofer | A relational perspective on the dynamics of the organic sector in Austria, Italy, and France[END_REF][START_REF] Jaime | Interactions between CAP Agricultural and Agri-Environmental Subsidies and Their Effects on the Uptake of Organic Farming[END_REF][START_REF] Sanders | Use and efficiency of public support measures addressing organic farming[END_REF][START_REF] Van Herzele | Effort for money? Farmers' rationale for participation in agrienvironment measures with different implementation complexity[END_REF]. [START_REF] Allaire | Spatial diffusion and adoption determinants of European agri-environmental supports related to extensive grazing in France[END_REF] and [START_REF] Pufahl | Evaluating the effects of farm programmes: Results from propensity score matching[END_REF] found different effects of direct payments coupled to production on participation in AECM, with an overall positive effect in Germany, and a marginal or negative effect in France for extensive grassland measures. Moreover, a positive effect of the decoupling of direct payments on the adoption of organic farming was found in Sweden [START_REF] Jaime | Interactions between CAP Agricultural and Agri-Environmental Subsidies and Their Effects on the Uptake of Organic Farming[END_REF]. Our second contribution is to capture the effect of direct payments on the contract adoption decision and acceptable payment in France under the 2014-2020 CAP framework.

The remaining of the paper is organised as follows. Section 2.2 presents the theoretical framework and econometric model of environmental contract adoption, the data and the procedure to simulate a reorientation of CAP budget. Section 2.3 describes the estimated econometric models. Section 2.4 presents the simulation results. Finally, section 2.5 discusses the findings and draws some conclusions.

Materials and methods

Our methodological approach to simulate a change in CAP budget allocation comprises three steps:

1. Estimation of the model of voluntary contract adoption under the current budget allocation.

2. Prediction of new probabilities and acceptable payments with a reduction of direct payments.

3. Starting from the farm with the highest probability to participate, allocation of the initial instrument budget plus an additional amount from the direct payments budget to participants, up to their estimated acceptable payment, until the budget is exhausted.

Theoretical model of voluntary adoption of an environmental contract

We represent the demand for environmental commitments from authorities during a CAP programming period by a function 𝜃(𝑀, 𝐵, Γ) describing a set of contracts 𝑀, a total budget 𝐵, We assume the supply of environmental commitments by farmers is driven by the profitability of adoption and eligibility. The decision 𝐷 𝑖 * of farmer 𝑖 to participate and the binary participation 𝐷 𝑖 are defined as follow:

𝐷 𝑖 = { 1 𝑖𝑓 𝐷 𝑖 * ≥

Econometric model of voluntary adoption of an environmental contract

Following the theoretical framework, we aim at estimating a model of adoption of AECM and OFS during a CAP programing period proposing the menu of contracts 𝑀. Due to the censored nature of the farm-level payment, an estimation of the acceptable payment with least squares methods is not applicable. We apply a generalised Tobit model [START_REF] Amemiya | Tobit models: A survey[END_REF][START_REF] Wooldridge | Econometric analysis of cross section and panel data[END_REF] in Equation (2.6).

The latent continuous variable 𝐷 𝑖𝑡 * is estimated with a Probit regression model with the binary variable 𝐷 𝑖𝑡 as dependent variable over the sample of participants and non-participants. The acceptable payment is estimated for each farm of the sample based on the estimation of the censored equation (2.4) using the participating farms. We do not impose an upper limit to the estimated acceptable payments to capture the behaviour of farmers requiring a strong financial incentive to participate. We impose that acceptable payments cannot be lower than 300€, which is the minimum required by French public authorities to start a contract [START_REF] Maa | Instruction technique relative aux Mesures AgroEnvironnementales et Climatiques et aux aides en faveur de l'agriculture biologique de la période 2015-2020[END_REF].

The Tobit regression model provides estimated coefficients of the effect of the explanatory variables on both the decision to participate in an environmental scheme and the farm-level acceptable payment triggering participation. The marginal effects of each variable are evaluated at sample means so that coefficients can be more easily interpreted.

Data

The French Metropole FADN data for the years 2015 to 2019 were used for the analysis. The data were accessed within a secured environment offered by the CASD (centre d'accès sécurisé aux données', Ref. 10.34724/CASD), and represent an unbalanced panel of 36,251 farm observations, including information on the payment received from AECM and OFS. The dataset does not include information on the surfaces enrolled in each contract, nor on the specific measures adopted. The national FADN is designed to be representative of medium and large farms contributing to more than 90% of the gross production and utilised agricultural area (UAA), and covers the scope of 65% of all farms [START_REF] Agreste | Réseau d'information comptable agricole (RICA) -Exercice 2019. Farm accountancy data network -2019[END_REF]. This data source is therefore particularly relevant for ex-ante CAP evaluations.

From 2015 to 2019, a total of around 1.6 billion was allocated to the farms of our sample for engaging in AECM and OFS (Table 2 1 Cumulated payments are weighted by the extrapolation coefficient of each observation. 2 To compute the real instrument budget for year t, we added the delayed payments distributed in year t+1 or t+2. Some of the direct payments for year t (maximum 0.2%) were distributed in t+1 for 2015, 2016, 2017, 2018 and 2018, and in t+2 for 2015 and 2017. Some AECM and OFS payments were distributed in t+1 for 2018 and 2019 (maximum 8.0%). We could not correct for 2019 instrument budgets distributed in 2021 (data not available). Source: 2015-2020 French FADN data.

Regarding the farm economic context (𝑒 𝑖𝑡 ), we control for the effect of CAP direct payments by including the amount of decoupled direct payments received per hectare (decoupled payment). We control for the amount of direct payments for suckler cows at the farm level (coupled payment for suckler cows) as it is the production receiving the highest coupled support in France. We further control for the cost of land lease per hectare of UAA (land lease), and the observed fuel and lubricant price of the farm (fuel price), the only variable input price that can be computed with FADN data. Fuel price is likely correlated to other farm input prices on the market (mineral fertilisers), and is an indicator of opportunity costs from adopting less input-intensive agricultural practices. When fuel price is not observed for a given observation (8.4% of the sample), we replace it with the mean of the observed fuel prices from the other years for the same farm (3.3% of the sample), or the annual mean of the sample (5.1% of the sample).

Accounting for farm and farmer characteristics (𝑘 𝑖𝑡 ) captures heterogeneous difficulties to meet contract requirements and preferences. We control for economic size (standard gross production), UAA (utilised agricultural area), total labour per hectare of UAA (labour), the share of rented land (rented UAA), assets depreciation per hectare of UAA (depreciation) and for the reception of LFA payment (LFA). We account for farm specialisation (1 dummy per technical orientation or group of technical orientations). Farmers' characteristics are age (age) and education (general education and agricultural education).

Additional explanatory variables were included to control for eligibility to specific environmental measures (𝛾 𝑖𝑡 ) and exclusion (Γ 𝑖𝑡 ) of the set 𝑀 defined by public authorities in the CAP 2014-2020 programming period. Most AECM are implemented at the local level and designed specifically for some land use or areas with high natural value. We control for the share of permanent grasslands in the UAA (permanent grasslands), and the load of grazing livestock per hectare (grazing livestock density). OFS eligibility depends on the region, with some not proposing maintenance OFS in all or part of their territory. We therefore account for farm location (1 dummy variable per region). Moreover, we add a dummy equals to 1 if half of the farm's UAA is located in a Natura2000 area (Natura2000), and one dummy variable equals to 1 if the farm is certified organic (organic certification). Controlling for organic certification captures the effect of eligibility to maintenance or conversion OFS, as only certified organic farms can apply to the former. To control for past participation, we estimate the model with 2016-2019 observations, and use 2015 data to construct a variable equals to 1 if the farm participated in AECM in 2015, 0 otherwise (observed participation in AECM in 2015), and a variable equals to 1 if the farm participated in OFS in 2015, 0 otherwise (observed participation in OFS in 2015). In addition, we capture part of the interaction between OFS and AECM uptake by controlling for observed participation in AECM (OFS respectively) at time 𝑡 -1 when estimating the decision to participate in OFS at time 𝑡 (AECM respectively) (observed participation in AECM at t-1 and observed participation in OFS at t-1). For model identification, we exclude this latter variable from the simultaneous outcome equation. We have unbalanced panel data and information on past participation is missing for observations which were not sampled the year before.

Finally, we control for year fixed effects.

Descriptive statistics of the covariates are presented in Table 2.2 and Appendix A2.

Simulation of CAP budget transfer

We simulate the impact on contract uptake of increasing the budget allocated to AECM and OFS while decreasing direct payments in 2019. On the side of the demand for environmental commitments, it corresponds to a change of demand 𝜃, such that the new budget in 2019 is 𝐵 19 + 𝐵 ̃19 . Direct payments distributed to the sample in 2019 (𝐷𝑃 19 ) accounted for 6.7 billion €. The 2019 CAP budget already includes a 7.5% transfer to rural development measures (MAA, 2021b). We first assume an additional transfer of 7.5% to reach 15%, which is the maximum rate allowed under current CAP regulations. The additional budget 𝐵 ̃19 = While keeping the budget ratio among instruments (53% to AECM and 47% to OFS), we also conduct additional simulations to identify the rate of budget transfer that would result in enough conversion OFS uptake to reach the target of 25% of the organic area in France.

Estimated model of AECM and OFS uptake

To evaluate the model quality, we compare observed participation and farm-level payments in 2016-2019 to predicted probabilities of participation and acceptable payments (Table 2.3). The AECM adoption model tends to underestimate the probability to participate in AECM.

Estimated acceptable payments are in the range of the observed farm-level payments of participants on average, although the standard deviation is lower, suggesting the model does not capture well extreme values. The OFS adoption model better captures the probability to participate, on average for the sample and in particular for maintenance OFS. The acceptable payment of participants is lower than observed farm-level payments on average, particularly for conversion OFS. Similarly to AECM, the model does not capture well the more extreme values. The difference between estimated data and observed data can be partly explained by missing data on exclusion criteria (omitted variable bias). In particular, the absence of information on whether the farm is located in an agri-environment-climate project area may largely explain why the probability of AECM participation is underestimated. Moreover, the difficulty in estimating the AECM acceptable payment of participating farms can be explained by the heterogeneity of AECM payments per hectare and the surfaces enrolled by those farms.

Similarly, it seems there are important factors explaining participation in conversion OFS that the model does not capture. The estimated effects describe the equilibrium of supply and demand of environmental commitments during the 2016-2019 period. The effect of each factor is a net effect and captures both the effect of the demand 𝜃(𝑀, 𝐵, Γ) each farm faces (amount of contracts, specific measures and payments each farm is eligible to) and the effect of the characteristics 𝑧 𝑖𝑡 = (𝛾 𝑖𝑡 , 𝑘 𝑖𝑡 , 𝑒 𝑖𝑡 ) of the supplying farms making them more or less likely to find participation profitable (opportunity costs, fixed costs). The effect of demand on the one hand, and supply on the other hand, cannot be isolated. The correlation estimates ρ of the selection and outcome equations are significant in both models. In particular, ceteris paribus, the acceptable payment for adopting AECM decreases with a higher probability of participation, while the acceptable payment for adopting OFS increases with a higher probability of participation.

The effects of covariates on AECM and OFS acceptable payments are difficult to interpret due to the high heterogeneity of contract requirements and payments per hectare, and we can only formulate hypotheses. A positive effect on acceptable payments might reveal either a higher payment per hectare or a higher amount of land to enroll to trigger participation. The estimated marginal effects of the explanatory variables on the adoption decision can more easily be confronted to the literature.

The farm economic context significantly explains the adoption behaviour of farms. Regarding our main covariates of interest, we observe the probability to participate in OFS significantly increases with decoupled payments per hectare and decreases with coupled payments for suckler cows. The marginal effects are low on average (+0.01% per 100€/ha of decoupled payments and -0.1% per 1,000€ coupled payments for suckler cows at the farm level).

Regarding AECM, the probability of adoption significantly increases with the amount of coupled payments for suckler cows (+0.1% per 1,000€ of coupled payments for suckler cows at the farm level), while the effect of decoupled payments per hectare is not significant. Both decoupled and coupled direct payments significantly increase the acceptable payment of OFS and AECM. The model suggests the effect of coupled direct payments for suckler cows is stronger on AECM acceptable payments (+167€ per 1,000€) than OFS acceptable payments (+29€ per 1,000€). Decoupled direct payments tend to increase more OFS acceptable payments (+122€ per 100€/ha) than AECM acceptable payments (+33€ per 100€/ha). Our model shows that farmers receiving more direct payments adopt environmental contracts for a higher farmlevel payment ceteris paribus. As expected, the probability to adopt both schemes increases with the price of fuel (higher relative profitability of adoption of less input-intensive practices).

A higher fuel price also tends to increase AECM acceptable payments, while it does not significantly affect OFS acceptable payments. We find that the effects of the land lease on the adoption decision are similar for AECM and OFS: the higher the cost of land lease per hectare, the lower the probability to participate. This suggests that having access to more productive agricultural land (with higher rent) makes it less economically profitable to dedicate it to environment-friendly production. The effect of direct payments on the OFS adoption decision confirms [START_REF] Jaime | Interactions between CAP Agricultural and Agri-Environmental Subsidies and Their Effects on the Uptake of Organic Farming[END_REF], who show that the decoupling of income support has favoured the adoption of organic practices, while coupled income support was a barrier. In the literature, the effect of coupled support on AECM adoption depends on the study [START_REF] Allaire | Spatial diffusion and adoption determinants of European agri-environmental supports related to extensive grazing in France[END_REF][START_REF] Pufahl | Evaluating the effects of farm programmes: Results from propensity score matching[END_REF]. Our results confirm those of [START_REF] Pufahl | Evaluating the effects of farm programmes: Results from propensity score matching[END_REF] in Germany. We interpret the effect of direct payments on AECM adoption as resulting from the higher set of AECM contracts designed for grazing livestock farming systems, more likely to have suckler cows on farms (MAA, 2020). The effect of the land lease on the adoption decision is also coherent with the literature [START_REF] Andreoli | Deliverable D4.1: Modelling land tenure and land dynamics in AECPGs provision[END_REF][START_REF] Pufahl | Evaluating the effects of farm programmes: Results from propensity score matching[END_REF] Regarding farm and farmer characteristics, we find that the farm's economic size, UAA, depreciation costs, the share of rented land, farmer's age and general education affect similarly the decision to adopt AECM or OFS. We observe a negative effect of the economic size (standard gross production). It suggests that participation is less profitable for farms with a high potential of production (high opportunity costs to adopt less intensive practices). The bigger the farm UAA, the higher the probability to adopt a contract (economies of scale), while depreciation costs per hectare are an economic barrier. Our model suggests a positive effect of the share of rented land on the probability to adopt an environmental contract. Moreover, younger farmers with high general education are more likely to adopt an environmental contract. These findings are coherent with the literature [START_REF] Allaire | Spatial diffusion and adoption determinants of European agri-environmental supports related to extensive grazing in France[END_REF][START_REF] Andreoli | Deliverable D4.1: Modelling land tenure and land dynamics in AECPGs provision[END_REF][START_REF] Chatzimichael | Informational cascades and technology adoption: Evidence from Greek and German organic growers[END_REF][START_REF] Damianos | Farmers' participation in agri-environmental schemes in Greece[END_REF][START_REF] Defrancesco | To leave or not to leave? Understanding determinants of farmers' choices to remain in or abandon agri-environmental schemes[END_REF][START_REF] Giovanopoulou | Modeling farmer participation in agrienvironmental nitrate pollution reducing schemes[END_REF][START_REF] Jaime | Interactions between CAP Agricultural and Agri-Environmental Subsidies and Their Effects on the Uptake of Organic Farming[END_REF][START_REF] Kallas | Farmers' objectives as determinants of organic farming adoption: The case of Catalonian vineyard production[END_REF][START_REF] Koesling | Factors influencing the conversion to organic farming in Norway[END_REF][START_REF] Läpple | Adoption of organic farming: Are there differences between early and late adoption?[END_REF][START_REF] Mack | Determinants for the Implementation of Action-, Resultand Multi-Actor-Oriented Agri-Environment Schemes in Switzerland[END_REF][START_REF] Mcgurk | Participation in agri-environmental schemes: A contingent valuation study of farmers in Ireland[END_REF][START_REF] Pavlis | Patterns of agri-environmental scheme participation in Europe: Indicative trends from selected case studies[END_REF][START_REF] Pufahl | Evaluating the effects of farm programmes: Results from propensity score matching[END_REF][START_REF] Uthes | Studies on agri-environmental measures: A survey of the literature[END_REF][START_REF] Vanslembrouck | Determinants of the willingness of Belgian farmers to participate in agri-environmental measures[END_REF][START_REF] Zimmermann | European farms' participation in agri-environmental measures[END_REF]. Except the effect of economic size, most commonly found to positively affect AECM adoption [START_REF] Damianos | Farmers' participation in agri-environmental schemes in Greece[END_REF][START_REF] Zimmermann | European farms' participation in agri-environmental measures[END_REF].

Still regarding farm and farmer characteristics, we identify an opposite effect of labour, LFA support and agricultural education on the AECM and OFS adoption decision. The effect of more labour per hectare, indicating a labour-intensive farm, is positive on the probability to adopt AECM and negative on the probability to adopt OFS. The effect of agricultural education is also found positive for AECM and negative for OFS while receiving support for LFA decreases the probability to adopt AECM and increases the probability to adopt OFS. Most of those findings are coherent with the literature [START_REF] Allaire | Spatial diffusion and adoption determinants of European agri-environmental supports related to extensive grazing in France[END_REF][START_REF] Andreoli | Deliverable D4.1: Modelling land tenure and land dynamics in AECPGs provision[END_REF][START_REF] Damianos | Farmers' participation in agri-environmental schemes in Greece[END_REF][START_REF] Ducos | Agri-environment contract adoption under fixed and variable compliance costs[END_REF][START_REF] Kallas | Farmers' objectives as determinants of organic farming adoption: The case of Catalonian vineyard production[END_REF][START_REF] Pavlis | Patterns of agri-environmental scheme participation in Europe: Indicative trends from selected case studies[END_REF][START_REF] Zimmermann | European farms' participation in agri-environmental measures[END_REF]. However, the effects of labour in our selection equations are opposite to previous results [START_REF] Defrancesco | Factors affecting farmers'participation 197 in agri-environmental measures: A northern Italian perspective[END_REF][START_REF] Jaime | Interactions between CAP Agricultural and Agri-Environmental Subsidies and Their Effects on the Uptake of Organic Farming[END_REF]. Another surprising result is the effect of agricultural education on the probability to participate in OFS since [START_REF] Koesling | Factors influencing the conversion to organic farming in Norway[END_REF] identified a positive effect on organic farming adoption. The effect of LFA payment on the AECM adoption decision in our model is also not consistent with [START_REF] Allaire | Spatial diffusion and adoption determinants of European agri-environmental supports related to extensive grazing in France[END_REF][START_REF] Unay Gailhard | Farm size and participation in agri-environmental measures: Farm-level evidence from Slovenia[END_REF][START_REF] Zimmermann | European farms' participation in agri-environmental measures[END_REF].

Regarding the farm types, we see that horticulture and market gardening farms (otexe 28, 29) are less likely to adopt AECM relative to the baseline (mixed farming, otexe 83, 84), while mixed cattle and sheep and goat farms are the most likely. For OFS, the highest probability is for arboriculture (otexe 39), while the lowest probability is for vineyards (otexe 37, 38).

The effect of farm characteristics affecting eligibility to specific environmental measures is significant. As expected, the probability to adopt both schemes increases with organic certification (higher relative profitability of adoption of less input-intensive practices). Our model also suggests a negative effect of the grazing livestock density (indicating more intensive production) on the probability to adopt an environmental contract. While the effect of the share of permanent grasslands is found positive for AECM and negative for OFS. Being located in a Natura2000 area increases the probability to adopt AECM while it tends to decrease OFS adoption. We observe that for both AECM and OFS, participation in 2015 significantly increases the probability to participate (+23% for AECM and +6% for OFS). Ceteris paribus, we also see that participation in AECM (OFS respectively), significantly decreases if the farm participated in OFS (AECM respectively) the year before. These findings are coherent with the literature [START_REF] Allaire | Spatial diffusion and adoption determinants of European agri-environmental supports related to extensive grazing in France[END_REF][START_REF] Andreoli | Deliverable D4.1: Modelling land tenure and land dynamics in AECPGs provision[END_REF][START_REF] Ducos | Agri-environment contract adoption under fixed and variable compliance costs[END_REF][START_REF] Läpple | Adoption of organic farming: Are there differences between early and late adoption?[END_REF][START_REF] Mack | Determinants for the Implementation of Action-, Resultand Multi-Actor-Oriented Agri-Environment Schemes in Switzerland[END_REF][START_REF] Pufahl | Evaluating the effects of farm programmes: Results from propensity score matching[END_REF][START_REF] Zimmermann | European farms' participation in agri-environmental measures[END_REF].

Finally, we identify significant year fixed effects. The probability to participate in AECM increases with time. This is expected as farmers see the experience of other farmers, are more aware of the existence of the scheme, and are also more likely to be already enrolled (5-year contract). We observe a drop in the probability to participate in OFS in 2017, which might result from the fact that some French regions stopped financing maintenance OFS starting from 2017.

Results of the simulation

The simulated impact on farmers' uptake of environmental contracts of a decrease of an additional 7.5% (reaching the maximum transfer rate of 15% between CAP pillars under current regulations) of direct payments to AECM and OFS in 2019 in France is presented in Table 2.5.

Participation in AECM increases from 11% to 24%, and in OFS from 7% to 17%. While the AECM budget more than doubles (+126%), participation and the UAA of participants increase proportionally less (+119% and + 112% respectively), suggesting decreasing returns of budget increase and that participants with the new budget allocation tend to have smaller farms.

Regarding OFS, participation and the UAA of participants increase proportionally more than the budget increase (+143% and + 162% respectively), and OFS beneficiaries under the new budget allocation tend to have larger farms. After the budget transfer, 5.7% of the sample is participating in both OFS and AECM, while it was 0.8% in the initial situation. The share of AECM participants with an OFS contract increases from 7.7% to 24.1%, while the share of OFS participants with an AECM increases from 12.1% to 34.3%. Two combined incentives explain this result. First, there is a direct effect of more budget dedicated to financing environmental commitments. More acceptable payments can be covered and participation becomes profitable for a larger share of farms. This additional budget is taken from 85% of observations receiving direct payments (99% of the UAA) and is redistributed to 29% of observations (34% of the UAA). 22% are new adopters of environmental contracts and 7% are observed participants in 2019 to which the simulation allocates an additional payment (adoption of additional measures). Second, there is an indirect effect of the decrease of direct payments on the acceptable payments triggering participation. The average decrease of acceptable payment per farm is 30€ for OFS, and 45€ for AECM. Those "savings" contribute to financing the participation of even more farms.

We identify a differentiated impact according to the type of farm. The farms losing the most income from lower direct payments are specialised in mixed cattle (-3,115 €/farm on average in otexe 47) and in mixed farming with field crops and grazing livestock (-3,015€/farm on average in otexe 83). The less affected farms are specialised in horticulture (-56€/farm on average in otexe 29) and quality wine (-205€/farm on average in otexe 37). On the one hand, the reorientation of the budget towards environmental contracts particularly incentivises farms specialised in grazing livestock to contract AECM (otexe 45, 46, 47, 48 and 83) (Table 2.

6).

This effect seems driven by the decrease in acceptable payments associated with lower coupled payments for suckler cows. In particular, AECM acceptable payments decrease the most for farms specialised in beef (-186€/farm on average in otexe 46) and mixed cattle (-125€/farm on average in otexe 47). On the other hand, the reorientation of the budget particularly incentivises farms specialised in permanent crops, dairy, pigs and poultry or mixed farming with field crops and grazing livestock to contract OFS (otexe 39, 45, 50, 83). For farms specialised in permanent crops or mixed farming with field crops and grazing livestock (otexe 39, 83), this effect seems driven by their highest probability to adopt OFS. The outputs of the simulations under different budget transfer scenarios, and in particular the resulting share of organic UAA are presented in Table 2.7. In 2019, almost 9% of the UAA was organic. In the first scenario of 15% of transfer between the two pillars (7.5%+7.5%), the uptake of conversion OFS is such that that the organic UAA more than doubles. To reach 25% of organic UAA, our model suggests a transfer rate of 15.5% (7.5%+8%) if OFS payments are restricted to farms undertaking a conversion to organic farming, and 21% (7.5+13.5%) if both certified and non-certified farms remain eligible.

Discussion and concluding remarks

AECM and OFS are currently the most ambitious environmental contracts in the CAP. We evaluated the potential to upscale their adoption without increasing the CAP budget, by transferring part of the budget for direct payments with little environmental conditionality to fund additional environmental contracts in France in 2019. Our findings suggest this mechanism successfully increases participation by combining two incentives. First, we identify a direct effect of more public money dedicated to financing environmental commitments.

Second, we identify an indirect effect on farmers' behaviour of receiving lower direct payments, which tends to decrease the farm-level acceptable payment triggering their decision to participate, making even more money available to finance more environmental commitments.

This study proposes a methodological approach to model farmers' behaviour at the national scale regarding the uptake of environmental commitments within the CAP, applied using FADN data available in all EU countries. We used it to evaluate ex-ante the impact of CAP budget allocation changes on the adoption of environmental contracts while capturing the effect of income support instruments on this adoption behaviour. The results can be analysed at the farm level, highlighting a differentiated impact according to farm specialisation. Nevertheless, simulation results need to be interpreted with care, as they depend on the quality of the adoption model estimated. Our model tends to underestimate the probabilities of adoption and acceptable payments compared with observed data, in particular for conversion OFS. It can be explained by insufficient information in the FADN to precisely capture contract eligibility, and the characteristics of the measures adopted by farmers. Not controlling for the payment per hectare and the surfaces enrolled for each type of measure remains an important limit of this work, as they represent sources of heterogeneity across farms that we do not capture. To improve this aspect, one could complexify the estimation procedure and control for individual fixed effects or lagged participation. Another possibility is to merge the FADN sample with the dataset on participants to rural development measures collected each year for the Annual implementation report (RAMO) and collect some of the missing information (surfaces under contract, type of measure adopted by each farm, municipalities eligible to environmental contracts). A second important limit to the study is that the reliability of the results decreases for higher rates of reduction of direct payment since the simulation uses marginal effects of direct payments on contract adoption. Nevertheless, our empirical findings support the relevance of decreasing untargeted payments and increasing targeted payments for the delivery of environmental public goods in the CAP.

Previous evaluation of the reorientation of 15% of direct payments towards rural development measures in the EU28 and in Germany with the Common Agricultural Policy Regionalised Impact partial equilibrium model identified marginal impacts on environmental indicators [START_REF] Schroeder | Quantitative modelling of the Rural Development Programs of the Common Agricultural Policy -EU-wide and region-specific effects[END_REF][START_REF] Schroeder | The Impact of Pillar II funding: Validation from a Modelling and Evaluation Perspective[END_REF]. Another study in Greece suggests 50% transfer would lead to an extensification of farming practices and improve water quality and biodiversity [START_REF] Giannakis | Modelling the impacts of alternative CAP scenarios through a system dynamics approach[END_REF]. While a transfer from direct payments to environmental incentives with the current regulation (maximum 15%) is unlikely to be sufficient to achieve the Farm to Fork target of 25% of organic land, our results suggest it can significantly contribute to it. The French government decided to limit eligibility to OFS to non-certified farms. Our simulations show this targeting facilitates the conversion of more land to organic. However, removing maintenance OFS can hinder the Green Deal objective in the long term if keeping organic practices is not profitable through the market. Finally, other levers can be applied such as improving contract design to increase attractiveness and environmental effectiveness, and supporting the development of the organic market. Moreover, the introduction of eco schemes in the first pillar of the CAP, financed with 25% of the direct payments envelope might trigger more voluntary adoption and significant environmental additionality.

Chapter 3. Payments for environmental services with ecological thresholds: farmers' preferences for a sponsorship bonus

In the two following chapters, I move my focus to the design of payment mechanisms of PES.

One of the main limits of the PES developed since the early 1990s (ex: AECM), is their high inefficiency when it comes to increasing the provision of public goods with threshold effects (water quality, biodiversity…). In particular, the dominating action-based payment conditionality based on the prescription of on-farm practices to individual farmers regardless of what is done on neighbouring farms seems inadequate to address their underprovision. In this chapter, I study the introduction of a payment mechanism combining action-based conditionality with a bonus for favouring a landscape approach. In particular, I propose a sponsorship bonus as a top-up to an individual per-hectare payment to promote higher participation in the target area. In addition, I do not constraint the PES to be funded by a public financing mechanism, and introduce the possibility for higher payments than currently proposed with AECM. I apply a choice experiment (CE) to measure ex-ante farmers' preferences for such a bonus mechanism in a PES aiming at improving the water quality of rivers in northwest France. [START_REF] Duval | Paiements pour services environnementaux et méthodes d'évaluation économique: enseignements pour les mesures agro-environnementales de la politique agricole commune[END_REF][START_REF] Wunder | Revisiting the concept of payments for environmental services[END_REF]. They emerged in the early 1990s, in response to the growing awareness of the value and shortage of agri-environment-climate public goods. In the European Union (EU), the most widely implemented PES are the agri-environmental measures, now called agrienvironment-climate measures (AECM), of the common agricultural policy (CAP). Over the past decades, the low environmental additionality, participation rates and cost-effectiveness of AECM have been highlighted in the literature, in particular, due to underfunded and poorly designed measures [START_REF] Cullen | Agri-Environment Scheme Design: Past Lessons and Future Suggestions[END_REF][START_REF] Dupraz | Effets des mesures agri-environnementales. Effects of agrienvironmental measures[END_REF][START_REF] Espinosa-Goded | Identifying additional barriers in the adoption of agri-environmental schemes: The role of fixed costs[END_REF][START_REF] Zavalloni | Agri-environmental Policies and Public Goods: An Assessment of Coalition Incentives and Minimum Participation Rules[END_REF]. Dedicated PES involving other contractual arrangements and financial contributors are also implemented on a smaller scale [START_REF] Heinz | Co-operative agreements and the EU Water Framework Directive in conjunction with the Common Agricultural Policy[END_REF]. Examples include schemes funded by water bottlers such as the Nestlé Waters, or by municipalities such as the water authorities of Munich and New York City [START_REF] Déprés | Contracting for environmental property rights: The case of Vittel[END_REF][START_REF] Grolleau | Designing watershed programs to pay farmers for water quality services: Case studies of Munich and New York City[END_REF].

Designing efficient payment mechanisms for public good provision is a challenge that often involves trade-offs between environmental ambition and large acceptance by farmers.

Conditionality rules must define environmental services with sufficient effort to reach the environmental objective(s) while remaining attractive enough to ensure significant participation on enough farmland. When the objective is to improve water quality or biodiversity, high participation and spatial continuity of environmental commitments at the landscape scale are necessary to observe environmental improvements [START_REF] Dupraz | Threshold effect and co-ordination of agrienvironmental efforts[END_REF]. Developing instruments favouring collaboration among land managers, coordination of actions and high uptake within the same area are promising ways to increase the environmental effectiveness of farmers' environmental services, as well as the cost-effectiveness of the payment. In addition to supporting the passing of ecological thresholds, collective approaches provide other advantages, such as fewer transaction costs for financial contributors, and the building of social capital for farmers [START_REF] Kuhfuss | Nudging farmers to enrol land into agrienvironmental schemes: The role of a collective bonus[END_REF][START_REF] Lefebvre | Agricultural landscapes as multi-scale public good and the role of the Common Agricultural Policy[END_REF][START_REF] Pretty | Social Capital and the Collective Management of Resources[END_REF].

Collective approaches can take different forms of PES contractual arrangements and payment conditionality [START_REF] Kuhfuss | Should agri-environmental schemes aim at coordinating farmers' pro-environmental practices? A review of the literature[END_REF][START_REF] Uetake | Managing Agri-Envirnonmental Commons Through Collective Action: Lessons from OECD Countries[END_REF]. Some involve a collective payment. In this case, the contracting party receiving the payment and meeting the requirements is a group of farmers, which distributes the amount to participants according to the rules defined by the collective. The Netherlands provide a large number of examples of successful collective 57 AECM, in which participants are local groups of farmers organised in environmental cooperatives [START_REF] Franks | The collective provision of environmental goods: A discussion of contractual issues[END_REF]. Cases from other EU countries are scarce. One can cite the collective AECM for preserving the European Hamster habitats in France [START_REF] Eichhorn | Deliverable 2.6: Catalogue of updated factsheets of European in-depth case studies[END_REF]. Other approaches are based on individual contracting, but the distribution of the payment is conditional to the achievement of a landscape-scale objective (minimum participation or land enrolment, reaching an environmental goal…), or of a collaborative action (coordination of management practices, agglomeration of the plots enrolled…). These conditionality rules can apply to all or part of the payment. In the latter case, the collective component of the contract takes the form of a conditional "reward" or "bonus". An example of such a payment mechanism is the Swiss network bonus (agglomeration bonus) [START_REF] Krämer | The agglomeration bonus in practice-An exploratory assessment of the Swiss network bonus[END_REF].

The literature suggests farmers are reluctant when collective requirements are conditioning the full payment, but favourable to a reward conditioned to collective action on top of an individual payment [START_REF] Villanueva | Heterogeneity of farmers' preferences towards agri-environmental schemes across different agricultural subsystems[END_REF][START_REF] Ben-Othmen | Farmers' preferences for grassland restoration: Evidence from France. 172nd EAAE Seminar 'Agricultural policy for the environment or environmental policy for agriculture?[END_REF][START_REF] Coent | Compensating Environmental Losses Versus Creating Environmental Gains: Implications for Biodiversity Offsets[END_REF] Thoyer 2017; Villamayor-Tomas, Sagebiel, and Olschewski 2019; [START_REF] Kuhfuss | Nudging farmers to enrol land into agrienvironmental schemes: The role of a collective bonus[END_REF]. Villanueva et al., (2015;[START_REF] Stiglitz | Overcoming the Copenhagen Failure with Flexible Commitments[END_REF] show that individual contracting tends to be preferred to collective contracting of a minimum number of farms from the same municipality, especially among older farmers with little experience in participating in cooperatives. Interestingly, Ben-Othmen and Ostapchuk (2019) find the opposite result, with positive preferences for collective contracting, but the threshold number was slightly lower (3 farms from the same municipality against 5 in (Villanueva et al. 2015)). Both case studies included prior information that farmers would be left free to form a group with whom they trust the most, and that only free-riders would be sanctioned in case of non-compliance with management requirements. A key factor of collective AECM acceptance is well-defined group governance and monitoring, which is often emphasized by researchers studying successful Dutch case studies of environmental cooperatives (Franks 2011; Uetake 2014; [START_REF] Barghusen | Motivations of farmers to participate in collective agri-environmental schemes: the case of Dutch agricultural collectives[END_REF], or more generally collective management of natural resources [START_REF] Ostrom | Chapter 24 Common-pool resources and institutions: Toward a revised theory[END_REF][START_REF] Kerr | Incentives, conditionality and collective action in payment for environmental services[END_REF]. Le [START_REF] Coent | Compensating Environmental Losses Versus Creating Environmental Gains: Implications for Biodiversity Offsets[END_REF] looked at farmers' preferences for biodiversity offsets with the full payment conditioned to a minimum of 20% of participation of farmers from the area. They found that farmers anticipate transaction costs for reaching the participation threshold and prefer contracts without it. Another study measuring preferences for an AECM requiring the coordination of the location of tree planting with neighbouring farms also concluded that farmers were reluctant to the collective approach due to transaction costs and beliefs that other farmers would not be willing to cooperate (Villamayor-Tomas, Sagebiel, and Olschewski 2019). However, they identified a peer effect, with the finding that farmers were more likely to choose an agrienvironmental measure recommended by other farmers. When it comes to collective bonus options, a study by [START_REF] Kuhfuss | Nudging farmers to enrol land into agrienvironmental schemes: The role of a collective bonus[END_REF] reveals positive preferences for a conditional bonus if at least 50% of the eligible area is enrolled in the scheme after five years.

Apart from this last study by [START_REF] Kuhfuss | Nudging farmers to enrol land into agrienvironmental schemes: The role of a collective bonus[END_REF] among vine growers, there is still little evidence of farmers' attitudes towards mixed-payment mechanisms promoting collective approaches. Further analyses would confirm or nuance the acceptability of these nudges in other contexts, and provide recommendations for designing successful schemes. This present study aims at providing new elements on the acceptability among farmers of a collective component in PES, designed to meet high participation rates and environmental efforts.

We develop a choice experiment (CE) to measure preferences for a contract targeting the improvement of river ecological quality in three regions of north-western France, characterized by the predominance of livestock farming and concerns over too much release of excess nitrogen and phosphorous into water bodies. CE are particularly relevant to elicit preferences for specific contract characteristics that do not yet exist [START_REF] Louviere | Stated Choice Methods: Analysis and Applications[END_REF]. Two types of bonuses are tested to explore new elements in the design of payment mechanisms: an individual bonus for sponsoring a peer, and a sponsorship bonus combined with a collective environmental result bonus distributed equally to all participants. Another contribution of the study is to offer payment levels which are higher than the range of current AES. By doing so, we consider the possibility for other contributors than public authorities to finance the PES, and we capture farmers' willingness to accept (WTA) beyond income foregone and additional costs.

The paper is organised as follows. Section 3.2 introduces the choice modelling and experimental design. Section 3.3 describes the survey data. Section 3.4 presents and discusses the results. Section 3.5 provides some concluding remarks and policy recommendations.

Method

Discrete choice experiment approach

A CE is a survey-based method to elicit the stated preferences of individuals. Respondents are successively asked to choose their preferred option among a small number of hypothetical alternatives, which differ according to several levels of attributes. CE techniques are based on Lancaster's theory that consumption decisions are determined by the utility derived from the attributes of the good being consumed [START_REF] Lancaster | A new approach to consumer theory[END_REF] and the random utility theory decomposes utility into a deterministic part and a random part [START_REF] Mcfadden | The measurement of urban travel demand[END_REF]. They are particularly useful to estimate ex-ante the marginal utility of different characteristics of policy design. The application of CE methods already provided a lot of useful policy recommendations for agri-environmental contracts design, for instance regarding farmers' preferences for contract length [START_REF] Bougherara | Farmers' preferences over conservation contract flexibility and duration : an estimation of the effect of transaction costs using choice experiment[END_REF][START_REF] Christensen | Determinants of farmers' willingness to participate in subsidy schemes for pesticide-free buffer zones-A choice experiment study[END_REF][START_REF] Gruau | Bilan des travaux préliminaires conduits sur le Bassin Versant du Lac au Duc en vue d'implanter des Paiements pour Services Environnementaux avec l'objectif de réduire les apports de phosphore d'origine agricole au lac[END_REF][START_REF] Latacz-Lohmann | Using choice experiments to improve the design of agri-environmental schemes[END_REF][START_REF] Ruto | Investigating farmers' preferences for the design of agrienvironment schemes: a choice experiment approach[END_REF], payment sequences [START_REF] Bougherara | Do farmers prefer increasing, decreasing, or stable payments in Agri-environmental schemes?[END_REF] and conditional bonuses [START_REF] Kuhfuss | Nudging farmers to enrol land into agrienvironmental schemes: The role of a collective bonus[END_REF][START_REF] Vaissière | Preferences for biodiversity offset contracts on arable land: A choice experiment study with farmers[END_REF].

Model specification

Under the random utility theory, the utility 𝑈 𝑛𝑗𝑡 that individual 𝑛 obtains from choosing alternative 𝑗 out of 𝐽 alternatives in the choice set 𝑡 out of a series of 𝑇 choice sets, is made of an observed component 𝑉 𝑛𝑗𝑡 (deterministic part) and a stochastic error term 𝜀 𝑛𝑗𝑡 (random part).

𝑈 𝑛𝑗𝑡 = 𝑉 𝑛𝑗𝑡 + 𝜀 𝑛𝑗𝑡 (3.1)
We assume individual 𝑛 chooses alternative 𝑗 if and only if that alternative maximises his or her utility amongst all alternatives in choice set 𝑡 . The probability that farmer 𝑛 chooses alternative 𝑗 is:

𝑃 𝑛𝑗𝑡 = 𝑃𝑟𝑜𝑏(𝑉 𝑛𝑗𝑡 + 𝜀 𝑛𝑗𝑡 > 𝑉 𝑛𝑖𝑡 + 𝜀 𝑛𝑖𝑡 ) = 𝑃𝑟𝑜𝑏( 𝜀 𝑛𝑗𝑡 -𝜀 𝑛𝑖𝑡 > 𝑉 𝑛𝑖𝑡 -𝑉 𝑛𝑗𝑡 ) ∀𝑖 ≠ 𝑗 (3.2)
The deterministic part of the utility function is typically specified to be linear in parameters.

The error terms are assumed to follow the Gumbel Type-1 extreme-value distribution [START_REF] Mcfadden | The measurement of urban travel demand[END_REF], such that a logit model can be applied to estimate the parameters.

Under the conditional logit (CL) model, the 𝛽 coefficients representing respondents' preferences for the attribute levels 𝑋 𝑛𝑗𝑡 are constant across individuals (homogeneous preferences), and the error terms are assumed independent and identically distributed across individuals and alternatives (3.3). It implies that the ratio of choice probabilities for any two alternatives is independent of the attribute levels of a third alternative in the choice set, and is known as the independence of irrelevant alternatives assumption (IIA).

𝑃 𝑛𝑗𝑡 = 𝑃𝑟𝑜𝑏( 𝜀 𝑛𝑗𝑡 -𝜀 𝑛𝑖𝑡 > 𝛽(𝑋 𝑛𝑖𝑡 -𝑋 𝑛𝑗𝑡 )) ∀𝑖 ≠ 𝑗 (3.3)
The Hausman test allows checking the independence of irrelevant alternatives (IIA) and validate the CL model specification [START_REF] Hausman | Specification Tests for the Multinomial Logit Model[END_REF]. To relax the IIA assumption and account for taste heterogeneity across farmers or groups of farmers, the mixed logit (ML) (3.4) or latent class (LC) (3.5) models are applied (Greene and Hensher, 2003). Evidence shows that hedge networks in agricultural landscapes such as bocage, act as buffer zones and erosion barriers preventing runoffs in water catchments, in synergy with many other ecological side-benefits [START_REF] Burel | Social, aesthetic and ecological aspects of hedgerows in rural landscapes as a framework for greenways[END_REF][START_REF] Caubel-Forget | Contrasted dynamics of nitrate and chloride in groundwater submitted to the influence of a hedge[END_REF][START_REF] Merot | The influence of hedgerow systems on the hydrology of agricultural catchments in a temperate climate[END_REF].

Avoiding long periods of bare soil, in particular in winter, also contributes to limiting soil erosion and runoffs [START_REF] Souchère | Grassland and crop trends: Role of the European Union Common Agricultural Policy and consequences for runoff and soil erosion[END_REF]. The choice of management and individual perhectare payment attribute levels was based on evidence from a study undertaken in a similar environmental context in Brittany [START_REF] Gruau | Bilan des travaux préliminaires conduits sur le Bassin Versant du Lac au Duc en vue d'implanter des Paiements pour Services Environnementaux avec l'objectif de réduire les apports de phosphore d'origine agricole au lac[END_REF]. In particular, their results show that payments of 400€/ha or less, restricts the adoption of PES with ambitious levels of management requirements because some farmers have a higher willingness to accept that cannot be met with this payment range. In France, the 5-year AECM contributing to water quality is typically in a range between 70€ and 350€/ha/year, based on an estimation of average opportunity costs (MASA, 2022). In our CE, we include individual per-hectare payment levels higher than typical AECM, to include the possibility that other contributors than governmental authorities finance all or part of the payment. The degradation of rivers' chemical and ecological quality does not only contribute to biodiversity loss but also increases the costs of water treatment for securing drinking water quality. Protecting water resources is of interest to many local stakeholders (water catchment bodies, inhabitants, companies, and municipalities…). Real-life contractual arrangements for reducing costs of drinking water depollution show that big municipalities such as Munich have been paying farmers up to 280€/ha/year [START_REF] Déprés | Contracting for environmental property rights: The case of Vittel[END_REF], while the private company Nestlé Waters spent around 230€/ha/year to secure their brand Vittel [START_REF] Perrot-Maitre | The Vittel payments for ecosystem services: a "perfect[END_REF]. Inhabitants of water catchment areas also exhibit a willingness to pay for reaching a good ecological status (40€/household/year estimated in Normandy), derived from the value they attach to multiple local benefits (recreational use, drinking water, floods prevention, landscape…) [START_REF] Poirier | Combien les résidents sont-ils disposés à payer pour des améliorations de la qualité de l'eau? How much are residents willing to pay for improving water quality?[END_REF]. Their role as PES scheme financers would better capture society's willingness to pay and cover farmers' WTA beyond compensation for foregone profits. WTA includes uncertainty and factors that are not necessarily technical barriers, such as transaction costs or social capital [START_REF] Espinosa-Goded | Identifying additional barriers in the adoption of agri-environmental schemes: The role of fixed costs[END_REF].

The bonus option levels were defined together with stakeholders involved in the development of experimental PES in the study area. A sponsorship bonus, suggested by a group of farmers from the Seiche Valley (Ille-et-Vilaine, Brittany) [START_REF] Bailly | Se lancer dans une démarche de PSE avec des collectifs d'agriculteurs: enseignements méthodologiques du projet LabPSE. Starting a PES approach with farmers' collectives: methodological lessons from the LabPSE project[END_REF], is introduced and takes the form of an individual reward for convincing a peer farmer from the water catchment area to enter the PES scheme. A farmer would receive a one-time 450€ per new peer sponsored. Each farmer can be sponsored only once. For the parties financing the PES scheme, offering the sponsorship bonus is an opportunity to increase participation at the water catchment scale while benefiting from the peer effect (communication on the PES, knowledge spillover…). However, sponsoring peers induces new transaction costs for farmers (social commitments, time). A second level of bonus option introduces an additional reward of 50€/ha, distributed to all participants if a collective environmental result is obtained. The environmental result is a higher step for the river's status on the water quality scale. This option aims at encouraging collaborative effort to reach a landscape objective and increase even further the environmental effectiveness of the scheme. Testing the combined introduction of a sponsorship and a collective environmental result bonus is particularly interesting to see if rewarding a collective environmental result affects the WTA of the bonus option relative to the sponsorship bonus only. The interest of the combined bonuses lies in increasing the incentive for reaching a critical mass of participants, and in particular where environmental effort contributes the most to water quality (big farms or located in the upstream of the river). Moreover, the positive effect of the sponsorship bonus on participation stops once all farmers from the eligible area have entered the scheme. The result-based collective bonus would maintain the incentive to pursue coordinated efforts towards the environmental objective. A fourth level with the collective result bonus without the individual sponsorship bonus was not included in the experimental design to limit the number of choice cards and minimum number of respondents required.

Choice sets include two contract alternatives and the status quo (option to opt-out and choose none of the contracts). They were designed by combining the different attribute levels (see For the econometric analyses, the individual per-hectare payment attribute (PAYMENT) is coded as a continuous variable, and the bonus option levels (BONUS sponsorship, BONUS sponsorship/collective result) as dummy variables. We compare continuous and effects coding for the management attributes (COVER, HEDGEROWS) to choose the best specification [START_REF] Mariel | Environmental Valuation with Discrete Choice Experiments: Guidance on Design, Implementation and Data Analysis[END_REF]. We define an alternative specific constant controlling for the status-quo alternative (ASCsq). The attribute levels of the status quo alternative are set at 0 for the individual per-hectare payment and bonus option attributes. For the management attributes, we compare a status quo level fixed at 0 and at the farm's current values (individual status quo) to identify the best specification. We conduct the analyses using the Apollo package on R (version 0.2.7). In particular, we use the apollo_searchStart function to test a large range of starting values for the model parameters and keep the best candidate for the estimation (Hess and Palma, 2022).

Survey structure

The CE was included as a section of a pan-EU survey on the acceptability of agrienvironmental-climate contract solutions, conducted in France among farmers located in Brittany, Normandy and Pays de La Loire. Voluntary farmers were contacted to organise a faceto-face interview after being recommended by intermediaries (farmers unions, organisations of milk producers, and farmers' associations…). The first section of the survey included general information on farmer and farm characteristics and the second section questions to evaluate the impact of contract characteristics on the willingness to adopt contractual solutions. For instance,

farmers were asked to state on a scale from 1 to 5 how much would the possibility to receive a common payment to be distributed among participants increase or decrease their willingness to participate. We use this information as an indicator of attitude towards collective approaches.

In the third section dedicated to the CE, respondents were introduced to the context, objective and rules of the game of the CE as well as the contract parameters (those fixed and those varying from one alternative to another). Preliminary questions were included to help the respondents estimating their current levels of management requirements (individual status quo). The current soil cover duration was calculated from the stated hectares of permanent grasslands, arable crops, permanent crops and total utilised agricultural area (UAA), as well as the average number of days with bare soil on arable lands and proportion of grass cover on the permanent crops surfaces (bare soil stopping after seeding). The current hedgerows density was calculated from the total UAA and total meters of multispecies multilayer hedgerows currently on the farmland.

Farmers were then asked 9 times to choose the preferred option among 2 contract alternatives and the status-quo.

Data

The interviews were conducted with 130 farmers between April and July 2021. Among them, The current levels of anti-erosion multispecies multilayer hedgerows density and soil cover duration estimated for the sample are particularly high for the surveyed area, with many farms already fulfilling the highest levels of the hypothetical contract's requirements. Farmers stated few days of bare soil for their arable land (25 days on average), and 88 m/ha of multispecies multilayer hedgerows on average at the farm level. All types of hedgerows considered (including monospecies or monolayer), the observed average density is 49 m/ha in Normandy, 48 m/ha in Brittany, and 55 m/ha in Pays de la Loire (Mission Bocage, 2011;[START_REF] Simon | Evaluation de la biomasse bocagère en Normandie. Assessment of the bocage biomass in Normandy[END_REF][START_REF] Simon | Evaluation de la biomasse bocagère en Bretagne. Assessment of the bocage biomass in Brittany[END_REF].

Regarding PES characteristics, most of the respondents (89%) have a positive attitude towards higher payments for higher environmental results (Figure 3.3). Collective approaches are less popular, with 64% of respondents declaring the possibility to agree collectively at the landscape-level would increase their willingness to adopt a contract, and 32% for receiving a common payment to be distributed among participating farmers.

Survey question: how much would the following contract characteristics increase or decrease your willingness to enroll? 1 The payment gets higher, the better your environmental results are. 2 You can collectively agree on environmental targets and measures at the landscape-level together with other land managers. 3 You and other land managers receive a common payment. You jointly agree on the distribution of the payment. Source: own elaboration, based on CONSOLE landowner survey results in France. Among the 130 respondents, five systematically chose the status quo option in the CE. We consider them as protest respondents and excluded their answers from the sample for the following econometric analyses.

Results

As a baseline, we estimate a CL model with attribute levels and the ASCsq as explanatory variables (Equation (3.3)) (Table 3.3). Three specifications are tested: continuous coding of management attributes with status quo levels fixed at the current farm level stated in the survey (CL1), continuous coding of management attributes with status quo levels fixed at 0 (CL2), and effects coding of management attributes with status quo levels necessarily fixed at 0 (CL3).

They provide similar estimates, in particular for the individual per-hectare payment and bonus attributes. Effects coding reveals nonlinear preferences for hedgerows management requirements. We decide to keep the first specification with the best goodness of fit measures (AIC, BIC). By capturing the individual status quo levels, specification CL1 better measures preferences for the ASCsq, while limiting the number of variables in the model. In a second ML specification (ML2), we add interaction terms with individual specific variables collected in the survey. Out of the set of covariates tested, we kept those significantly explaining the heterogeneity of farmers' choices while not deteriorating the model's goodness of fit. As expected, farmers who are members of an environmental organisation (ENVORGA=1) and therefore particularly aware of environmental issues, exhibit lower preferences for the statusquo option and higher preferences for higher levels of management requirements attributes. Organic farmers (ORGANIC=1) have higher preferences for more ambitious levels of hedgerows density requirements. We can assume organic farms value the multiple ecosystem services delivered by hedgerows (habitats for natural predators of pests, reducing exposure to pesticide spray drift from neighbouring farms…). On the other hand, respondents who plan to stop farming activities in 5 years or less (SHORT-TERM=1) have strong negative preferences for hedgerows requirements, which require long-term engagement for maintaining them. Large farms also tend to prefer lower levels of hedgerows requirements, for which compliance might be particularly costly. Regarding the bonus option, the higher the farmer's score (COLPAY={0,1,2,3,4}) in terms of the impact of a common payment on the willingness to adopt a contract, the higher his or her preferences for the combined sponsorship and collective result bonuses. It suggests that some farmers have "pro-collective" behaviour. Preferences for the combined bonuses also increase with the share of permanent grasslands in the cropping system (SHAREPGRASS). Finally, respondents for which farming contributes to less than 70% of the household gross revenue (HHDIVREVENU=1) are less likely to choose the status quo option. This is consistent with the findings by [START_REF] Defrancesco | Factors affecting farmers'participation 197 in agri-environmental measures: A northern Italian perspective[END_REF] that the high dependency of the households on agricultural income is a barrier to the adoption of AES.

Farmers' marginal WTA for the attributes are reported in Table 3.5. Ceteris paribus, a farmer accepts a contract with on average 43€ less of individual payment per hectare if there is a sponsorship bonus of 450€/peer. For a farm of 100ha (average farm size of the sample), it represents a decrease of 4,300€ in individual payment per year. A farmer would need to convince at least 10 new farmers each year to receive the same amount of sponsorship bonuses.

This result confirms the result by [START_REF] Kuhfuss | Nudging farmers to enrol land into agrienvironmental schemes: The role of a collective bonus[END_REF] that introducing a bonus option can improve the cost-effectiveness of a PES. We further characterise preference heterogeneities by estimating a LC model. The best model fit was obtained for 3 and 4 classes, as the Bayesian information criterion (BIC) increases starting from 5 classes (Table 3 .6). We decided to keep 3 classes to limit the number of variables in the model and add individual specific variables to explain class membership. The first class (57% of respondents) describes farmers with positive preferences for both types of bonus options, and with the highest preferences for the individual per-hectare payment (Table 3.7). Relative to the other classes, the level of financial incentive seems to drive their choice more than technical constraints. Farmers who are members of an environmental organisation, and therefore have experience in working collectively on environmental issues, are more likely to belong to this "pro-incentive" class. The second class of farmers (29% of respondents) exhibits preferences for low management requirements and is not affected by the bonus option.

Conventional farmers and farmers stopping their activity within 5 years are more likely to be in this "management change averse" class. The third class (14% of respondents) depicts farms preferring PES contracts with high management requirements and no bonus option. Organic farmers and farmers for which the household income is highly dependent on farming are more likely to be in this "pro-environment individualists" class. The preference parameter for the individual per-hectare payment is not significant, suggesting that the individuals' choice is more driven by the contract design in itself than by the incentive. While the third class describes a small share of the sample, it reveals the low acceptance of bonus incentives from a part of the farming population in the surveyed area, either because they prefer current action-based PES, or because they are reluctant to collective approaches.

Concluding remarks

The effectiveness of payment schemes for farmers' environmental services aiming at the delivery of environmental public goods with provision thresholds (biodiversity, water quality) depends on reaching enough farmland enrolment and aggregated environmental effort at the landscape scale. The objective of the present study was to elicit farmers' preferences for a payment mechanism made of a bonus incentivising farmers to adopt a collaborative behavior with other farms from the same area, on top of an individual action-based payment. In comparison to collective requirements conditioning the full payment, the conditional bonus option reduces the risk of receiving no compensation for one's environmental services if the aggregated effort and surfaces are insufficient at the landscape scale. Using a CE approach, we measured preferences for a sponsorship bonus of 450€/sponsored farmer rewarding individual farmers for increasing participation, and a combined bonus option comprising the sponsorship bonus and a collective result bonus of 50€ per hectare delivered to all participants if an environmental target is met at the landscape level.

Findings suggest that on average, respondents prefer contracts with a bonus for sponsoring a peer to no bonus, but are less favorable to a combined sponsorship/collective result bonus.

Designing bonuses distributed according to an individual effort for attracting more farmers could be a promising way to increase participation and PES cost-effectiveness, while collective bonuses distributed to all might be counterproductive. We characterised respondents' heterogeneity with a latent class model and identified three groups of farmers with a different attitude towards the bonus options: (i) "pro-environment individualists" with negative preferences for both, (ii) farmers who seem indifferent to both, and (iii) "pro-incentive" farmers with positive preferences for both.

A limit to the generalisation of our findings is that due to the sampling procedure, our data are biased. Asking and controlling for individual status-quo levels allowed us to control part of the bias regarding the already high levels of management requirements implemented by respondents. In addition, there is an over-representation of organic farms (39% of the respondents while the actual share is closer to 10%). Since organic farms are more likely to have a "pro-environment individualist" preference pattern, our results likely overestimate the negative attitude towards the bonus option, in particular towards the combined sponsorship/collective environmental result bonuses.

To ensure sufficient adoption, the introduction of PES with conditional bonuses may require paying farmers beyond opportunity costs. The involvement of private and local stakeholders in financing PES represents an opportunity to capture a higher willingness to pay for water quality.

In particular, bonus-mechanisms rewarding a landscape result or high participation could be of particular interest to stakeholders benefiting directly from the improvement of rivers' ecological quality (water bottle companies, water catchment bodies…). Another issue at stake in capturing more willingness to pay for PES is to consider the other public goods provided in synergy with the implementation of hedgerows and the reduction of bare soil duration, such as carbon storage and the protection of agrobiodiversity. On the one hand, the emergence of carbon and biodiversity offsets together with watershed payments represents an opportunity for farmers to find contributors more easily, and valorise the multiple environmental services they provide.

Stakeholders from north-western France seem particularly interested in developing local carbon 76 markets based on the valorisation of a bunch of public goods [START_REF] Dupraz | Conception of local carbon markets connecting farmers and companies : socio-economic outlines of innovative devices[END_REF]. On the other hand, the multiplication of those initiatives could lead to counterproductive effects. Different payment levels for the implementation of the same practices depending if a contributor values more water quality, carbon storage or biodiversity raise the issue of fairness. It might provide an additional incentive for farmers to work together in securing a collective supply of environmental services at the landscape level and increase their bargaining power. In areas where experience in collective approaches is low, building institutions facilitating collective action would support this process [START_REF] Kerr | Incentives, conditionality and collective action in payment for environmental services[END_REF].

Further research is needed to assess if conditional bonuses are successful in improving public good provision in practice. An AECM to protect the European Hamster in France recently introduced an individual bonus payment when a burrow is detected on a plot [START_REF] Eichhorn | Deliverable 2.6: Catalogue of updated factsheets of European in-depth case studies[END_REF]. This case study might provide useful empirical evidence to build on in the future. Observations from the Eco-Methane programme were the starting point for the empirical analysis developed in this chapter. We discuss two design elements of PES targeting the reduction of enteric methane emissions on dairy farms, which are crucial for their effectiveness: We also quantify the extra milk production costs of integrating more grass in the fodder systems by estimating variable cost functions for different dairy systems in France.

Chapter 4. Taking the diet of cows into consideration in designing a payment to reduce enteric methane emissions on dairy farms

Introduction

The agricultural sector is a major source of greenhouse gases (GHG), accounting for 10% of EU-KPs (European Union, United Kingdom and Iceland) in 2018 (Citepa, 2020a;[START_REF] Eea | Annual European Union greenhouse gas inventory 1990 -2018 and inventory report 2020[END_REF]. 81% of agricultural methane emissions result from enteric fermentation, and 39% of those 81% are produced by dairy cows [START_REF] Eea | Annual European Union greenhouse gas inventory 1990 -2018 and inventory report 2020[END_REF]. Methane is the second contributor to radiative forcing. Currently, the global warming potential of methane is set at 28 times higher than the global warming potential of carbon dioxide over 100 years and 84 over 20 years [START_REF] Myhre | Anthropogenic and natural radiative forcing[END_REF]. As methane is a short-lived climate pollutant continuously destroyed in the atmosphere, its effect on climate change depends mostly on short-term emission rates. In theory, decreasing the methane emissions rate below its natural destruction rate would have a cooling effect [START_REF] Cain | Improved calculation of warming-equivalent emissions for short-lived climate pollutants[END_REF]. Therefore, a significant reduction in methane emissions, in particular from agricultural activities, would rapidly mitigate climate change and is a powerful lever to meet the European Union's 2050 climate targets [START_REF] Dupraz | Policies for the ecological transition of agriculture: the livestock issue[END_REF].

Enteric fermentation is identified as the first source of GHG emissions from dairy farms in both developed and developing countries (Jayasundara et al., 2019;[START_REF] Wilkes | Variation in the carbon footprint of milk production on smallholder dairy farms in central Kenya[END_REF]. The quantity of methane produced during the digestive process of ruminants depends highly on the characteristics of the animal itself, such as the breed, body weight and age [START_REF] Gavrilova | 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories[END_REF]. However, enteric methane emissions are also directly related to farming practices, in particular the amount of feed intake and composition, and the proportion of carbohydrates that feed ration contains [START_REF] Martin | Methane mitigation in ruminants: from microbe to the farm scale[END_REF]. In particular, for a given productivity level, enteric methane emissions decline as dairy cow feed is enriched with alpha-linolenic acid ALA (polyunsaturated fatty acid of the omega-3 family), for which the main natural sources are linseed and grass fodders [START_REF] Chilliard | Milk fatty acids in dairy cows fed whole crude linseed, extruded linseed, or linseed oil, and their relationship with methane output[END_REF][START_REF] Dong | Lipid induced depression of methane production and digestibility in the artificial rumen system (RUSITEC)[END_REF][START_REF] Grainger | Can enteric methane emissions from ruminants be lowered without lowering their production[END_REF][START_REF] Martin | Methane output and rumen microbiota in dairy cows in response to long-term supplementation with linseed or rapeseed of grass silage or pasture based diets[END_REF][START_REF] Martin | Methane mitigation in ruminants: from microbe to the farm scale[END_REF][START_REF] Martin | Methane output and diet digestibility in response to feeding dairy cows crude linseed, extruded linseed, or linseed oil[END_REF][START_REF] Martin | Comment réduire la production de méthane chez les ruminants ? How can the production of methane by ruminants be reduced ?[END_REF]. Moreover, as productivity per cow increases, methane emissions per kilogram of milk decrease [START_REF] Martin | Comment réduire la production de méthane chez les ruminants ? How can the production of methane by ruminants be reduced ?[END_REF]. Animal productivity can also be improved through nutrition, as well as through herd's management and genetics [START_REF] Boadi | Mitigation strategies to reduce enteric methane emissions from dairy cows: Update review[END_REF]. To accurately monitor the evolution of enteric methane emissions on dairy farms, one must consider both dimensions (productivity and feeding). Authors show enteric methane emissions can differ significantly from one indicator to another and recommend considering both production intensity and feed usage for more accurate estimates [START_REF] Hagemann | Benchmarking of greenhouse gas emissions of bovine milk production systems for 38 countries[END_REF][START_REF] Sauvant | Influences des régimes et de leur fermentation dans le rumen sur la production de méthane par les ruminants (in French)[END_REF].

Economic incentives are currently being developed in the agricultural sector to support the reduction of GHG emissions. Changing management practices, and in particular cows' diet, to decrease enteric methane emissions may be costly for many farmers, and can be supported financially through payments for environmental services (PES). Developing PES schemes for the reduction of enteric methane emissions raises the question of the choice of a practical emission indicator sensitive to both diet and productivity effects, easily applicable and measurable on the farms. While numerous other motivations may encourage farmers to join a PES program, such as improving milk quality, environmental quality, zootechnical performance and the image of agriculture, economic interests are likely to be crucial factors.

An efficient payment level of a PES scheme targeting GHG emissions is equal to the socially optimal carbon price. In the EU, carbon tax levels differ largely among countries. In 2021, it was set at 120€/teqCO2 in Sweden and 45€/teqCO2 in France, while the EU ETS (European Trading System) market price was 44€/teqCO2 (The World Bank, 2021).

In this paper, we aim to provide insights into the design of PES schemes targeting the reduction of enteric methane emissions in dairy farms by examining two aspects of a payment mechanism for which failing to consider the feeding dimension could undermine its effectiveness in cutting enteric methane emissions: the choice of emissions indicator defining the environmental service, and the level of payment. By comparing an indicator constructed using a methodology applied in a real-life case study from France to the Tier 2 indicator currently used in the French annual GHG emissions inventory which considers productivity only, we examine how the diet of dairy cows influences the enteric methane emissions attributed to farms. Changing the diet of cows to improve the milk fatty acid profile can generate additional production costs that are not yet evaluated. The second contribution is to quantify the additional cost of a change in the diet of cows at the farm level to evaluate the economic incentives needed for improving dairy systems towards more environment-friendly practices. We estimate the variable cost function of dairy farms at the scale of France and for different fodder systems.

Background on enteric methane emission indicators

Many indicators of enteric methane emissions have been developed and adapted to specific constraints, often related to the scale of their application and the data available for estimating emissions [START_REF] Ellis | Prediction of methane production from dairy and beef cattle[END_REF][START_REF] Kebreab | Methane and nitrous oxide emissions from Canadian animal agriculture: A review[END_REF][START_REF] Negussie | Invited review: Largescale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions[END_REF]. For result-based PES, emissions should regularly and easily be monitored on the farms. The emission indicator chosen must therefore be easily measurable by the farmers and/or the paying agent using a simple methodology, representative of the environmental target and reliable (based on strong and reliable scientific evidence) [START_REF] Allen | Biodiversity protection through results based remuneration of ecological achievement[END_REF]. In addition, it must be sensitive to the different dimensions on which farmers can act to decrease emissions, in particular cows' diet and productivity.

The Intergovernmental Panel on Climate Change (IPCC) defines 3 families of methods, to be applied for national inventories according to data availability. Tier 1 methods attribute default yearly enteric methane emissions factor per dairy cow. Tier 1 methods provide aggregate estimates, and are not adequate for monitoring changes over time and considering the variability of dairy farming practices. Tier 2 methods improve the accuracy of emission factors by including feed intake estimates of a representative diet and dairy cow [START_REF] Gavrilova | 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories[END_REF].

Finally, Tier 3 methods require a precise characterization of cows' diets to account for digestibility. Both Tier 2 and Tier 3 approaches for France are presented in [START_REF] Eugène | A new Tier 3 method to calculate methane emission inventory for ruminants[END_REF].

Several recent studies applied those indicators. [START_REF] Stetter | Greenhouse Gas Emissions and Eco-Performance at Farm Level: A Parametric Approach[END_REF] applied a Tier 1 enteric methane emission indicator at the micro scale but as part of an overall assessment of the relative GHG emissions and economic performance of farms. Life cycle assessment analyzes calculating the carbon footprint of dairy products tend to apply Tier 2 methods (Jayasundara et al., 2019;[START_REF] Wilkes | Variation in the carbon footprint of milk production on smallholder dairy farms in central Kenya[END_REF], sometimes also including diet composition data [START_REF] Gollnow | Carbon footprint of milk production from dairy cows in Australia[END_REF][START_REF] Hagemann | Benchmarking of greenhouse gas emissions of bovine milk production systems for 38 countries[END_REF]. Bioeconomic models estimating emissions abatement costs in the agricultural sector use Tier 3 indicators of enteric methane emissions precise enough to capture both productivity and diet effects [START_REF] Lengers | Comparison of GHG-Emission indicators for dairy farms with respect to induced abatement costs, accuracy, and feasibility[END_REF][START_REF] Mosnier | Greenhouse gas abatement strategies and costs in French dairy production[END_REF]. Most Tier 3 and "individualized" Tier 2 approaches mentioned above require a large amount of detailed individual farm-level data on cows' feed composition, making it too costly to be applied as monitoring indicators on a large number of farms. However, some of the Tier 3 methods can use information from milk analyzes and thus, be more easily integrated into farm routines.

A Tier 3 indicator applied in the Eco-Methane result-based scheme

Numerous studies have been carried out to understand the connection between dairy cows' enteric methane emissions, fat intake and milk composition [START_REF] Chilliard | Milk fatty acids in dairy cows fed whole crude linseed, extruded linseed, or linseed oil, and their relationship with methane output[END_REF][START_REF] Dong | Lipid induced depression of methane production and digestibility in the artificial rumen system (RUSITEC)[END_REF][START_REF] Grainger | Can enteric methane emissions from ruminants be lowered without lowering their production[END_REF][START_REF] Martin | Methane output and rumen microbiota in dairy cows in response to long-term supplementation with linseed or rapeseed of grass silage or pasture based diets[END_REF][START_REF] Martin | Methane mitigation in ruminants: from microbe to the farm scale[END_REF][START_REF] Martin | Methane output and diet digestibility in response to feeding dairy cows crude linseed, extruded linseed, or linseed oil[END_REF][START_REF] Martin | Comment réduire la production de méthane chez les ruminants ? How can the production of methane by ruminants be reduced ?[END_REF]. In particular, experimental research shows that enteric methane emissions in gCH4/L (Methane) can be calculated from milk productivity in kg/cow/year (Productivity) and the ratio of the sum of fatty acids with 16 carbon atoms or less (𝐹𝐴 ≤ 𝐶16) to the total amount of fatty acids (TotalFA) in the milk they produce (Equation (4.1)). This ratio has a strong biological causal relationship with methanogenesis in the rumen and is significantly reduced by more sources of omega-3 in cows' diet. Martin), and received a patent under the title "Method for evaluating the quantity of methane produced by a dairy ruminant and method for decreasing and controlling such quantity" (WO2009156453A1) [START_REF] Weill | Method to evaluate the quantity of methane produced by a dairy ruminant and method for decreasing and controlling this quantity[END_REF]. The necessary data to implement it are relatively easy to collect on farm. One needs milk productivity and an analysis of the fatty acid composition of milk, obtained with infrared spectroscopy. Milk infrared spectroscopy is relatively simple to integrate into the milk analyzes routines of dairy farms and involves low costs. Since dairy farms already undertake milk analyzes regularly, it makes it a relatively cheap indicator to monitor emissions. In addition, the equation calculates enteric methane emissions per unit of product by taking into account both milk productivity and feed quality, hence captures both dimensions on which farmers can dedicate effort to reduce emissions.

The indicator described above is used since 2011 to evaluate the reduction of enteric methane emissions of dairy farms participating in the PES scheme Eco-Methane in France, implemented and coordinated by the Bleu-Blanc-Coeur association. Eco-Methane meets the reference PES definition by Wunder (2015). In the scheme, private stakeholders (service users) give financial support to volunteer dairy farmers (service providers) for actions that contribute to climate change mitigation (environmental services). The payment is conditional and proportional to the reduction of CO2eq, making the scheme a result-based PES. The reduction is calculated relative to baseline monthly emission levels attributed to the farms that are representative of its type of fodder system. Through the definition of different baseline scenarios, the PES design partially considers the variability in the potentiality of environmental services provision according to the production basin and the fodder system. Hence, rather than rewarding farms that produce the least emissions per unit of product (which would tend to favor the most productive farms), Eco-Methane supports all emission reduction efforts.

The Eco-Methane scheme uses eleven scenarios of baseline emission levels representative of 11 fodder systems of French specialized dairy farms. These fodder systems were characterized by the French Dairy Interbranch Organization (CNIEL) in collaboration with the French Livestock Institute (IDELE) in 2009, based on large production basins (plain and mountainous areas), and the proportion of corn in fodder crop rotation systems (CNIEL, 2015). The baseline emissions for each scenario are determined by Bleu-Blanc-Coeur using equation (4.1).

Eco-Methane brings together more than 600 farmers whose emissions reduction was estimated at 11% on average in 2017 [START_REF] Boadi | Mitigation strategies to reduce enteric methane emissions from dairy cows: Update review[END_REF]. Bleu-Blanc-Coeur pays farmers according to their reduction of methane emissions in CO2eq with a financial envelope made of donations from private actors (15€/tCO2eq on average in 2017). The main strengths of the scheme lie in the strong scientific foundations of the method for quantifying emissions and the easy participation procedure for dairy farmers. Each contract signatory commits to provide a monthly milk analysis to the association and to include feed with a high content of sources of omega-3 in dairy cow rations (alfalfa, extruded linseed, grass). These data are used to estimate enteric methane emissions using equation (4.1). Eco-Methane is recognized by the United Nations as a GHG emission reduction project eligible for issuing carbon credits (UNFCCC, 2016).

Materials and methods

Data

Observations of a balanced panel of 735 French dairy farms from France's farm accountancy data network (FADN) for the years 2016 to 2018 were selected for the analysis. This European database is freely accessible online and representative of socioeconomic and accountancy information of medium and large dairy farms contributing to more than 90% of the gross production and utilized agricultural area. Due to this characteristic, it is a particularly relevant dataset to investigate emission abatement costs at the national level. As the compositions of the feed ration and milk are not surveyed, information on the diet of dairy cows is limited and in particular, the fatty acid profile is unknown. Instead, data on the fodder crop rotation systems are used to assess a change in crop rotation and approximate a change in feed composition.

Descriptive statistics of the sample are presented (Table 4.1).

Attribution of enteric methane emissions

We use the Tier 2 method used in the French annual inventory of GHG emissions to define an indicator of enteric methane emissions sensitive to productivity effects. Dairy cows' emission factors are calculated from equation (4.2) (Citepa, 2020b).

𝐸𝐹 = 0.0105 * 𝑀𝑖𝑙𝑘 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑁𝑐𝑜𝑤𝑠 + 48.971 (4.2)
The emission factor EF (kgCH4/cow/year) can be easily calculated for each farm of the FADN from the milk production (kg/year) of the herd (Milk production) and the number of dairy cows (Ncows). We then derive an emission indicator (TIER2) per liter of milk, capturing variability according to milk productivity (L/cow/year):

𝑇𝐼𝐸𝑅2 = 𝐸𝐹 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 (4.3)
Due to the absence of data on dairy cows' diets, a Tier 3 method cannot be applied to evaluate individual emissions of FADN farms and capture both productivity and diet effects. In particular, data are too limited to estimate individual enteric methane emissions of French farms using equation (4.1). They are, however, sufficient to identify their Eco-Methane scenario and therefore the baseline emissions corresponding to their fodder system. Baseline emissions from the 11 scenarios are available per month and were obtained from Bleu-Blanc-Coeur. We calculate the annual average to define the Eco-Methane baseline emissions indicator (Eco-Methane baseline) (Table 4.2). An individual baseline scenario was assigned to each farm of the sample based on two criteria: the location and the share of corn silage in the fodder area of the farm. In the FADN database, the farm location variable corresponds to the 21 old French administrative regions (the administrative divisions were changed in 2015), while the Eco-Methane scenarios are defined according to large production basins built from a lower administrative level (departments). It was therefore necessary to allocate a production basin to each administrative region. For the regions with departments belonging to different production basins, we allocated the basin of the departments producing the highest volumes of milk to the entire region. This attribution was made using the 2018 annual dairy survey [START_REF] Agreste | Enquête annuelle laitière 2018[END_REF] and is detailed in Appendix A5.

Estimation of the extra-cost of milk production with more grass in the fodder system

The optimal payment level of a PES scheme lies between society's willingness to pay for climate change mitigation and farmers' willingness to accept for reducing emissions. The optimal price of climate change mitigation corresponds to the optimal tax rate of CO2 emission.

In France, the closest financial tool to a carbon tax is the Climate and Energy Contribution proportional to the carbon dioxide content of energy products (fossil fuels) [START_REF] Rogissart | La Contribution Climat Energie en France : fonctionnement, revenus et exonérations. The Climate-Energy Contribution in France: operation, revenues and exemptions[END_REF]. The contribution level was 30€/tCO2eq in 2017 and increased to 40€/tCO2eq in 2018 and 2019. Farmers participating in Eco-Methane received an average of 15€/tCO2eq in 2017, suggesting that the payment of the scheme is suboptimal and provides little incentive to participate (Bleu-Blanc-Coeur, 2022b). Evaluating farmers' willingness to accept is necessary to define a more efficient price and trigger a large scale adoption of practices decreasing enteric emissions.

Since the composition of the feed ration and milk of cows are not available in the FADN, the effect of an improvement of the fatty acid profile on milk production costs cannot be analyzed directly. Instead, an evolution of the fodder crop rotation is assumed. As grass is a high source of omega-3 fatty acids strongly encouraged in Eco-Methane, we assume that a commitment to the program would lead to an increase in grassland surfaces on farms. This hypothesis is quite strong and implies that the estimation of extra costs does not consider either the strategy of supplementing the ration with other feeds with high omega-3 content such as extruded linseed or the optimization of grazing increasing grass yield and quality without necessarily increasing grassland surfaces.

Based on dual production theory [START_REF] Mcfadden | Cost, Revenue and Profit Functions[END_REF], we estimate a variable cost function describing expenditures in variable production factors x with exogenous input prices w that minimize variable costs given the production level y targeted by the farmer and available quasifixed inputs z such as land, labor and equipment that are assumed to be predetermined in the short term. The variable cost function is defined as follows:

𝑉𝐶(𝑤, 𝑦, 𝑧) = min 𝑥 𝑤𝑥 𝑠𝑢𝑏𝑗𝑒𝑐𝑡 𝑡𝑜 𝑦 ≤ 𝑓(𝑥, 𝑧) (4.4)
The variable cost function meets several theoretical properties. It must be concave, nondecreasing and homogeneous of degree 1 in input prices, decreasing with fixed factors of production, and convex according to output levels.

We estimate a system of equations comprising a homogeneous translog cost function (4.5)

The translog functional form is commonly used in the literature on the cost structure and efficiency of dairy farms because of its flexibility and the possibility of imposing homogeneity of degree 1 [START_REF] Alvarez | Diseconomies of size with fixed managerial ability[END_REF][START_REF] Moschini | The Cost Structure of Ontario Dairy Farms: A Microeconometric Analysis[END_REF][START_REF] Mosheim | Scale economies and inefficiency of U.S. dairy farms[END_REF][START_REF] Nehring | Small U.S. dairy farms: can they compete?[END_REF][START_REF] Singbo | Scale economies, technical efficiency, and the sources of total factor productivity growth of Quebec dairy farms[END_REF][START_REF] Sobczyński | Dairy farm cost efficiency in leading milk-producing regions in Poland[END_REF][START_REF] Wimmer | Diversification economies in dairy farming -Empirical evidence from Germany[END_REF]. i and t are indices for individuals and years, respectively. We assume that dairy farms produce one output, the quantity Y1 of the milk of cows produced per year (Milk production), the other products would be considered as a control variable. We consider two variable inputs, fuel X1

and cattle feeding stuffs X2, for which the expenses represent a high share of intermediate consumption. The choice of including fuel is motivated by the possibility of calculating farmlevel fuel prices and therefore capturing more heterogeneity. The price of fuel W1 (fuel price)

is calculated from the nonroad gas oil expenses and volumes. As individual cattle feeding stuff prices are not available in the data, W2 (feed price) is measured by the index of purchase prices of the means of agricultural production (IPAMPA) for adult cattle feeding stuffs of year t-1, available for each French current administrative region. We also include three quasi-fixed inputs. Grassland surface Z1 (grassland) includes permanent and temporary pastures, alfalfa for dehydration and other artificial fodders. We add two other quasi-fixed factors of production: machinery and constructions fixed assets Z2 (capital) and annual work units Z3 (labor). The aggregated volume Y2 of the other products of the farm (other productions) allows us to capture the heterogeneity linked to diversification. Y2 is calculated as the total gross product of the year (crop products, livestock products and other products) net of animal purchases and milk production of the cows, deflated by the French agricultural producer price index (API) of year t. eit, u1it and u2it are the error terms assumed to follow a normal distribution.

As grassland areas, milk production and input use can be simultaneous decisions, and lnZ1it and lnY1it are likely to be correlated with the error terms. To correct for endogeneity, a three-stage least squares regression analysis with instrumental variables (3SLS-IV) is adopted. We include as instrumental variables the milk selling price P1 (milk price), the utilized agricultural area (UAA) Q1 (utilized agricultural area), the permanent pasture area Q2 (permanent pastures), the number of dairy cows on farm Q3 (number of dairy cows) and 20 regional dummies Dri approximating the pedoclimatic conditions. These variables were chosen to capture important factors influencing the simultaneous decisions made by farmers regarding cattle feeding strategy and output level each year. By doing so, we assume that the UAA and surfaces of permanent pastures (installed for at least 5 years) are exogenous over the period of the analysis (3 years). The number of dairy cows is included as an instrumental variable based on the observation that Q3 presents little intraindividual variability from one year to the next.

Therefore, we consider the number of dairy cows to be a quasi-fixed decision in the short term and keep it in the model. The instrument Mit comprising all the exogenous and instrumental variables of the model is used to regress the endogenous variables in the three equations of the system and is presented in Appendix A6.

The system of equations (4.5) + (4.6) + (4.7) is estimated for all the farms of the sample and then for the three major production basins and groups of Eco-Methane scenarios defined in Table 4.2 to identify potential differences in extra costs according to the type of dairy system.

Descriptive statistics of the model variables of the sample and subsamples are presented in are characterized by a strong dominance of corn silage and few grasslands in forage crop rotation systems. For example, 68% of farms in Brittany would be assigned scenario 2 with more than 30% of corn in the forage crop rotation and 28% scenario 4 with 10 to 30%. The administrative regions of the plain production basin outside the western region (31% of the sample) and of the mountainous areas (24% of the sample) are quite different. Some plain regions, such as Rhône-Alpes, contain a high proportion of grazing systems dominated by grasslands (less than 10% of corn silage in the fodder crop rotation), while others, such as the Centre, have more intensive systems dominated by corn silage. All the observations from Languedoc-Roussillon correspond to grazing systems, while the observations from Midi-Pyrénées have a relatively small proportion (32%). Due to the missing information on departments in the FADN dataset and our scenario allocation procedure, some farms have been allocated to a plain system scenario, while, in reality, they are located in a mountainous department and vice versa. This allocation might partly explain the large share of farms with grazing systems in Rhône-Alpes. Nevertheless, those farms produce relatively low volumes of milk in comparison with plain farms from the same region.

Enteric emissions: relation to productivity and fodder system

The mean of the Tier 2 indicator for the sample is 17.9 gCH4/L, while it is 16.3 gCH4/L for the Eco-Methane baseline indicator, suggesting that considering the fodder cropping system in the calculation revises enteric emissions downwards. Both indicators show a decrease in emissions per liter of milk as productivity increases (Table 4.4). According to indicator Tier 2, farms in mountains emit significantly more methane per liter of milk than farms in the plains, which can be explained by their lower productivity. The same observation is made with the Eco-Methane indicator, but the difference between the groups is significantly less (Table 4.4 andFigure 4.

2).

This finding confirms the hypothesis that a diet dominated by fodder rich in omega-3 (dairy farms typically feed cows with more grass in mountains) reduces emissions per liter of milk. Although the average methane emissions calculated with the Tier 2 method are not significantly different between the western plains and the other plains, their average Eco-Methane baselines are significantly different (Table 4.4). Considering the fodder crop rotation system in the calculation, enteric methane emissions are higher in the western plains. The productivity of the two groups is not significantly different, suggesting that the fodder system could explain the better environmental performance of the plains outside the western region measured by the Eco-Methane baseline indicator. As suggested by the distribution of Eco-Methane scenarios (Figure 4.1), corn silage dominates more in the western plains (32% of the fodder area on average) than in the other plains (21%). In the plains outside the western region, the feed ration of dairy cows likely includes more grass or other fodders with high omega-3 content. In addition, the lower the share of corn silage in the fodder area (and therefore, the more grasslands), the higher the difference between the emissions calculated with the two indicators.

Our observations are in line with the literature [START_REF] Grainger | Can enteric methane emissions from ruminants be lowered without lowering their production[END_REF][START_REF] Martin | Comment réduire la production de méthane chez les ruminants ? How can the production of methane by ruminants be reduced ?[END_REF]. A recent meta-analysis of life cycle assessments also highlighted the negative relationships between milk yield and enteric methane emissions on the one hand and pasture intake and enteric methane emissions on the other hand [START_REF] Lorenz | Is low-input dairy farming more climate friendly? A meta-analysis of the carbon footprints of different production systems[END_REF]. Other authors also show that enteric methane emissions particularly differ from one indicator to another in grazing systems [START_REF] Hagemann | Benchmarking of greenhouse gas emissions of bovine milk production systems for 38 countries[END_REF]. Choosing an adequate indicator of enteric methane emissions is the topic of ongoing debate. This analysis illustrates the importance of the choice of environmental indicator when designing a PES scheme targeting the reduction of enteric methane emissions in dairy farms, as it is likely to affect its environmental performance. We show the relevance of using an emission indicator sensitive to diet when defining economic incentives for the reduction of GHG emissions.

Detailed indicators are the most cost-effective, but due to heavy data collection needs (precise feed digestibility and composition), this advantage decreases when applied at a large scale [START_REF] Lengers | Comparison of GHG-Emission indicators for dairy farms with respect to induced abatement costs, accuracy, and feasibility[END_REF]. An indicator such as the one used in Eco-Methane presents several advantages to be implemented on a large scale, and be a better proxy compared with the most widely used Tier 2 and data demanding Tier 3 indicators. It is precise enough to capture the efforts of farmers on both cow productivity and feed ration composition, and it considers the potential of an omega-3-rich diet as a climate change mitigation practice. This feeding strategy is already implemented in dairy systems integrating a large share of grasslands in their fodder crop rotation systems, with the side provision of other environmental benefits (biodiversity maintenance). Additionally, the fatty acid composition of milk provides information on the complementary health benefits for consumers of an increase in sources of omega-3 fatty acids in the diet of dairy cows [START_REF] Weill | Effects of introducing linseed in livestock diet on blood fatty acid composition of consumers of animal products[END_REF]. The accuracy of indicators based on milk analyzes could be further improved by controlling for factors likely to affect the correlation between milk fatty acid composition and enteric emissions such as the lactation stage [START_REF] Negussie | Invited review: Largescale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions[END_REF].

Furthermore, the environmental performance of PES schemes specifically targeting enteric methane emissions depends on the absence of negative spillovers on other factors of GHG emissions in dairy farms (fertilization management, machinery…). Decreasing enteric methane emissions per liter of milk is a lever particularly interesting to rapidly reduce the contribution of dairy farming to climate change while also considering the food security dimension as it refers to the quantity of food produced. But it should be complementary to further farm-level and area-based assessments of GHG emissions to support effective mitigation strategies.

Impact of increasing the grassland area on the marginal cost of milk production

Several model specifications were tested, and the results are robust to a change (single variable costs equation, system of equations with and without imposing constraints on the parameters for ensuring homogeneity of degree 1). The estimation of variable input shares provides additional information and improves the quality of the variable cost estimation (measured by R 2 ). Consistent with the hypothesis of cost minimization, imposing restrictions on the parameters across equations also improved the variable cost estimation quality. Therefore, we present the results of the constrained system estimation. All the reported first-stage F-statistics were above 10, suggesting no weak instruments.

We verify that the variable cost function is nondecreasing with input prices (positive estimated variable input cost shares). However, some of the empirical models do not respect all the theoretical properties of a cost function. In particular, variable costs are decreasing with at least one quasifixed factor of production only in the model applied to the entire sample and for the subsample of plain farms with less than 30% corn silage in the fodder area.

The first-order derivative of the variable cost function (4.5) gives the marginal cost function The results presented in the following paragraphs are calculated from the regression results detailed in the Appendix A7.

When applied to all farms of the sample and on the subsamples of farms from the two plain production basins, the model suggests that producing milk with more grass does not significantly affect variable costs (Table 4.5). There are significant extra costs per additional hectare of grassland in mountainous areas (+3.6€/1000L/ha) already facing high marginal production costs and lower productivity.

for which we observe non-significant extra-costs. Current dominant fodder systems involve high expenditures on specific corn inputs (seeds, herbicides, etc.) and high protein content complements (soya, rapeseed) to balance dairy cow feed rations. Adding more grass and benefiting from a PES would reduce dependence on costly inputs. Synergies between the reduction of GHG emissions and the economic performance of intensive dairy farms have already been pointed out in the literature [START_REF] Borreani | Effect of different feeding strategies in intensive dairy farming systems on milk fatty acid profiles, and implications on feeding costs in Italy[END_REF]Jayasundara et al., 2019).

Moreover, other authors found evidence of differences in emissions abatement costs among dairy farms according to their geographical location [START_REF] Njuki | The economic costs of environmental regulation in U.S. Dairy farming: a directional distance function approach[END_REF]. It shows the relevance of considering the variability of dairy systems when studying the willingness of farmers to accept entering a PES programme, as we find different extra production costs linked to the modification of fodder crop rotations (increase in grassland area). Not considering the feeding strategy of dairy farmers, and in particular the type of fodder system, would lower the attractiveness of a payment scheme. It would be relevant to consider this heterogeneity when establishing an optimal payment for environmental services.

Given the low level of payment in current PES schemes (for instance in the Eco-Methane programme), it seems reasonable to assume that participating farms already had good economic profitability and/or feeding practices compatible with emission reductions when entering the programme. In the prospect of engaging more farmers and more liters of milk in the feed ration transition, we identify three types of dairy farms that could integrate a PES for the reduction of enteric methane emissions. Farms for which reducing enteric emissions is already profitable (no or negative extra costs) (type 1), farms for which it requires little financial support (low but positive extra costs) (type 2), and farms for which it requires high financial support (high positive extra costs) (type 3). Our study suggests that French plain-intensive farms broadly correspond to type 1. Although their individual willingness to accept is likely to be low, the programme would still need important financial means to offer a payment given the large number of unit of emissions reductions to compensate (high milk productivity). In contrast, dairy farms located in mountainous areas or with a high share of grasslands are more likely to correspond to type 3 and exhibit a high individual willingness to accept. Attracting them into the programme would require a high level of payment per CO2eq for fewer units (lower milk productivity). For those farms, increasing milk productivity might be a cheaper lever to reduce enteric emissions per liter. Most French dairy farms are likely to be type 2, with an intermediate individual willingness to accept the programme but a large number of emission reduction units to compensate given the large number of potential participants.

The positive effect of grass on methane emissions is likely to be partly offset by a drop in the productivity of the cows. Other sources of omega-3 fatty acids such as linseed could also be integrated in the feed ration to maintain productivity [START_REF] Fuentes | Effect of extruded linseed on productive and reproductive performance of lactating dairy cows[END_REF]. Feed complementation is however likely to be a more expensive lever to implement for most farmers, as they are often not produced in farms. Due to the absence of data, the extra-costs of increasing the use of omega-3 sources rich complements could not be estimated. Furthermore, for the Eco-Methane payment to efficiently subsidize the reduction of enteric methane emissions through an increase in grassland areas, the payment will have to cover both the additional costs per liter of milk and the other extra costs per hectare of grass. Beyond impacting production costs per unit of milk, a new hectare of grassland can have a direct effect on farm costs. In this study, we consider only variable costs (intermediate consumption). There may also be fixed costs (specific machinery for grass cultivation, buildings for storage) or other constraints (access to land) increasing the overall extra costs of participation. A study considering all farm costs (variable and fixed costs) found higher GHG emissions abatement costs per liter of milk in large farms (with a high number of dairy cows) compared with smaller farms [START_REF] Njuki | The good and the bad: environmental efficiency in northeastern U.S. dairy farming[END_REF].

Conclusions

Two aspects of PES design for reducing enteric emissions per liter of milk are particularly crucial to favor its environmental performance. First, the choice of emission indicator should measure farmers' efforts on both cows' productivity and diet, while being easily and regularly implemented on farm at low cost. Second, evaluating farmers' willingness to accept and its variability according to farm type is necessary to define the optimal payment level and scheme's budget ensuring sufficient participation. For a given production level, producing milk with more grass have a different impact on milk variable production costs depending on the production basin and fodder system. This research provide more insights into the impact of methane emissions reduction on the production costs of livestock farms, and how to improve support for pressing abatement measures and contribute effectively to achieving climate targets.

Introduction

The development of organic agriculture in the 2000s inspired economists to evaluate consumers' willingness to pay for agricultural food products with environmental labels (eco-labels). Even if there is a willingness to pay for environmental factors [START_REF] Teisl | Can eco-labels tune a market? Evidence from dolphinsafe labeling[END_REF], the literature largely pointed out that consumers' motivations were not purely altruistic and associated with strong environmental sensitivity. If consumers perceive that an environmentally friendly process guarantees food safety, then the perceived benefits from the environmental attributes may also be private [START_REF] Bougherara | Eco-labelled food products: What are consumers paying for?[END_REF]. The existing research shows that health factors are the main motives (among others, [START_REF] Magnusson | Choice of organic foods is related to perceived consequences for human health and to environmentally friendly behaviour[END_REF][START_REF] Verhoef | Explaining purchases of organic meat by Dutch consumers[END_REF]; Aldanondo-Ochoa and Almansa-Sáez 2009; [START_REF] Brécard | Consumer preferences for eco, health and fair trade labels. An application to seafood product in France[END_REF] for consuming organically produced food products.

Other papers have found that environmental preferences matter more in the decision to purchase organic products, with health concerns still having a high and significant impact [START_REF] Durham | The Impact of Environmental and Health Motivations on the Organic Share of Produce Purchases[END_REF]. Based on these findings, several studies have reinforced the importance of encouraging ecofriendly purchases by promoting their positive effects on health. [START_REF] Dabbert | Measuring and Communicating the Environmental Benefits of Organic Food Production[END_REF] concludes that attempts to sell organic products based only on their environmental characteristics are likely to fail, while providing information about the private benefits (such as the health benefits), as a secondary aspect, can have a positive effect on sales. [START_REF] Rousseau | Green market expansion by reducing information asymmetries : Evidence for labeled organic food products[END_REF] show that after providing additional objective information on the environmental and health effects of organic apple production, the price premium consumers were willing to pay for organic apples increased from 33 eurocent to 57 eurocent per kilogram. In the context of multiple signals, labels can reinforce or attenuate each other [START_REF] Grolleau | Interaction between food attributes in markets: The case of environmental labeling[END_REF][START_REF] Onozaka | Does local labeling complement or compete with other sustainable labels? A conjoint analysis of direct and joint values for fresh produce claims[END_REF].

The new instruments put in place by the European Green Deal also show such a trend. The new European Farm to Fork Strategy that could guide and support transformation paths toward more sustainable agricultural practices includes actions for transforming European food systems, including the development of a food-labeling framework to promote healthy and environmentally friendly food consumption (EC, 2020a).

To our knowledge, whether promoting private characteristics, such as the health benefits, of goods produced from environmentally friendly practices can increase the provisioning of public goods has not been demonstrated. In this paper, we theoretically assess the potential of labels that target health and environmental aspects and show that such labels may improve the delivery of environmental public goods compared with environmental labels.

friendly practices, which generates the same private characteristic as well as a public characteristic (the improvement of the quality of the environment). He also provides substitutes for the green product. Consumers can obtain private characteristics by buying conventional products or green products and public characteristics by buying green products or by making a direct donation to the corresponding environmental cause. Van't Veld and Kotchen (2011) consider that the green product brings an additional private benefit to the consumer compared to the conventional product. On the other hand, they assume that consumers' willingness to pay for this green product depends only on the private benefit associated with its consumption, since all consumers can benefit from the public benefits (free-ride behavior).

Following these works, we consider two food products, a conventional good 𝑐 and a green good 𝑔. These two goods generate the same private characteristic 𝑋, which corresponds to the need to feed oneself. The green good 𝑔 generates the private characteristic 𝑋 as well as two additional characteristics, a public characteristic 𝑌 and another private characteristic H. Since the good 𝑔 is produced by more environmentally friendly agricultural practices, it is assumed that its production and consumption allow for the improvement of the quality of the environment corresponding to the public good 𝑌. The originality of our approach is that the nutritional qualities of the green good 𝑔 are superior or less chemical products are required for its production compared with conventional good 𝑐. Thus, the consumption of good g improves the health of the consumer, which is a private characteristic H.

We The question we sought to answer is whether the information given to consumers on food products impacts the provision of environmental public goods. More specifically, we want to know if the valorization of products for their benefits for health is an approach to be encouraged in the framework of environmental policies. Therefore, we compare three market settings for a same green product 𝑔 (Table 5.1) that differ only by the information given to consumers on the green product. This information will modify their consumption choices according to their preferences and potentially influence the provision of environmental public goods. Our framework is based on the assumption that the label is the only way for consumers to obtain information about goods. We consider that there are no other types of information that can change consumers' perceptions. Depending on whether there is a label or not, the consumer does not perceive the same information on this good, although this one keeps the same characteristics. In the first market, with the environmental label, consumers know that good 𝑔 is produced using environmentally friendly practices. They have no a priori information on its health benefits. The second market offers a conventional product and a product with a label guaranteeing health benefits. Consumers know that good 𝑔 provides higher health benefits than good 𝑐; however, they have no information on the environmental impact of the agricultural practices associated with their production. In the third market, we assume that the information is complete for consumers based on its label, which identifies both the environmental and health benefits of the product 𝑔.

Each individual 𝑖 can allocate his wealth 𝑟 𝑖 to purchase a quantity 𝑐 𝑖 of conventional good 𝑐 at price 𝑝 𝑐 and a quantity 𝑔 𝑖 of impure public good 𝑔 at price 𝑝 𝑔 , such that 𝑝 𝑐 𝑐 𝑖 + 𝑝 𝑔 𝑔 𝑖 ≤ 𝑟 𝑖 . It is assumed that 𝑝 𝑔 > 𝑝 𝑐 to ensure the viability of the conventional good on the market, which implies that buying good 𝑐 is the most inexpensive method of obtaining private characteristic 𝑋.

Regarding agricultural technologies, buying one unit of 𝑐 leads to the provision of one unit of 𝑋 while buying one unit of 𝑔 leads to the provision of one unit of 𝑋, 𝛼 units of 𝐻 and 𝛽 units of 𝑌, with 𝛼 > 0 and 𝛽 > 0. These technological parameters are considered exogenous and known to all consumers when this information is provided on the product label. The relation between the quantities of goods 𝑐 𝑖 and 𝑔 𝑖 and the consumption of the characteristics 𝑋 𝑖 , 𝐻 𝑖 and 𝑌 𝑖 is then defined by 𝑋 𝑖 = 𝑐 𝑖 + 𝑔 𝑖 , 𝐻 𝑖 = 𝛼𝑔 𝑖 and 𝑌 = 𝛽𝑔 𝑖 + 𝛽𝑔 -𝑖 . Given these relations, the utility function can be rewritten as follows: 𝑈 𝑖 (𝑐 𝑖 + 𝑔 𝑖 , 𝛼𝑔 𝑖 , 𝛽𝑔 𝑖 + 𝛽𝑔 -𝑖 ). We consider an economy with production to obtain the market equilibria (and not just consumer equilibria).

Even if our paper focuses on the analysis of consumer behavior, it is interesting to consider the behavior of producers when discussing the assumptions made about production technologies.

In addition, the analytical framework we propose could be used in further research to focus on producer behavior. Here, we consider one representative producer who produces the two goods 𝑐 and 𝑔, subject to technological constraints represented by 𝑇(𝑐, 𝑔) = 0. Since 𝑝 𝑔 > 𝑝 𝑐 , the marginal cost of producing good 𝑔 must be greater than the marginal cost of producing good 𝑐 to prevent the producer from producing only good 𝑔.

Optimal regulation of our economy

In this section, we describe the optimal conditions that characterize our economy from the perspective of a social planner, an environmental agency and a health agency. The social planner seeks a Pareto optimal outcome by considering both the health and environmental characteristics of the food products. In contrast, we assume that the environmental agency seeks to optimize the total utility of the consumers without considering the health benefits of the products while the health agency seeks to optimize the total utility without considering the environmental benefits of the products.

Social optimum

If a social planner could choose the optimal level of public good provision, he would maximize correspond to the marginal rate of substitution between two characteristics, i.e., the change in the quantity consumed of one characteristic required to keep its utility constant following a change in the quantity consumed of the other characteristic. In the presence of a public good, we have to consider the sum of the marginal willingness to pay for this public good over all consumers since the quantity of public good consumed is the same for all (Bowen-Lindahl-Samuelson condition) [START_REF] Samuelson | Contrast between Welfare Conditions for Joint Supply and for Public Goods[END_REF][START_REF] Samuelson | The Pure Theory of Public Expenditure[END_REF].

Environmental agency's optimum

If an environmental agency has the ability to choose the optimal level of public good provision, it would only consider food production 𝑋 𝑖 and the public good 𝑌 jointly produced with 𝑔. The optimal condition for an environmental agency corresponds to the optimal condition (Equation (5.4)) with 𝛼 = 0 since this agency does not consider the health benefits of consumption of good 𝑔. In the presence of a private good and a public good, state intervention, such as by an environmental agency, is justified to ensure the provision of the public good. Assuming perfect information from the state, the optimal provision of 𝑌 could be achieved by collecting a tax equal to ∑ 𝜕𝑈 𝑖 𝜕𝑌 𝑒𝑎 ⁄ 𝜕𝑈 𝑖 𝜕 ⁄ 𝑋 𝑖 𝑒𝑎 𝑖 on consumers' income to subsidize the production of good 𝑔. In this case (and in theory), the provision of public good would be optimal according to the condition defined in equation (5.5). In practice, the state has only imperfect information, notably concerning the costs of providing a public good and the willingness of consumers to pay. Then, the real provision of the public good is below its optimal level.

Health agency's optimum

If a health agency had the ability to choose the optimal level of public good provision, it would only consider food production 𝑋 𝑖 and the private good 𝐻 𝑖 jointly produced with 𝑔. The optimal condition for a health agency corresponds to the optimal condition (Equation (5.4)) with 𝛽 = 0 since this agency does not consider the environmental benefits of consumption of good 𝑔. (5.6) Where 𝑋 𝑖 ℎ𝑎 and 𝐻 𝑖 ℎ𝑎 correspond to the optimal demand from the health agency perspective for private and public characteristics of goods 𝑔 and 𝑐.The marginal rates of substitution between the two private characteristics must be equal to the marginal rate of transformation between the two goods. The corresponding public consumption 𝑌 ℎ𝑎 is obtained from 𝑌 ℎ𝑎 = 𝛽𝑔 ℎ𝑎 * when 𝑔 ℎ𝑎 * solves the optimization program of the health agency.

Compared with the environmental agency, the health agency has no role to play and does not need to intervene in this market as long as information on the health benefits of an agricultural product is given to consumers, since any market equilibrium is Pareto optimal in a market characterized by private goods. Consumer demand for characteristic 𝐻 is therefore optimal without state intervention. If health information is not provided, the health agency can intervene, for instance by taxing unhealthy food consumption [START_REF] Allcott | Regressive Sin Taxes, With an Application To the Optimal Soda Tax[END_REF][START_REF] Griffith | Corrective taxation and internalities from food consumption[END_REF].

Equilibria under different levels of information

In this section, we derive the different market equilibria according to the level of consumer information on the products and compare these equilibria to the regulators' optima defined in the previous section. The benefits on the environment and health associated with the consumption of goods are present in each economy. The three market settings only differ in terms of the information available to consumers (label).

Health and environment label

This part presents the market equilibrium conditions under complete information provided by a label that identifies the environmental and nutritional qualities of product (5.10) where𝑋 𝑖 𝑒ℎ , 𝐻 𝑖 𝑒ℎ and 𝑌 𝑒ℎ correspond to the demand for private and public characteristics of goods 𝑔 and 𝑐 at equilibrium in a market characterized by health and environment label. The willingness to pay for the health and environment labelled product is equal to the sum of the marginal utility of the health characteristic and the marginal utility of the public characteristic.

In the case of a single consumer, this equilibrium condition coincides with the socially optimal condition defined in equation (5.4). In this case, the full information equilibrium is then socially optimal. In other words, the inefficiency of the full information equilibrium in the case of several consumers only comes from the absence of considering the externality created by 𝑔 𝑖 by each consumer on the others, as we can see from the formulation. When comparing equation (5.10) to the optimality condition of the environmental agency (5.5), we notice that the environmental efficiency of the health and environment label will depends on the relative marginal utilities of the health and environmental characteristic, while the health and environment label reaches the optimal amount of health provision targeted by a health agency (Equation (5.6)).

Environment label

In the second market setting, we assume that consumers know that good 𝑔 is produced using environmentally friendly practices. However, they have no a priori information on the health benefits of the product, although they exist. Each consumer 𝑖 maximizes his utility function under his budget constraint. The first-order conditions are derived only in relation to the product characteristics known by the consumers, i.e., 𝑋 𝑖 and 𝑌. These conditions, which are associated with the producer's equilibrium, lead to the following market equilibrium condition: (5.11) where 𝑋 𝑖 𝑒 , 𝐻 𝑖 𝑒 and 𝑌 𝑒 correspond to the demand for private and public characteristics of goods 𝑔 and 𝑐 at equilibrium in a market characterized by an environmental label. These conditions also correspond to the market equilibrium of the green consumption model of [START_REF] Kötchen | Impure public goods and the comparative statics of environmentally friendly consumption[END_REF].

𝛽 𝜕𝑈 𝑖 𝜕𝑌 𝑒 ⁄ 𝜕𝑈 𝑖 𝜕𝑋 𝑖 𝑒 ⁄ = 𝜕𝑇(𝑐,𝑔) 𝜕𝑔 ⁄ 𝜕𝑇(𝑐,𝑔) 𝜕𝑐 ⁄ -1 ,
Each agent does not consider that the financed public good provision also benefits other agents.

Agent 𝑖 contributes to providing the public good until the marginal cost of the private good is equal to its marginal rate of substitution. Consequently, consumers as a whole contribute less to the public good than what would be desirable to achieve Pareto optimality or the environmental agency's optimality.

Health label

In this third market setting, we assume that consumers know that good 𝑔 has superior nutritional qualities compared with good 𝑐 but have no information on the environmental impact of the agricultural practices associated with the production process. (5.12) where 𝑋 𝑖 ℎ and 𝐻 𝑖 ℎ correspond to the demand for private and public characteristics of goods 𝑔 and 𝑐 at equilibrium in a market characterized by a health label. Classically, the market equilibrium leads to the optimal provision of private characteristics from the perspective of a health regulator (see Equation (5.6)).

Even if consumers do not have information on the positive environmental externality associated with their consumption, the public good 𝑌 is provided jointly with the production of good 𝑔.

The quantity of public characteristics 𝑌 provided through the consumption of good 𝑔 is thus equal to the sum of the quantities of private characteristics 𝐻 𝑖 consumed by all consumers multiplied by the ratio of the technology parameters, such as the following:

𝑌 ℎ = 𝛽 𝛼 ∑ 𝐻 𝑖 ℎ 𝑖 .
( 5.13) This equation reflects the jointness of production between environmental and health characteristics, with the ratio 𝛽 𝛼 ⁄ corresponding to the intensity of this jointness. Substituting

As previously defined, 𝑌 𝑒 , 𝑌 ℎ and 𝑌 𝑒ℎ correspond to the equilibrium provisioning of a public good with an environment, a health label, and a health and environment label, respectively.

𝑌 𝑒 = 𝛽 ( The weight of preferences for health and/or environment, which are represented by a ratio depending on 𝜃 𝑋 , 𝜃 𝑌 and 𝜃 𝐻 , has an important impact on the level of public good provided by the three types of labels. This ratio describes the consumers' willingness to pay for these characteristics. With the environmental label, the market failure is such that the preference for the environment 𝜃 𝑌 is individualized (Equation (5.16)). Consumers do not consider the willingness of other consumers to pay for this public characteristic. Rather, they only consider their willingness to pay, which is translated in the model as a level of preference divided by the number of consumers ( 𝜃 𝑌 𝐼 ⁄ ). In an optimal situation from an environmental agency's perspective, the ratio of preferences would be equal to 𝜃 𝑌 (𝜃 𝑋 + 𝜃 𝑌 ) ⁄ . The level of public good provided with an environmental label is therefore much lower than those provided in optimal situations (all the more so as the size of the market is large). In contrast, in the case where 𝜃 𝑌 = 𝜃 𝐻 and prices of goods are the same across market settings, the level of public good provided by the health label is optimal in the sense of an environmental agency (Equation (5.17)). The provision of public good by the health and environment label (Equation (5.18)) also suffers from an underestimation of the consumers' willingness to pay for 𝑌. Similar to the environmental label, preferences for the environment appear individualized. On the other hand, consumers' willingness to pay for health greatly increases the supply of public goods, and the provision of public good can reach the optimal amount targeted by an environmental agency under certain conditions of relative preferences for health and the environment.

When information is incomplete and consumers only have access to information on one of the two complementary characteristics (environmental label or health label), more public goods are provided through the market of a health label in most situations. Assuming identical prices between the environment-labeled and health-labeled good g, an environmental label leads to higher provisioning of the public good only for a case characterized by a very small market associated with a significantly higher preference for environmental characteristics than health characteristics (dividing the expression of Equations (5.16) and ( 5.17) leads to the condition 𝜃 𝑌 𝜃 𝐻 ⁄ > 𝐼, in which the environmental label provides more public good). Under perfect information (health and environment label) and when consumers exhibit preferences for the three characteristics (𝜃 𝑋 , 𝜃 𝑌 , 𝜃 𝐻 > 0), the provision of the public good is always higher than the market outcomes of an environmental label or a health label.

Our analysis shows that preference parameters influence market outcomes. This is an expected result because the impact of individual preferences has been highlighted in numerous studies on consumer demand and differentiated market efficiency [START_REF] Aldanondo-Ochoa | The private provision of public environment: consumer preferences for organic production systems[END_REF][START_REF] Brécard | Consumer preferences for eco, health and fair trade labels. An application to seafood product in France[END_REF][START_REF] Brécard | Determinants of demand for green products: an application to eco-label demand for fish in Europe[END_REF][START_REF] Lusk | Public preferences and private choices: effect of altruism and free riding on demand for environmentally certified pork[END_REF][START_REF] Moon | Willingness to pay for environmental practices: implications for eco-labeling[END_REF][START_REF] Schifferstein | Health-related determinants of organic food consumption in the Netherlands[END_REF]. This literature also emphasizes that consumer preferences are heterogeneous.

Moreover, consumers with high preferences for the environment may have different socioeconomic characteristics than those with high preferences for health. On the one hand, willingness to pay for environmental attributes increases with income, altruism, education and environmental awareness and decreases with age (Aldanondo-Ochoa and Almansa-Sáez, 2009; [START_REF] Brécard | Determinants of demand for green products: an application to eco-label demand for fish in Europe[END_REF][START_REF] Lusk | Public preferences and private choices: effect of altruism and free riding on demand for environmentally certified pork[END_REF][START_REF] Moon | Willingness to pay for environmental practices: implications for eco-labeling[END_REF]. On the other hand, willingness to pay for health attributes decreases with education and increases with age [START_REF] Brécard | Consumer preferences for eco, health and fair trade labels. An application to seafood product in France[END_REF][START_REF] Govindasamy | Predicting willingness-to-pay a premium for organically grown fresh produce[END_REF][START_REF] Schifferstein | Health-related determinants of organic food consumption in the Netherlands[END_REF]. In this section, we do not account for this heterogeneity, although we know it exists. We focus on the market outcome considering the behavior of a consumer representative of the average preferences of the population. Adding heterogeneity might introduce additional nuancing elements but would not affect the overall results and conclusions.

We have calculated the quantities of goods 𝑔 and 𝑐 at consumer equilibrium, which allows us to derive the demand for public good 𝑌 in each market characterized by a specific type of label.

We observe that the demand for the public good is higher when consumers have information on the health benefits of consuming good 𝑔. However, these public good demands are not directly comparable since the prices of goods 𝑔 and 𝑐 are not the same from one market to

another. An increase in the demand for good 𝑔 will lead to an increase in the production of this good 𝑔 and therefore an increase in its marginal cost, which will be borne by the producer. The selling price of good 𝑔 will adjust upwards so that it equals its marginal cost. The increase in the price of good 𝑔 will therefore reduce the initial demand for good 𝑔 until an equilibrium price, allowing supply and demand to be equalized, is reached. Thus, although the supply of public good will always be higher when the health attribute is valued, the difference in public good 𝑌 provided by the different labels will be mitigated by the increase in the price of good 𝑔.

To compensate for this, the behavior of the producer must be considered, which will be explored in the following section using a simulation.

Simulations of different market equilibria

A simulation is performed to observe the evolution of the provision of 𝑌 at the equilibrium of the different markets according to the levels of preference for health and the environment of consumers. In the simulation, we consider a market of 50 consumers who each have an income of 5 to allocate to the purchase of good 𝑐 and/or good 𝑔, which is produced by a single producer.

We characterize the production technologies of goods 𝑐 and 𝑔 simply, such that several assumptions are met. First, the production of one unit of good 𝑔 requires less polluting inputs than the production of one unit of good 𝑐. Second, the marginal cost of producing good 𝑔 is higher than the marginal cost of producing good 𝑐. If the price of good 𝑔 was less than or equal to the price of good 𝑐 , good 𝑐 would never be consumed. The assumptions made about production technologies are detailed in Appendix A8.

We assume that consumers have a preference 𝜃 𝑋 for characteristic 𝑋 equal to 0.8. This preference represents consumers' need for nutrition. The preference for health 𝜃 𝑋 is set to 0.2.

We vary the value of the preference for the environment 𝜃 𝑌 so that the ratio 𝜃 𝑌 𝜃 𝐻 ⁄ varies between 0 and 4. A ratio close to 0 means that the consumer preference for the environment is close to zero or very much lower than the consumer preference for health. A ratio equal to 1 means that the preference for the environment is the same as that for health. The higher the ratio is, the stronger the preference for the environment than for health. For each of the values of this ratio, we calculate the equilibrium prices 𝑝 𝑐 and 𝑝 𝑔 , which equalize the supply and demand in different markets and thus the level of public goods supplied. Figure 5.1. shows the evolution of public good provision at equilibrium in the three economies with labels and at the optimum (social and environmental agency) according to the ratio of preferences for the environment and health and the size of the market.

𝜃 𝑌 / 𝜃 𝐻 is less than 1. Promoting private attributes, such as health, to stimulate the consumption of environmentally friendly products contributes to the provisioning of more Y than an alternative, such as subsidies driven by the environmental agency. Moreover, in this case, the difference with the Pareto optimal Y is the smallest.

We also show that market size does not affect the relative environmental performance of the types of labels. Indeed, with 50 consumers, the environmental label provision will start surpassing the health label provision when preferences for the environment are at least 50 times higher than for health, which is very unlikely in a real life setting. Moreover, the larger the population, the less effective the environmental label and the smaller the difference of provisions between the health and environment label and the health label. This finding suggests that adding information on the joint production of a public characteristic to a label that initially promoted a private characteristic has a negligible environmental impact in a large market.

We can imagine the implementation of an aid to producers to encourage them to have more environmentally friendly practices. In our model, this practice would correspond to a decrease in the marginal cost of production of good 𝑔. The equilibrium price of good 𝑔 would therefore be lower than its price without subsidies. In all labelling scenarios, the provision of public good would be stimulated. Even if the provision of public good is always higher in the case of the health and environment label, the variation of public good provided (with and without subvention) is stronger in the case of the environmental label. An economic incentive for good agricultural practices reduces the gap between the different labels and improves the efficiency of the environmental label compared to other labels.

These results are also dependent on the characteristics of the production technologies used to produce the goods and of the producers, which are in practice very heterogeneous. A producer who can adapt to price variations by changing the quantity of inputs used and outputs produced (that correspond to a weaker parameter 𝛾, see Appendix A8) will provide more public goods under different labels. On the other hand, a technological improvement that would increase the productivity of the less-polluting input (by further lowering the value of 𝜂 𝑔 , see Appendix A8)

would not change the quantity of good 𝑔 produced but would improve the environmental benefit. This would correspond to an increase in the technological parameter 𝛽 , which represents the amount of public characteristics provided by the consumption of one unit of good 𝑔.

Conclusion

In this paper, we investigate the potential of markets for a healthy and environmentally friendly good to contribute to improving environmental public good provisioning. Our model applies when environmentally friendly agricultural practices jointly improve the nutritional quality (or any other intrinsic characteristic) of an agricultural product. That is, when health and environmental characteristics are complementary.

The theoretical analysis provides two main results. First, when consumers only have access to partial information on one of the two complementary characteristics (environment label or health label), only a health label leads to the optimal amount of public good provisioning from the perspective of an environmental agency under certain conditions. Second, providing full information on the public and private characteristics of the agricultural product increases the (i) environmental benefits compared with an ecolabel and (ii) environmental benefits compared with a health label. The extent of this increase depends mainly on the consumers' preferences and market size. Indeed, the difference between a health label and a health and environment label becomes less when consumer preference for health is higher than for the environment.

Our approach relies on several hypotheses. First, we assume no additional cost of labeling on two characteristics rather than one. In practice, the costs of the transaction and the costs of providing, disseminating and processing information in particular are likely to modify market outcomes in many cases. Second, our results are valid under the assumptions of convexity of consumer preferences and the production set. In particular, our assumption of homothetic preferences implies constant income elasticity of demand. For many types of food products, demands for health and environmental quality characteristics are likely to be income elastic [START_REF] Clements | Engel's law, diet diversity, and the quality of food consumption[END_REF][START_REF] Markusen | Per-Capita Income As a Determinant of International Trade[END_REF]. In a multiconsumer economy, nonhomothetic utility functions (e.g., with Stone-Geary preferences) could capture income-related effects on the demand for characteristics. One could, for example, assume there is no demand for health and/or environmental quality below a threshold income level. This would result in health labeling having an even stronger positive effect on public goods provision as population income increases. Third, we consider well-defined complementary joint production. Natural processes underlying joint production are complex and often context-dependent. Thus, it might not always be technically feasible to link an agricultural commodity to a measured health and/or environmental attribute.

The combined effects of environmental, nutritional, health and taste characteristics is a topic of many ongoing debates [START_REF] Bougherara | Eco-labelled food products: What are consumers paying for?[END_REF]. While some complementarities are based on consumers' perceptions without scientific proof, others have been extensively studied and documented. Even if the organic label is initially an environmental label, it can be considered as a health and environment label in our analysis framework since consumers associate a private benefit related to health. Other examples of food labels based on a strict complementarity between health and environmental characteristics do exist. The French quality BBC (Bleu-Blanc-Coeur) branch provides a good illustration. The BBC label was created in the early 2000s to offer consumers differentiated animal products that provide nutritional benefits to human health by enriching the diet of livestock with sources of omega-3 fatty acids [START_REF] Weill | Effects of introducing linseed in livestock diet on blood fatty acid composition of consumers of animal products[END_REF]. In parallel to the development of the BBC market, new research has emerged showing that enteric methane emissions decline as ruminant feed is enriched with unsaturated omega-3 fatty [START_REF] Dong | Lipid induced depression of methane production and digestibility in the artificial rumen system (RUSITEC)[END_REF][START_REF] Grainger | Can enteric methane emissions from ruminants be lowered without lowering their production[END_REF][START_REF] Martin | Methane output and rumen microbiota in dairy cows in response to long-term supplementation with linseed or rapeseed of grass silage or pasture based diets[END_REF][START_REF] Martin | Methane output and diet digestibility in response to feeding dairy cows crude linseed, extruded linseed, or linseed oil[END_REF]. The availability of new information on the positive environmental impact of the BBC nutritional approach offered new perspectives. The label now communicates both the nutritional and environmental attributes of dairy products. The nutritional and environmental importance of the BBC approach has by officially recognized by the French government. Our theoretical analysis suggests that a health and environment label such as the BBC label would contribute more to methane emissions abatement than a dairy environmental label to the reduction of enteric methane emissions.

The European Commission recently presented its Farm to Fork strategy as part of the Green Deal with the objective of developing labels promoting both health and environmental benefits.

Our results suggest that from an environmental policy perspective, nutritional and health labeling is a relevant tool to increase public goods provisioning and complement agrienvironmental subsidies. In addition to supporting the development of labels, policy makers have a role in reducing information asymmetries regarding the reliability and accuracy of the information they carry.

Our findings highlight interesting directions for future research. In a context where consumer preferences for health are strong, knowledge on the impacts of agricultural practices on human health must be strengthened and environmentally friendly agricultural practices that produce healthy products must be encouraged. For example, labeling goods produced without pesticides, for which consumers have a real willingness to pay [START_REF] Florax | A meta-analysis of the willingness to pay for reductions in pesticide risk exposure[END_REF], seems to be an interesting lever for reducing the use of pesticides. Similarly, it would be interesting to promote research on the evaluation of consumers' willingness to pay for private characteristics (nutrition, health, taste, and social value) for several types of goods produced in an environmentally friendly way. This would allow us to identify the information that should be communicated to consumers via labels. They can be of many types and exhibit heterogeneous preferences and willingness to pay. From the existing schemes in the EU, we identify taxpayers at different levels (EU, national, local), consumers of food commodities, and private organisations (companies, agencies, associations…). The set of rules characterises the condition(s) for the payment to be delivered to the farmer. In particular, we can distinguish commitments on agricultural practices and/or environmental targets. On the demand side, the literature shows evidence that ES provision is largely underfunded through the existing payment channels. On the supply side, the literature reveals the inadequacy of current PES to meet ambitions, mainly from the observation that participation of farmers is low and their environmental additionality insufficient. Low participation shows that PES are not profitable for most farmers (which can be related to low funding from the demand side). Low environmental additionality is both the result of low participation and poor instrument design. In my PhD, I study two key dimensions to increase PES effectiveness: capturing more willingness to pay from contributors, and adapting the payment mechanism to the technical problem addressed.

Chapter 6. General conclusion

Main contributions

The first type of PES mechanism I analyse is public support dedicated to voluntary environmental commitments of farmers within the framework of the common agricultural policy (CAP). The main PES currently implemented in the EU are 5-years contracts for implementing AECM or organic practices. Empirical data shows that there is a gap between the stated priorities of the CAP and their relative budget. In particular, the budget dedicated to supporting environment-friendly agricultural practices is low in comparison with the budget for direct payments to farmers which have no or little environmental conditionality. In the second chapter, I study a policy lever to upscale environmental incentives and increase the uptake of public PES by farmers. I evaluate the impact of a budget transfer from direct payments towards support for the voluntary adoption of AECM and organic farming (OFS) in France. This option aims at increasing the public funding of environmental incentives without raising taxpayers' contributions. Participation in a PES results from a farm-level decision process influenced by many factors, including eligibility and the characteristics of the PES proposed by public authorities, and farm characteristics. We further assume it can be affected by interactions with price signals from other CAP instruments. We apply a generalised Tobit to model farmers' voluntary adoption of AECM and OFS at the farm level, with a system of two simultaneous equations representing the probability to adopt a contract, and the minimum farm-level payment triggering this adoption. We assess the effect of direct payments, and use the estimates to simulate a change of budget allocation from direct payments to environmental incentives. The ex-ante evaluation method proposed is developed with panel data from the French farm accountancy data network (FADN), and can be reproduced for other EU countries. A difficulty lies in overcoming missing information on the eligibility of farmers to AECM and/or OFS with a large set of control variables. We identify two effects of the budget transfer mechanism. The direct effect is a bigger budget available for meeting the supply of environmental commitments by more farmers and financing the adoption of more measures. The indirect effects of the reduction of direct payments on farmers' behaviour are heterogeneous according to the farm type. In our transfer simulations, constrained by the current regulation (maximum 15% of direct payments), indirect effects are of limited extent and suggest that cutting into direct payments would not affect much the profitability of adopting environment-friendly practices. It calls for the implementation of complementary measures aiming at improving the environmental effectiveness of the public provision of public goods. Given the lower public budget allocated to the CAP for the 2023-2027 period, there is a need to rethink the design of positive incentives for environmentally sound agricultural practices and seek other contributors to complement taxpayers. In addition, contrary to the current AECM designed mainly through a supply-side approach, more efficient PES should better integrate the demand of ES.

In the third and fourth chapters, I study more specifically the design of payment mechanisms dedicated to ES. Based on the example of two specific PES, a hypothetical one and a real-life case study, I show how cost-effectiveness can be enhanced by adapting the targeting of conditionality rules to the environmental and technical problems addressed by the scheme.

In the third chapter, I focus on the delivery of public goods with threshold effects, such as biodiversity and water quality. However, its acceptability is lower when combined with a collective result bonus. We also show that preferences for conditional bonuses are heterogeneous and characterise this heterogeneity.

In particular, this study suggests that introducing a bonus rewarding individual effort to convince new farmers to adopt the scheme is promising to promote landscape approaches, while collective bonuses distributed equally to all might be counterproductive as long as the payment for individual commitments is not high enough.

The Results stress the relevance of using an indicator sensitive to diet when defining economic incentives to precisely measure farmers' effort for reducing enteric emissions. We also show that dairy systems are heterogeneous when it comes to the extra-costs they face for changing practices. Most farms exhibit significant and high additional costs, in particular plain farms with a large share of grasslands and mountain farms. To support a large-scale transition, the payment level should be sufficiently high to exceed those costs, or modulated according to the dairy system.

Throughout my PhD, I manipulated different types of data. Secondary data is useful to conduct analyses representative of the farming population when it comes to the modelling of PES adoption behaviour (chapter 2) and extra-costs (chapter 4). Collecting primary data in chapter 3 allows to measure farmers preferences for a hypothetical PES with the possibility of getting 124 rid of current budget constraints. We could introduce attributes that are not observed in current data and make ex-ante contributions.

In the modelling approaches, I represented PES considering different scales: the aggregate policy scale in chapter 2, the contract scale in chapter 3 and the payment design scale in chapter 4. This multi-scale approach allows to get a broader picture on the different factors of PES environmental effectiveness and their limits, each one providing insights into the incentive signal sent to farmers. At the policy scale, the effectiveness of PES can be improved by better targeting the budget available (contributions from taxpayers) towards instruments for the provision of public goods. At the scale of the PES design, introducing new payment conditionality mechanisms such as collective and/or result-based incentives adapted to the public good targeted should boost the achievement of environmental results, on the condition that they are accepted and largely adopted by farmers. Hence, the improvement of PES design goes hand in hand with ensuring the payment level exceeds the willingness to accept of farmers.

Allowing for contributions from a diversity of contributors with a willingness to accept can help raising enough budget. The three empirical approaches also contribute to characterise the heterogeneity of farming systems: profitability of adoption environment-friendly practices This observation led to pose the theoretical problem of how to increase the willingness to pay for ES in the fifth chapter. I focus on consumers, as they are the last stage of the food supply chain and as such, can send a price signal for the agricultural and food sector along all the value chain. Since the empirical literature suggests consumers care about their health when buying environment-friendly food products, we develop a theoretical model to show that health concerns can efficiently finance ES provision. The theoretical model proposes to capture additional contributions from consumers, and in particular, if there are private benefits to consume food products produced in an environment-friendly way. On the supply side, we consider the special case of an agri-environmental production technology that jointly provides 125 an ES and a food commodity with superior health benefits in comparison with a conventional agricultural technology. On the demand side, consumers have a choice between the food commodity produced with the conventional agricultural practices or with the environmentfriendly practices. Expanding the impure public good model, we consider three market settings.

One in which the consumers are provided with incomplete information that the "green" product jointly provides an environmental public good (environmental label), one in which they are provided with the incomplete information that it provides private health benefits (health label), and one in which they are provided with the full information (health and environment label).

We consider homogeneous consumers and derive the market equilibria of the three market settings. Results show a health label leads to higher public good provisioning than an environmental label in most cases, with full information leading to the highest provision.

Moreover, while there is underprovision of the public good in the sense of Pareto in all market settings, health labelling can lead to the optimal provisioning of the public good sought by an environmental agency (efficient market) if consumers' preferences for health are high enough relative to their preferences for the environment. While PES initiatives from the private sector favours inefficiency problems from free riding of voluntary contributors, our theoretical results

show that attaching private benefits to the funding of ES can temperate it. When it is possible to identify private benefits to the provision of ES, value chain included PES can be efficient instruments to complement agri-environmental policies. Investigations to understand the scope and diversity of joint production technologies might be fruitful to identify key private benefits valuable for consumers.

Main limits

The first type of limitations to the generalisation of the findings are that they rely on assumptions we had to make to overcome missing information from the available data.

Empirical results of chapter 2 and 4 are derived from the FADN, which contains little information to precisely characterise agricultural practices and environmental services implemented at the farm level. Linking the adoption of a PES to changes of agricultural practices and to environmental outcomes required making assumptions. The European Commission initiative and roadmap for the conversion of the FADN to the Farm Sustainability Data Network (FSDN) will facilitate modelling of farmers' change of practices in the future (EC, 2022a).

In chapter 2, we estimate a farm-level acceptable payment using a large set of control variables describing the farm system and its size, to overcome the lack of information on the type of environmental commitments, payment amount per hectare and surfaces enrolled of participating farms. Yet, the inter-individual heterogeneity of participating farms and AECM measures is very high, and our current model fails to capture enough of it to reproduce accurately the observed behaviour. In particular, it tends to underestimate AECM adoption probabilities. It affects the robustness of the results and the quality of the simulations.

In chapter 4, to overcome the absence of data on the composition of dairy cows ration and on farm GHG emissions, an increase of the use of omega-3 rich feed in the diet of dairy cows is approximated by an increase of agricultural area dedicated to grass fodder production to evaluate the extra variable costs. Hence, we only characterise farms extra-costs heterogeneity for this specific lever. Information on grasslands yields would be necessary to evaluate extracosts of more grass fodders more precisely. Moreover, Eco-Methane participants also add feed complements to increase sources of omega-3 in cows ration (such as linseed). Due to the absence of information on their purchase, we could not take this lever into account.

A limitation to the generalisation of the findings of chapter 3 is the biased sample collected to conduct the choice experiment, which is not representative of the farming systems of the regions targeted. This is mainly due to the sampling procedure which could not be randomized to follow the general data protection regulation. As a result, the sample is biased towards the population already the most likely to be willing to enroll in a PES and already implementing ambitious environmental services (such as organic or highly educated farmers). We are likely underestimating the actual willingness to accept of farmers for adopting the hypothetical contract evaluated. Moreover, inherent to the survey-based methodology used, results on preferences for the bonus options are likely to change in another area, depending on the context.

In addition, there are further limitations due to the scope of the studies.

In chapter 4, we study an economic incentive to reduce enteric methane emissions by increasing grasslands area on dairy farms. Accounting for spillovers of more grass on other GHG emissions (or farmland biodiversity) would better capture the environmental impact of such a result-based PES. Moreover, the environmental effectiveness of PES for reducing GHG emissions per unit of product depends on not increasing total emissions. Hence, complementary levers are needed to ensure that production levels and demand for livestock products do not increase. It calls for a change of EU consumers' diet towards more plant-based products.

In chapter 5, we build a theoretical framework based on an assumption of complementary provision of health and environmental benefits by environment-friendly practices. This case does not apply to all types of environment-friendly practices, some of which cannot be linked to quality and/or nutritional improvements of the food product. We also consider a linear relationship between health benefits and public good provision, and do not account for consumers' heterogeneity. Relaxing one of those assumptions would affect the extent of our findings. For instance, results are not applicable for the case of local public goods, as not all consumers would benefit from public good provision and exhibit a willingness to pay for it. We can however assume health labelling would even more outperform environmental labelling in the case of local public good provision, strengthening the scope of our result.

I remain with further questions I could not pursue do to a lack of time and means.

Regarding the voluntary adoption model in chapter 2, I see two possibilities to improve the robustness of the model and the simulations. First, the econometric approach could be developed, in particular by better capturing individual fixed effects with panel estimation, for instance by distinguishing the mean values over the 5 years analyzed and the difference to the mean on a yearly basisevery year for all covariates potentially varying from one year to another.

This would better capture the supply of environmental commitments. To better characterize the demand from public authorities, adding more information on the type of AECM adopted by FADN farms and eligibile areas is feasible by matching with the dataset on the beneficiaries of the CAP second pillar payments. This would give us access to the type of AECM and the payment per hectare enrolled for this specific measure.

To identify the optimal level of incentive for adding more grass in dairy systems in chapter 4, I was constrained with the unavailability of representative data allowing to link enteric methane emissions to fodder rotation systems. Ideally, an interesting output would be to answer the question: for an announced price of tCO2eq, how many dairy farmers would be willing to participate in a PES like Eco-Methane? The idea would have then been to link the extra-costs of changing practices (grass surfaces) to units of ES (reduction of enteric methane emissions in tCO2eq). It could have been done by working together with the Bleu-Blanc-Coeur association Vous avez 50 ha de SAU répartis en 25 ha de prairies permanentes et 25 ha de cultures arables.

1/ Il faudrait implanter 50 X 100 = 5000 m linéaire de haies 2/ 25 ha de votre SAU sont à 100% couverts (prairies permanentes). Pour arriver à un taux de couverture de 95% de la SAU totale, il faut que le taux de couverture sur les 25 ha de cultures arables soit de 90%, ce qui correspondant à 365 X 90% = 328,5 jours de sols couverts. Vous ne devez donc pas avoir plus de 36 jours de sols nus pour ces 25 ha de cultures arables.

Vous ne devrez pas avoir plus de 36 jours de sol non couvert sur les terres arables.

3/ Vous recevrez 22 500€/an de paiement individuel. Si l'objectif de qualité de l'eau est atteint, vous recevrez 2 500€/an supplémentaire.

Si vous convainquez un agriculteur de se joindre au programme, vous disposeriez de 450€ supplémentaire par agriculteur parrainé.

Exemple contrat B :

Si vous avez 50 ha de SAU dont 25 ha de prairies permanentes (couvertes à 100%) et 25 de cultures arables.

1/ Il faudrait implanter 50*600= 3000m linéaire de haies.

2/ 25 ha de votre SAU sont à 100% couverts. Pour arriver à un taux de couverture de 85% de la SAU totale, il faut que le taux de couverture sur les 25 ha de cultures arables soit de 70%, ce qui correspondant à 365 X 70% = 255 jours de sols couverts. Vous ne devez donc pas avoir plus de 109 jours de sols nus pour ces 25 ha de cultures arables. Title : Theoretical and empirical analysis of dedicated and food chain included payments for environmental services Keywords : environmental services, public good, agri-environmental policy, food labeling, willingness to pay, willingness to accept Abstract : This PhD thesis applies empirical and theoretical microeconomic approaches to analyse the efficiency of payments for environmental services in the agricultural sector. I assess levers to promote their adoption by farmers at different scales. I show empirically that targeting part of the income support of the Common Agricultural Policy towards increased funding of agri-environmental and climate measures and support for organic farming promotes participation in these schemes. My main contribution is to show that a sponsorship bonus in payments for environmental services is promising to encourage the participation of a critical mass of farmers when ecological threshold effects exist. The results of this thesis also suggest that result-based payments, in the form of a collective bonus or a payment proportional to an environmental indicator, are effective on the condition that the level of payment is sufficiently attractive. With a theoretical approach, I focus on the demand side and propose a tool, the health label, to increase consumers' willingness to pay in the particular case where the joint production technology of environmental services is complementary to the improvement of the intrinsic health quality of the agricultural commodity. I contribute to the literature by showing that consumers' health concerns can efficiently finance environmental services and complement agri-environmental policies.

  Figure S.1. Mécanismes de paiements pour services environnementaux pour remédier à la sous-provision des biens publics par l'agriculture.

Chapitre 2 .

 2 développons un modèle théorique de pour étudier la fourniture d'un bien public à travers trois labels (label environnemental, label santé, label santé et environnement), et dérivons les conditions d'optimalité en fonction des objectifs d'un planificateur social, d'une agence environnementale ou d'une agence sanitaire. xi Amplifier les incitations environnementales dans la politique agricole commune : une méthode d'évaluation ex ante appliquée avec le réseau d'information comptable agricole Dans ce chapitre co-écrit avec Pierre Dupraz, nous évaluons le levier d'un meilleur ciblage du budget public de la PAC vers des instruments de fourniture de biens publics. Les MAEC et le soutien à l'agriculture biologique sont les deux principaux instruments soutenant l'adoption de pratiques agricoles respectueuses de l'environnement dans l'Union Européenne depuis les années 90. Ils ont été insuffisants pour atteindre des améliorations environnementales significatives, notamment parce que sous-financés par rapport aux aides au revenu sans ou avec peu de conditionnalité environnementale (paiements directs). En utilisant les données du panel français du RICA de 2015-2019, un modèle Tobit généralisé est appliqué pour estimer simultanément la probabilité d'adopter un contrat environnemental et le paiement acceptable déclenchant cette décision pour chaque observation de l'échantillon et pour chaque type de contrat. Nous utilisons un large ensemble de variables de contrôle afin de surmonter le manque d'informations sur le type d'engagements, le montant du paiement par hectare et les surfaces contractualisées des exploitations participantes. Ce modèle d'adoption volontaire est utilisé pour simuler l'adoption des MAEC et du soutien à l'agriculture biologique si les paiements directs étaient diminués de 7,5% et que ce budget était redirigé vers le financement de dispositifs environnementaux en 2019.

Chapitre 4 .

 4 Prise en compte du régime alimentaire des vaches pour concevoir des paiements pour réduire les émissions de méthane entérique dans les exploitations laitières Une source d'inefficacité des PSE à obligation de moyens est qu'ils rémunèrent des pratiques sans additionnalité environnementale si les SE demandés ne sont pas assez ambitieux et/ou pas adaptés au bien public visé. Ce chapitre est co-écrit avec Sabine Duvaleix et Pierre Dupraz, et se concentre sur la conception de PSE à obligation de résultat.

Chapitre 6 .Table 1 . 2 .

 612 Conclusion généraleDans les approches de modélisation empirique, cette thèse étudie les PSE en considérant différentes échelles : l'échelle de la politique globale au chapitre 2, l'échelle du contrat au chapitre 3 et l'échelle de la conception du paiement au chapitre 4. Cette approche multi-échelle permet d'obtenir une image plus large des différents facteurs de l'efficacité environnementale des PSE et de leurs limites, chacun d'entre eux fournissant des informations sur le signal incitatif envoyé aux agriculteurs.Les résultats suggèrent qu'à l'échelle des politiques publiques, l'efficacité des PSE peut être améliorée en ciblant davantage le budget vers des instruments de fourniture de biens publics. À l'échelle de la conception du PSE, l'introduction de nouveaux mécanismes de conditionnalité des paiements, tels que des incitations collectives et/ou axées sur les résultats, adaptés au bien public visé, devrait favoriser l'obtention de résultats environnementaux, à condition qu'ils soient acceptés et largement adoptés par les agriculteurs. Par conséquent, l'amélioration de la conception des PSE va de pair avec la garantie que le niveau de paiement dépasse le consentement à recevoir des agriculteurs. Le fait d'autoriser les contributions d'une diversité de contributeurs avec un CAP peut aider à réunir un budget suffisant. Les trois approches empiriques contribuent également à caractériser l'hétérogénéité des systèmes agricoles en particulier en ce qui concerne la profitabilité de l'adoption des PSE (chapitre 2), l'acceptabilité des attributs du contrat (chapitre 3) et les surcoûts liés au changement de pratiques (chapitre 4). De plus, nos résultats théoriques (chapitre 5) montrent que lorsqu'il est possible d'identifier des avantages privés à la fourniture de SE, les PSE inclus dans la chaîne de valeur peuvent être des instruments efficaces pour compléter les politiques agro-environnementales. Des études scientifiques visant à comprendre l'étendue et la diversité des technologies de production jointes permettraient d'identifier les cas où cela ce levier pourrait s'appliquer. Les résultats empiriques des chapitres 2 et 4 sont dérivés d'analyses du RICA, qui contient peu d'informations permettant de caractériser précisément les pratiques agricoles et les SE mis en oeuvre au niveau de l'exploitation. Pour établir un lien entre l'adoption d'un PSE et les changements de pratiques agricoles et les résultats environnementaux, il a fallu formuler des hypothèses (fortes). L'initiative et la feuille de route de la Commission européenne pour la conversion du RICA en Réseau de données sur le développement durable des exploitations agricoles (FSDN) faciliteront la modélisation des changements de pratiques des agriculteurs à l'avenir (EC, 2022a). xvi Payments for environmental services mechanisms to allocate the willingness to pay of contributors in France. .................................................................................................. 18

2 .Table 3 . 3 .Table 3 . 4 .Table 3 . 5 .Table 3 . 6 .Table 4 . 1 .Table 4 . 2 .Table 4 . 3 .Table 4 . 4 .Table 4 . 5 .Table 5 . 1 . 1 .Figure 1 . 1 . 2 Figure 1 . 2 .Figure 1 . 3 .Figure 3 . 1 .Figure 3 . 2 .Figure 3 . 3 .Figure 4 . 1 .Figure 4 . 2 .Figure 5 . 1 .

 23334353641424344455111121213313233414251 Figure S.1. Mécanismes de paiements pour services environnementaux pour remédier à la sousprovision des biens publics par l'agriculture ............................................................................ vii Figure 1.1. Main interactions between agroecosystems and the environment. ......................... 2 Figure 1.2. The logic of payments for environmental services for securing land use conservation. ............................................................................................................................ 11 Figure 1.3. Payments for environmental services mechanisms to tackle the underprovision of public goods by agriculture. ..................................................................................................... 24 Figure 3.1. Example of choice set of the choice experiment................................................... 64 Figure 3.2. Distribution of the sampled farms in the surveyed regions (ratio). ...................... 66 Figure 3.3. Stated effect of contract design characteristics on willingness to adopt. .............. 68Figure 4.1. Distribution of Eco-Methane baseline scenarios among French regions. ............. 91 Figure 4.2. Average enteric emissions in French regions according to the TIER2 and Eco-Methane baseline indicators. .................................................................................................... 93 Figure 5.1. Simulation of public good provisions. ................................................................ 115

Figure 1 . 2 .

 12 Figure 1.2. The logic of payments for environmental services for securing land use conservation.

Figure 1 . 3 .

 13 Figure 1.3. Payments for environmental services mechanisms to tackle the underprovision of public goods by agriculture.

Chapter 2 to 5

 25 are research articles aiming at answering the research questions presented in the previous paragraph. Chapter 2 (Le Gloux and Dupraz) develops an empirical ex-ante evaluation method of a transfer of budget from direct payments to AECM and organic farming support within the framework of the CAP. Chapter 3 (Le Gloux, Dupraz, Issanchou, and Ropars-Collet) presents a choice experiment to empirically measure farmers' preferences for a PES contract with a bonus payment conditional on the sponsorship of other farmers on the territory and/or a collective environmental result. Chapter 4 explores empirically the design of a result-based PES for reducing enteric methane emissions from dairy cows. Chapter 5 develops a theoretical model of impure public goods and compares the provision of a global public good through three labels (environment label, health label and health and environment label) in the case where the provision of public good is complementary to the production of a healthy agricultural product. Chapter 6 is a general discussion of the main scientific and methodological contributions of the PhD, and the limits and perspectives of the work done.

  , to study the impact on environmental indicators aggregated for farm types and EU regions. Hence, it remains unsure how effective it can be to significantly increase the voluntary adoption of environment-friendly practices at the farm level, and what are the underlying microeconomic mechanisms. We develop our model with observed data, and assume a transfer towards existing contracts during the 2014-2020 CAP programming period: OFS and AECM. Using panel data from the farm accountancy data network (FADN), we propose a generalised Tobit model estimating the adoption decision and the farm-level payment (acceptable payment) triggering adoption. Adoption results from the confrontation of the supply of environmental commitments by farmers (farm and farmer characteristics, opportunity costs), and demand from public authorities (budget, eligibility criteria, contract requirements, payment). Our model partly overcomes the absence of information on specific contract characteristics and eligibility criteria by controlling for many factors of farm heterogeneity. The estimations are used to simulate contract uptake in 2019 under a new budget allocation.

  and policy parameters Γ defining environmental contracts exclusion rules. The confrontation of demand and supply of environmental commitments results in an uptake equilibrium such that 𝐵 = ∑ 𝑃 𝑖 (𝑀, Γ 𝑖 , 𝛾 𝑖 , 𝑘 𝑖 , 𝑒 𝑖 ) 𝑖 . With 𝑃 𝑖 the farm-level payment allocated to farms, Γ 𝑖 the farm characteristics affecting exclusion to environmental contracts (location in eligible area), 𝛾 𝑖 the farm characteristics affecting eligibility to a subset of environmental measures of 𝑀 (location, land use, organic certification status), 𝑘 𝑖 other farm and farmer characteristics (economic size, surface, age, education, technical orientation…), and 𝑒 𝑖 the farm economic context (market prices, CAP support…).

  This chapter was co-authored with Carole Ropars-Collet (Institut Agro, SMART), Alice Issanchou (INRAE, SMART) and Pierre Dupraz (INRAE, SMART), and involved the following individual contributions: Fanny Le Gloux: conceptualisation, investigation, methodology, data curation, formal analysis, original draft; Carole Ropars-Collet: conceptualisation, methodology, validation, writing review and editing; Alice Issanchou: conceptualisation, validation, writing review and editing; Pierre Dupraz: conceptualisation, supervision, validation. Preliminary versions were presented at the 96 th Annual Conference of The Agricultural Economics Society (4 th -6 th April 2022 in Leuven, Belgium), the 4 th Annual Meeting of the Research Network on Economic Experiments for the Common Agricultural Policy (8 th -9 th June 2022 in Uppsala, Sweden), and the 9 th PhD Workshop of the European Association of Agricultural Economists (22 nd -24 th June 2022 in Parma, Italy). The analyses also contributed to deliverable D3.2 (D'Alberto et al., 2022) of the CONSOLE project (https://console-project.eu/), and to an article for stakeholders of the French agricultural sector 3.1. Introduction Payments for environmental services (PES) are initiatives supporting farmers' voluntary interventions contributing to the preservation of ecological functions

  𝑃 𝑛𝑗𝑡 = 𝑃𝑟𝑜𝑏( 𝜀 𝑛𝑗𝑡 -𝜀 𝑛𝑖𝑡 > 𝛽 𝑛 (𝑋 𝑛𝑖𝑡 -𝑋 𝑛𝑗𝑡 )) ∀𝑖 ≠ 𝑗(3.4)𝑃 𝑛𝑗𝑡|𝑞 = 𝑃𝑟𝑜𝑏( 𝜀 𝑛𝑗𝑡 -𝜀 𝑛𝑖𝑡 > 𝛽 𝑞 (𝑋 𝑛𝑖𝑡 -𝑋 𝑛𝑗𝑡 )|𝑐𝑙𝑎𝑠𝑠 𝑞) ∀𝑖 ≠ 𝑗 (3.5) Both the ML model and the LC model keep the assumption that error terms are independent and identically Gumbel Type-1 distributed, but allow preference parameters to vary. The ML model specifies a continuous distribution of the coefficients such that preferences vary randomly across individuals. The LC model specifies a discrete distribution to the coefficients and relies on the definition of classes of individuals. While preferences are heterogeneous across the different classes, individuals of the same class are assumed homogeneous.A monetary attribute is included (ex: individual payment of a PES contract) to evaluate the WTA of respondents for each specific attribute level. An estimate of the average WTA for each attribute 𝑋 𝑛𝑗𝑡 is obtained from the ratio of the coefficient of the corresponding attribute 𝛽 𝑋 and the payment coefficient 𝛽 𝑝𝑎𝑦𝑚𝑒𝑛𝑡 (3.6)[START_REF] Mariel | Environmental Valuation with Discrete Choice Experiments: Guidance on Design, Implementation and Data Analysis[END_REF]. 𝑊𝑇𝐴 𝑋 is the average annual payment per hectare a farmer requires to accept a contract for which the level of attribute 𝑋 is higher by one unit.

Figure 3 .

 3 Figure 3.1 for an example of a choice card). A d-efficient design of 36 choice sets to be divided into 4 blocks of 9 choice cards was constructed (Appendix A4).

Figure 3 . 1 .

 31 Figure 3.1. Example of choice set of the choice experiment.

  97 farms are located in Brittany, 23 in Pays de la Loire, and 10 in Normandy (Figure 3.2). Departments of Brittany: Finistère, Côtes-d'Armor, Ille-et-Vilaine, Morbihan. Departments of Normandy: Manche, Calvados, Orne, Eure. Departments of Pays de la Loire: Mayenne, Sarthe, Loire-Atlantique, Maine-et-Loire, Vendée. Source: own elaboration.

Figure 3 . 2 .

 32 Figure 3.2. Distribution of the sampled farms in the surveyed regions (ratio).

Figure 3 . 3 .

 33 Figure 3.3. Stated effect of contract design characteristics on willingness to adopt.

  This chapter focuses on the design of result-based dedicated payments for environmental services (PES). The conditionality rules of result-based PES define a payment based on the achievement of an environmental outcome, rather than the implementation of prescribed practices. In theory, they exhibit the payment mechanisms the most targeted towards public good provisioning. The design of result-based PES aims at cost-effectiveness, as the payment conditionality ensures that there is no payment without environmental output. It also favours the efficiency of farmers, who are free to choose the less costly practices adapted to their situation to meet the contractual requirements. Only three agri-environment-climate measures (AECM) with result-based features were proposed in France during the 2014-2020 common agricultural policy (CAP) programming period, with payments conditioned to the presence of a minimum number of specific flower species on grasslands. Private initiatives also emerged for the reduction of GHG emissions or carbon storage in agricultural soils, measured in tonnes of carbon dioxide equivalent. For instance, the result-based scheme Eco-Methane proposes a payment proportional to the reduction of enteric methane emissions on French dairy farms. Implemented since 2011, participation after 10 years remains marginal (around 2.3% of French dairy farms) (Bleu-Blanc-Coeur, 2022b). It suggests that despite their intrinsic advantages, barriers remain to the implementation of successful result-based PES.

  (i) the choice of emissions indicator capturing the effect of farmers' practices and (ii) the payment amount relative to the extra milk production costs incurred. Using representative farmlevel economic data from the farm accountancy data network (FADN), we compare enteric methane emissions per liter of milk calculated with an Intergovernmental Panel on Climate Change Tier 2 method, to baseline emissions from a Tier 3 method accounting for diet effects.

  coinvented by teams from the animal feed manufacturing company Valorex (P. Weill and G. Chesneau) and the French National Institute for Agricultural Research (INRA) (Y. Chilliard, M. Doreau and C.

1 .

 1 Allocation of Eco-Methane scenarios and distinction of three milk production basins Following the allocation of the Eco-Methane baseline scenarios to the farms of the sample, their proportion within each region can be observed (Figure 4.1). Farms in the regions of the western plains basin (Brittany, Pays de la Loire and Basse-Normandie) represent 44% of the sample and

Figure 4 . 1 .

 41 Figure 4.1. Distribution of Eco-Methane baseline scenarios among French regions.

Figure 4 . 2 .

 42 Figure 4.2. Average enteric emissions in French regions according to the TIER2 and Eco-Methane baseline indicators.

( 4 .

 4 8), in which parameter 𝜌 11 corresponds to the effect of grassland surfaces on the marginal cost of milk.

  consider 𝑖 = 1, … , 𝐼 consumers. Each individual's preferences are represented by a strictly increasing and strictly quasi-concave utility function 𝑈 𝑖 (𝑋 𝑖 , 𝑌, 𝐻 𝑖 ) , where 𝑋 𝑖 and 𝐻 𝑖 are individual i's private consumption of characteristics 𝑋 (food product) and 𝐻 (health benefits), and 𝑌 (environmental benefits) is the provisioning of the public characteristic such that 𝑌 = ∑ 𝑌 𝑖 𝐼 𝑖 , where 𝑌 𝑖 is individual i's private contribution. For each individual, the contribution of others to the public characteristic is exogenous, such that 𝑌 = 𝑌 𝑖 + ∑ 𝑌 𝑗 𝐼 𝑗≠𝑖 = 𝑌 𝑖 + 𝑌 -𝑖 .

  social welfare corresponding to the sum of the individual utility and solve the following problem: max 𝑐,𝑔 {∑ 𝑈 𝑖 |𝑐 = ∑ 𝑐 𝑖 𝑖 , 𝑔 = ∑ 𝑔 𝑖 𝑖 , 𝑇(𝑐, 𝑔) = 0 𝑖 }.(5.1)At the optimum, the sum of the quantities of goods c and g consumed by all individuals is equal to the quantity of goods produced by the producer according to the production technology 𝑇(𝑐, 𝑔). The derivation of this program leads to the following first-order conditions: 𝜆 is the Lagrangian multiplier associated with production technology. Combining these two conditions leads to the Pareto optimum condition: 𝑝 , 𝐻 𝑖 𝑝 and 𝑌 𝑝 correspond to the Pareto optimal demand for private and public characteristics of goods 𝑔 and 𝑐. The Pareto optimum requires that the sum of the marginal rates of substitution between characteristics, weighted by technology parameters 𝛼 and 𝛽, be equal to the marginal rate of transformation. The term on the right-hand side of equation(5.4) represents the marginal rate of the transformation of goods, i.e., the quantity by which the production of the good c must be reduced to produce an additional unit of the other good g

  𝑒𝑎 and 𝑌 𝑒𝑎 correspond to the optimal demand from the environmental agency perspective for private and public characteristics of goods 𝑔 and 𝑐. The sum of the marginal rates of substitution between public and private characteristics must be equal to the marginal rate of transformation between public and private goods. Note that this condition is also the Pareto optimum condition associated with the model of green consumption defined by[START_REF] Kötchen | Impure public goods and the comparative statics of environmentally friendly consumption[END_REF], which does not consider the private characteristic 𝐻 𝑖 . The corresponding private consumption 𝐻 𝑖 𝑒𝑎 is obtained from ∑ 𝐻 𝑖 𝑒𝑎 𝑖 = 𝛼𝑔 𝑒𝑎 * when 𝑔 𝑒𝑎 * solves the optimization program of the environmental agency.

  Environmental services (ES) refer to farmer interventions contributing to maintaining or enhancing ecosystem services. They contribute to the provision of public goods such as climate change mitigation, and water quality and biodiversity preservation, and are jointly provided with agricultural commodities. In a context of increasing scarcity and overall degradation of public good provisioning from agriculture, there is a consensus that ES are subject to market failure. In the absence of regulations, they are positive externalities currently provided at a very low level relative to the environmental challenges. Payments for environmental services (PES) are instruments aiming at correcting this underprovision. PES incentivise farmers to voluntarily maintaining or implementing agricultural practices contributing to well-functioning ecosystem services. My PhD aimed at applying empirical and theoretical microeconomic approaches to analyse the efficiency of their payment mechanisms, and in particular the two polar cases: (i) public support dedicated to agri-environment-climate measures (AECM), (ii) price premium on a joint agricultural commodity. My PhD thesis is organised in six chapters. In the first chapter, I introduce the main concepts and definitions I use, and provide a short literature review of the different types of mechanisms of PES implemented in the European Union (EU). The next four chapters are research articles, for which I summarise the main contributions, limits and perspectives in the next sections. I adopt the PES definition of Wunder (2015). They are voluntary transactions between ES providers and ES users conditioned to the implementation of an agreed set of rules for generating offsite services. In my PhD, I only consider PES with financial transactions (payments), and farmers as ES providers. Rather than ES users, I use the term ES contributors.

  fourth chapter aims at studying the design of cost-effective result-based PES for the provision of a linear global public good depending on aggregate efforts, such as climate change mitigation. Result-based PES pay individual farmers proportionally to the emissions mitigated, letting them choose the most efficient mitigation practices for their farming system. Technical difficulties arise on how to precisely capture and measure farmers' individual efforts to the provision of the public good, and to define the level of incentive for encouraging high aggregated mitigation efforts from the farming population. Inspired by a French case study, we study two design elements of PES targeting the reduction of enteric methane emissions on dairy farms which are crucial for their effectiveness: the choice of emissions indicator and the payment level. Using publicly available farm-level panel data from the French FADN, we compare enteric emissions computed with an IPCC Tier 2 method to baseline emissions from a Tier 3 method accounting for diet effects. We use the dual theory of production economics and estimate variable cost functions for different French dairy systems to quantify the extracosts of milk production for reducing enteric emissions with more grasslands in fodder systems.

(chapter 2 )

 2 , acceptability of contract attributes (chapter 3), and extra-costs for changing practices (chapter 4). The empirical analyses from chapter 2 to 4 focus on the behaviour of farmers facing economic incentives to supply ES. The empirical observations illustrate that current schemes are not paid enough to finance ES provision, and highlight the limitation of PES effectiveness from the lack of sufficient contributions to trigger large-scale adoption. It becomes necessary to also look at the demand side.

3 /

 3 Nous allons vous proposer plusieurs ensembles de choix de contrats de PSE. Ces sont totalement fictifs. Ils ont été créés spécifiquement pour le questionnaire. Il s'agit d'une expérience qui ne vous engage en aucun cas à adhérer à de tels contrats. Nous vous demandons toutefois de répondre comme s'il s'agissait d'une proposition réelle. Pour chaque ensemble de choix, nous allons vous proposer 2 contrats de PSE. Vous aurez le choix entre : 1/ Accepter le contrat de PSE A 2/ Accepter le contrat de PSE B Aucun des deux contrats/Conserver vos pratiques actuelles. L'adoption d'un contrat de PSE est totalement volontaire : vous avez le choix de refuser le PSE A et le PSE B si vous considérez que la rémunération est insuffisante ou que les obligations de gestion sont inatteignables. Les haies : ATTENTION ! Les haies basses, les taillis monospécifiques ou autres alignements d'arbres ne compteront pas dans le linéaire. En effet, les haies doivent être multistrates (arbres, arbustres, etc…) et multiessences (plusieurs espèces). Elles doivent être d'une largeur minimale de 2,50 m. L'installation des haies est à 100% subventionnée et réalisée par d'autres organismes (Breizh Bocage par exemple). Seul l'entretien serait à votre charge, avec 1 entretien minimum tous les 5 ans. 3 niveaux vous seront proposés dans les contrats fictifs de PSE, à savoir : -20 m de linéaire de haies par hectare de SAU Exemple de choix : de trois choix : choisir le contrat A, le contrat B ou conserver vos pratiques (« ne choisir aucun des deux contrats proposés » ?) Exemple contrat A :

3 /

 3 Vous recevrez 15 000€/an de paiement individuel. Ce contrat ne propose ni bonus collectif en fonction du résultat, ni incitation au parrainage.

Table 2 . 1 .

 21 Common Agricultural Policy budget and beneficiaries in 2015-2019. .................. 37

Table 2 . 2 .

 22 Descriptive statistics of the sample (N=28,967). .................................................... 40

Table 2 . 3 .

 23 Comparison between observed and estimated adoption behaviour (N=28,967). ... 42

Table 2 . 4 .

 24 Generalised Tobit models estimation: marginal effects at the sample mean. ........ 43

Table 2 . 5 .

 25 Simulated impact of a decrease of 7.5% of direct payments in 2019 (N=7,194). .. 49

Table 2 . 6 .

 26 Change of allocation of environmental incentives among farm types with an additional transfer of 7.5% of direct payments budget to reach 15% in 2019 (%)(N=7,194). 51

Table 2 . 7 .

 27 Impact of a budget transfer in 2019 under several transfer scenarios (N=7,194). . 52

Table 3 . 1 .

 31 Attributes and attribute levels in the choice experiment. ....................................... 62

Table 3 .

 3

  The European Commission (EC) defines ambitious strategies and targets for 2030 and 2050 regarding water, air and soil quality, biodiversity and climate. Some derive from binding international agreements such as the Convention on Biological Diversity and the Paris Agreement(United Nations, 2015[START_REF] Hornick | Factors Affecting the Nutritional Quality of Crops[END_REF], or are cross-cutting with global Sustainable

	Development Goals (EC, 2022b). The Climate Law commits the EU to reach net zero GHG
	emissions by 2050 (EU, 2021). The EC recently published a proposal for a Nature Restoration
	Law with biding obligations (EC, 2022c). The Farm to Fork Strategy and the Biodiversity
	Strategy for 2030 include quantified targets: a reduction by 50% of chemical pesticides use and
	risk, antimicrobials sales and nutrient losses, together with a reduction by 20% of fertilizer use.

Table

Table 1 . 1 .

 11 Instruments accompanying the agricultural sector for the delivery of water quality, biodiversity and climate targets in the EU.

	Political objective	Current instruments

  . When a farmer converts arable land to permanent grasslands or any other practice increasing the organic matter content of his or her soil, it directly contributes to climate change mitigation (arrow A9

in figure

1.1)

. In these cases, there is the near-linear relationship between ES and public good provision with regards to the surface dedicated to ES and effort (𝑓 is simply positive and increasing in 𝑠 𝑗 and e). Water quality and biodiversity are however characterised by ecological threshold effects and a nonlinear relationship with ES provision. A farmer can implement practices to reduce pesticide leaching or nutrients runoff of land, but water quality gains are only observed if ES are continuously implemented on a large share of the upstream watershed over a sufficient period (arrows A10-A11 in figure

1

.1)

[START_REF] Landell-Mills | Silver bullet or fool's gold? A global review of markets for forest environmental services and their impact on the poor[END_REF]

.

Table 1 .2. Payments

 1 for environmental services mechanisms to allocate the willingness to pay of contributors in France.

	Contributor	Financing mechanism	Payment mechanism	Example
	EU taxpayers	Budget allocation to common	Dedicated payment (profit	270 million € per year for Agri-
		agricultural policy instruments	foregone and extra-costs), no	Environment-Climate Measures
		by public authorities	double funding
	Pollution taxpayers (ex:	Project calls and co-funding of	Dedicated payment (profit	19.3 million € in 2020 from water
	companies selling pesticides)	common agricultural policy	foregone and extra-costs), "de	agencies for local PES around water
		instruments by local public	minimis" cap, no double	catchment areas, Agri-Environment-
	Payers of fees for extracting and	authorities and government	funding	Climate Measures targeting water
	using natural resources (ex: water	agencies		quality, and support to organic farming
	and sanitation)
	Private companies	Donation to an intermediary	Dedicated payment, based on	7,500 € per year (with a 60% tax
		coordinating a PES	company willingness to pay	deduction) on average by company to
				the Eco-Methane fund for reducing
				enteric methane emissions on dairy
				farms (around 7.5€/tCO2eq)
	Private companies	Investment	Dedicated payment, based on	1.6 million € per year during 7 years
			(bilateral) negotiation	from Nestlé Waters for the conversion
				of 37 farmers to environment-friendly
				practices
	Customers of agricultural
	commodities

  𝑖 , 𝛾 𝑖 , 𝑘 𝑖 , 𝑒 𝑖 ) = Φ 𝑖 (𝑚 𝑖 receive for enrolling all eligible surfaces under 𝑚 𝑖 * . 𝑃 𝑖 * (𝑚 𝑖 * , 𝛾 𝑖 , 𝑘 𝑖 , 𝑒 𝑖 ) is the minimum payment farm 𝑖 should receive for accepting to enrol the profit maximising share of eligible surfaces under 𝑚 𝑖 * . If ∀𝑚 𝑖 ∈ 𝑀, Φ 𝑖 (𝑚 𝑖 , Γ 𝑖 , 𝛾 𝑖 , 𝑘 𝑖 , 𝑒 𝑖 ) = 0 𝑜𝑟 0 < Φ 𝑖 (𝑚 𝑖 , Γ 𝑖 , 𝛾 𝑖 , 𝑘 𝑖 , 𝑒 𝑖 ) < 𝑃 𝑖 * (𝑚 𝑖 , 𝛾 𝑖 , 𝑘 𝑖 , 𝑒 𝑖 ) (the farmer is not eligible or participation is not profitable), then 𝐷 𝑖 * < 0 and the farm is not participating. If ∃𝑚 𝑖 ∈ 𝑀, Φ 𝑖 (𝑚 𝑖 , Γ 𝑖 , 𝛾 𝑖 , 𝑘 𝑖 , 𝑒 𝑖 ) ≥ 𝑃 𝑖 (𝑚 𝑖 , 𝛾 𝑖 , 𝑘 𝑖 , 𝑒 𝑖 ), the farmer is eligible to at least one contract profitable for him or her, and the farm decides to participate

	0 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 allocated to farms 𝑃 𝑖 is: ; 𝐷 𝑖 * (𝑀, Γ with the optimal contract uptake 𝑚 𝑖 * such that 𝐷 𝑖 * ≥ 0. In this setting, the farm-level payment 𝑃 𝑖 (𝑀, Γ 𝑖 , 𝛾 𝑖 , 𝑘 𝑖 , 𝑒 𝑖 ) = { 𝑃 𝑖 * (𝑚 𝑖 * (𝑀, Γ 𝑖 , 𝛾 𝑖 , 𝑘 𝑖 , 𝑒 𝑖 ) , 𝑘 𝑖 , 𝑒 𝑖 ) 𝑖𝑓 𝐷 𝑖 * (𝑀, Γ 𝑖 , 𝛾 𝑖 , 𝑘 𝑖 , 𝑒 𝑖 ) ≥ 0 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 (2.2)

  than the selection equation. The payment 𝑃 𝑖𝑡 received by participant 𝑖 at year 𝑡 is observed (censored variable at zero) (Equation(2.4)).

	𝑃 𝑖𝑡 * = 𝛽𝑍 𝑖𝑡 + 𝛿Γ 𝑖𝑡 + 𝑢 𝑖𝑡 , 𝑢 𝑖𝑡 ~𝑁(0, 𝜎 2 ), 𝑃 𝑖𝑡 = {	𝑃 𝑖𝑡 * 𝑖𝑓 𝐷 𝑖𝑡 * ≥ 0 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒	(2.4)
	Without information to characterise the exclusion criteria Γ 𝑖𝑡 , the actual models estimated are
	the following ones:
	𝐷 𝑖𝑡 * = 𝛼𝑍 𝑖𝑡 + 𝑒 𝑖𝑡 , 𝑒 𝑖𝑡 ~𝑁(0,1), 𝐷 𝑖𝑡 = {	1 𝑖𝑓 𝐷 𝑖𝑡 * ≥ 0 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒	(2.5)
	𝑃 𝑖𝑡 * = 𝛽𝑍 𝑖𝑡 + 𝑣 𝑖𝑡 , 𝑣 𝑖𝑡 ~𝑁(0, 𝜎 2 ), 𝑃 𝑖𝑡 = {	𝑃 𝑖𝑡 * 𝑖𝑓 𝐷 𝑖𝑡 * ≥ 0 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒	(2.6)
	And we have an omitted-variable bias on 𝛼 equals to 𝛾	𝐶𝑜𝑣(𝑍 𝑖𝑡 ,Γ 𝑖𝑡 ) 𝑉𝑎𝑟(𝑍 𝑖𝑡 )	in Equation (2.5) and on 𝛽
	equals to 𝛿	𝐶𝑜𝑣(𝑍 𝑖𝑡 ,Γ 𝑖𝑡 ) 𝑉𝑎𝑟(𝑍 𝑖𝑡 )
	𝐷 𝑖𝑡 * = 𝛼𝑍 𝑖𝑡 + 𝛾Γ 𝑖𝑡 + 𝜀 𝑖𝑡 , 𝜀 𝑖𝑡 ~𝑁(0,1), 𝐷 𝑖𝑡 = {	1 𝑖𝑓 𝐷 𝑖𝑡 * ≥ 0 0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒	(2.3)

to simultaneously estimate two dependent variables: the decision to participate (selection equation) and the acceptable payment (outcome equation), as functions of observed determinants from a sample of participants and non-participants. Because the adoption behaviour of farmers, in particular the acceptable payment, likely differs between OFS and AECM, we estimate one model for each type of contract. With panel data, the decision to participate of farmer 𝑖 in year 𝑡, is represented by the latent variable 𝐷 𝑖𝑡 * explained by observed covariates 𝑍 𝑖𝑡 = (𝛾 𝑖 , 𝑘 𝑖𝑡 , 𝑒 𝑖𝑡 ) , environmental contract exclusion criteria Γ 𝑖𝑡 and an error term 𝜀 𝑖𝑡 . The observed farm level participation can be described by a binary random variable 𝐷 𝑖𝑡 = {0,1} (Equation (2.3)). Our outcome of interest is the acceptable payment 𝑃 𝑖𝑡 * triggering participation, which is explained by observed covariates 𝑍 𝑖𝑡 = (𝛾 𝑖 , 𝑘 𝑖𝑡 , 𝑒 𝑖𝑡 ), environmental contract exclusion criteria Γ 𝑖𝑡 and an error term 𝑢 𝑖𝑡 . For identification, the outcome equation must include one less explanatory variable

Table 2 . 1 .

 21 .1). The highest budget was for 2019, with 228 million € to 11% of sample farms for AECM and 203 million € to 7% of sample farms for OFS. Common Agricultural Policy budget and beneficiaries in 2015-2019.

	Information on farms' organic certification allows us to deduct that 66 million € are distributed

to 1.5% of sample farms for conversion OFS and 138 million € to 5% of sample farms for maintenance OFS. For that same year (2019), the French Government reported allocating a total of 244 million € for AECM and 249 million € for OFS, including 191 million € for conversion OFS and 58 million € for maintenance OFS (DDT Ariège, 2020). Assuming the total number of farms in France Métropole was the same in 2019 as in 2020 (389,800), we deduct that 11% of French farms contracted an AECM, 5% conversion OFS and 3% maintenance OFS

(INSEE, 2022)

. Hence, our FADN sample describes the allocation of 93% of the AECM budget and 82% of the OFS budget to a representative ratio of participants/non-participants in 2019. However, it does not represent well the repartition between conversion OFS and maintenance OFS, and overestimates the allocation of OFS to certified farms relative to farms in conversion. Yet, we observed the ratio within the OFS-eligible population (i.e. farms converting to organic farming or already certified in 2019) is well represented in the FADN, at least when it comes to the utilised agricultural area (UAA) (see Appendix A1) (Agence bio, 2020).

Based on the literature on the factors affecting AECM and organic farming adoption and our theoretical approach

[START_REF] Allaire | Spatial diffusion and adoption determinants of European agri-environmental supports related to extensive grazing in France[END_REF][START_REF] Defrancesco | Factors affecting farmers'participation 197 in agri-environmental measures: A northern Italian perspective[END_REF][START_REF] Elliott | Design of Agri-Environmental Schemesevidence from the monitoring and evaluation GLAS in Ireland[END_REF][START_REF] Espinosa-Goded | Identifying additional barriers in the adoption of agri-environmental schemes: The role of fixed costs[END_REF][START_REF] Pavlis | Patterns of agri-environmental scheme participation in Europe: Indicative trends from selected case studies[END_REF]

, we selected a set of variables to model contract uptake.

Table 2 . 2 .

 22 Descriptive statistics of the sample (N=28,967).

	Weighted mean	Standard deviation

  In practice, criteria Γ 𝑖 prevent some farms from participating in certain measures based on their location. In particular, only farms located in an agri-environment-climate project are eligible to AECM, while maintenance OFS are not available in some regions. Because we do not have enough information in the FADN to identify and exclude non-eligible farms, we assume all the sample becomes eligible. Another (strong) necessary assumption to be allowed to use the estimated model for simulating a change of budget allocation is that the menu of contracts 𝑀 (technical requirements, area payment) is not affected by a budget transfer. As a result, the estimated effects of farm and farmer characteristics (𝛾 𝑖𝑡 , 𝑘 𝑖𝑡 ) and economic context (𝑒 𝑖𝑡 ) on the adoption decision and acceptable payments can be considered the same with a different budget allocation.

	be allocated to sample farms is now 𝐵 19 𝐴𝐸𝐶𝑀 + 𝐵 ̃19 𝐴𝐸𝐶𝑀 =514 million € and 𝐵 19 𝑂𝐹𝑆 + 𝐵 ̃19 𝑂𝐹𝑆 =458
	million €.
	𝐷𝑃 19 1-0.075	*
	0.075 to be allocated is 541 million €. We keep the current budget ratio among the instruments:
	53% to AECM (𝐵 ̃19 𝐴𝐸𝐶𝑀 =286 million €) and 47% to OFS (𝐵 ̃19 𝑂𝐹𝑆 =255 million €). The budget to

In the first stage, model estimates are used to predict farm probabilities and acceptable payments for enrolling in AECM (OFS respectively) in 2019 with a decrease of 7.5% of decoupled payments and coupled payments for suckler cows received. In the second stage, farms are ranked according to decreasing predicted probabilities of adopting AECM (OFS respectively). In a third stage, 𝐵 19 𝐴𝐸𝐶𝑀 + 𝐵 ̃19 𝐴𝐸𝐶𝑀 (𝐵 19 𝑂𝐹𝑆 + 𝐵 ̃19 𝑂𝐹𝑆 respectively) is allocated to farms up to their predicted acceptable payment, starting with the farm with the highest probability to the lowest, until the budget is exhausted.

Table 2 . 3 .

 23 Comparison between observed and estimated adoption behaviour (N=28,967).The marginal effects of the covariates on the latent decision to participate and acceptable payment are presented in Table2.4, and the coefficients in Appendix A3.

	All sample	Participants
	Observed Estimated Observed Estimated

Table 2 . 4 .

 24 Generalised Tobit models estimation: marginal effects at the sample mean. -value <0.001, ** p-value <0.01, * p-value<0.05, + p-value<0.1. Standard errors in parentheses. AWU : annual work unit. LU: livestock unit. AECM: Agri-Environment-Climate Measure. OFS: Organic farming support. Source: own elaboration, using 2015-2020 French FADN.

		AECM		OFS
	Participation decision (𝐷 𝑖 * )	Acceptable payment (𝑃 𝑎𝑖 ) in 1,000€	Participation decision (𝐷 𝑖 * )	Acceptable payment (𝑃 𝑎𝑖 ) in 1,000€

Table 2 . 5 .

 25 Simulated impact of a decrease of 7.5% of direct payments in2019 (N=7,194). Standard deviation in parentheses. AECM: Agri-Environment-Climate Measure. OFS: Organic farming support. UAA: utilised agricultural area. Source: own elaboration, using 2019 French FADN.

			Baseline		With a budget transfer
		AECM	OFS	Total	AECM	OFS	Total
	Budget (1,000€)	227,862	203,267	431,130	513,981	458,848	972,429
	Share of farms (%)	10.8	6.9	16.8	23.7	16.7	34.6
	Total UAA of participants (ha)	3,808,678 1,657,456 5,148,400 8,093,439 4,342,287 10,743,844
	Share of total UAA (%)	14.5	6.3	19.6	30.8	16.6	41.0
	Payment of	7,279	10,238	8,843	7,497	9,499	9,699
	participants (€)	(6,768)	(12,032)	(9,758)	(3,610)	(7,972)	(7,484)
	Acceptable	5,843	8,902		5,798	8,872
	payment (€)	(3,509)	(7,573)		(3,482)	(7,566)

Table 2 . 6 .

 26 Change of allocation of environmental incentives among farm types with an additional transfer of 7.5% of direct payments budget to reach 15% in 2019 (%)(N=7,194). Environment-Climate Measure. OFS: Organic farming support. Source: own elaboration, using 2019 French FADN.

	Technical	AECM -	AECM -	OFS -baseline OFS -budget
	orientation	baseline	budget transfer		transfer
	15	16.69	8.07	16.46	17.06
	16	3.96	1.75	6.35	4.33
	28	0.74	0.20	4.93	4.53
	29	0.00	0.00	1.76	1.94
	37	3.75	3.60	14.79	11.14
	38	0.75	0.28	0.11	0.52
	39	1.16	0.73	6.35	8.95
	45	17.67	21.74	18.08	20.85
	46	24.87	27.38	7.34	7.98
	47	4.79	7.10	1.39	0.82
	48	6.25	8.92	5.57	3.22
	50	2.60	1.73	2.48	5.01
	61	0.78	0.21	2.79	2.90
	73	0.18	0.55	1.92	1.63
	74	1.09	0.66	1.31	1.21
	83	10.37	13.23	3.66	4.66
	84	4.31	3.86	4.71	3.25
	AECM: Agri-

Table 2 . 7 .

 27 Impact of a budget transfer in 2019 under several transfer scenarios(N=7,194). Environment-Climate Measure. OFS: Organic farming support. UAA: utilised agricultural area. Budget allocation assumption: 53% AECM/47% OFS. Source: own elaboration, using 2019 French FADN.

	Direct payments transfer (%)	15		15.5	21
	Environmental scheme	AECM	OFS	Conversion OFS	OFS
	Budget (million€)	514.0	458.8	475.5	663.7
	Share of farms (%)	23.7	16.7	14.5	23.3
	Share of total UAA (%)	30.8	16.6	18.5	24.5
	Acceptable payment (€)	5,798	8,872	8,751	8,848
	Total organic UAA (%)	17.8		25.9	25.4
	AECM: Agri-

Table 3 . 1 .

 31 Attributes and attribute levels in the choice experiment.

	Attribute	Description			Levels
	Soil cover Average agricultural soil coverage	85%
		throughout the year at the farm level	90%
		(no bare soil, starting from seeding)	95%
	Hedgerows Average density of anti-erosion	20m/ha
		multi-species multilayer hedgerows	60m/ha
		at the farm level		100m/ha
	Payment	Per-hectare	individual	annual	150€/ha
		payment			300€/ha
					450€/ha
					600€/ha
	Bonus	Bonuses conditioned to a collective	None
		action :			Sponsorship bonus
		A fixed individual sponsorship	Sponsorship bonus + collective result
		bonus of 450€ the farmer receives	bonus
		each time he convinces a peer into
		entering the scheme ;
		A collective result bonus of 50€/ha
		distributed to all participants if the
		river's status reaches a higher step of
		the water quality scale
	Source: own elaboration.

Table 3 . 2 .

 32 Descriptive statistics of the sample (N=130).

	Variable

Table 3 . 3 .

 33 Conditional Logit estimations.

	Specification	CL1	CL2	CL3
	PAYMENT	0.004 *** (0.000)	0.004 *** (0.000) 0.004 *** (0.000)
	COVER	0.007 (0.016)	0.021 + (0.013)
	COVER -90%			0.077 (0.066)
	COVER -95%			0.070 (0.073)
	HEDGEROWS	-0.006 ** (0.002)	-0.004 * (0.003)
	HEDGEROWS -60m/ha			0.134 * (0.068)
	HEDGEROWS -100m/ha			-0.246 * (0.108)
	BONUS sponsorship	0.419 *** (0.127)	0.409 *** (0.118) 0.426 *** (0.124)
	BONUS sponsorship/collective result	0.265 * (0.138)	0.256 * (0.129)	0.277 * (0.131)
	ASCsq	0.653 ** (0.245)	2.145 * (1.190)	0.526 ** (0.191)
	Log Likelihood	-916.15	-986.41	-983.75
	Adjusted-R 2	0.19	0.19	0.19
	AIC	1844.30	1984.81	1983.49
	BIC	1873.98	2014.94	2023.66
	Observations	1039	1120	1120
	Number of farms	116	125	125
	Significance levels: *** robust p-value <0.001, ** robust p-value <0.01, * robust p-value<0.05, +
	robust p-value<0.1. Robust standard errors in parentheses.
	Source: own elaboration.

Table 3 . 4 .

 34 Mixed Logit estimations (normal distribution of random parameters).

	ML1	ML2

Table 3 . 5 .

 35 Marginal willingness to accept the payment for environmental services contract design characteristics, estimated with the delta method (€/ha/year).

	ML1

Table 3 . 6 .

 36 Selection of Latent Class model.

	Number of classes	2	3	4	5	6
	Log Likelihood	-796.07 -715.8	-692.42 -673.93 -662.43
	AIC	1618.13 1471.6 1438.84 1415.85 1406.87
	BIC	1682.43 1570.52 1572.38 1584.01 1609.65
	Pseudo-R 2	0.2912 0.3554 0.3697 0.3798 0.3837
	Average probability to belong to the	0.9777 0.968	0.9501 0.9445 0.9254
	attributed class
	Source: own elaboration.

Table 3 .

 3 7. Latent Class estimation.

		Class 1	Class 2	Class 3
	PAYMENT	0.008 ** (0.003)	0.002 + (0.002)	0.001 (0.001)
	COVER	0.041 * (0.021)	-0.055 ** (0.020)	0.107 *** (0.031)
	HEDGEROWS	0.005 (0.004)	-0.041 * (0.022)	0.020 ** (0.007)
	BONUS sponsorship	0.989 *** (0.206)	0.103 (0.428)	-0.708 * (0.395)
	BONUS sponsorship/collective result	1.216 * (0.523)	-0.392 (0.340)	-1.027 ** (0.400)
	ASCsq	-2.601 * (1.519)	0.335 (0.491)	-1.952 *** (0.464)
	Log likelihood		-700.61
	Pseudo-R 2		0.3617
	AIC		1457.21
	BIC		1595.7
	Observations		1039
	Number of farms		116
	Probability of class	0.6078	0.1607	0.2314
	Share of respondents (%)	56.90	29.31	13.79
	Class membership function
	Intercept		-0.129 (0.655)	-1.726 ** (0.609)
	SHORT-TERM	-	1.013 + (0.774)	-0.443 (0.854)
	ORGANIC	-	-0.985 + (0.643)	1.476 * (0.726)
	ENVORGA	-	-15.615 *** (1.392)	-1.352 + (0.828)
	HHDIVREVENU	-	-0.710 (0.809)	-12.054 *** (1.578)
	Significance levels: *** robust p-value <0.001, ** robust p-value <0.01, * robust p-value <0.05,
	+ robust p-value<0.1. Robust standard errors in parentheses.
	Source: own elaboration.

Table 4 . 1 .

 41 Description of the sample (N=2,205) Information on surfaces and the number of dairy cows available in the database are ranges of values. We constructed the variables used in the analysis by taking the lower value of the range for each observation. Source: French 2016-2018 FADN data.

	Variable	1 st quartile	Median	Mean	rd 3 quartile
	Utilized Agricultural Area (ha) 1	50.0	80.0	87.4	110.0
	Fodder area (ha) 1	40.0	60.0	67.4	80.0
	Corn silage area (ha) 1	1.0	10.0	14.1	20.0
	Pasture area (ha) 1	26.0	40.0	50.3	61.0
	Productivity (L/cow/year)	5,593.4	6,676.4	6,707.9	7,851.1
	Number of dairy cows 1	35	55	58	70
	Agricultural Work Unit	1.0	2.0	1.8	2.1
	Purchase of cattle feed concentrates (€)	14,326.0	24,996.5	32,853.2	43,645.0
	1

Table 4 . 2 .

 42 Characteristics of the eleven baseline scenarios used in the Eco-Methane scheme

				Eco-Methane
	Scenario	Corn in the fodder area	Production basin	baseline
				(gCH4/L)
	1	More than 30%	Plains outside the western region	15.75
	2		Plains of the western region	15.92
	3	Between 10 and 30%	Plains outside the western region	15.83
	4		Plains of the western region	16.43
	5	Less than 10%	Plains outside the western region	16.56
	6		Plains of the western region	17.38
	7	More than 10%	Mountains	15.96
	8		Mountains of the Massif Central	17.13
	9 10	Less than 10%	Mountains of the Northern Alps Mountains of Franche-Comté	17.83 16.22
	11		Other mountains	17.20
	Source: Bleu-Blanc-Coeur data.

Table 4 .

 4 3.

Table 4 . 3 .

 43 Mean values of the model variables

	Variable	France N=2,205	Western plains N=645	Plains outside the western region N=965	Mountains N=585	Plains, >30% of corn N=767	Plains, ≤ 30% of corn N=853
	Scenarios	1-11	2, 4, 6	1, 3, 5	7-11	1-2	3-6
	Variable Costs	128,073.5	139,405.3	136,399.4	96,533.0	170,654.1	112,079.6
	(€/year)	(105,612.7)	(107,167.1)	(112,800.6)	(80,772.0)	(124,937.8)	(58,355.4)
	Milk production	398,594.1	446,128.0	402,355.2	306,703.0	526,707.0	348,741.1
	(L/year)	(297,513.2)	(328,781.5)	(296,923.0)	(226,416.1)	(333,580.8)	(254,671.3)
	Other productions	498.6	581.3	554.6	274.4	750.2	425.9
	(€/base 100/year)	(671.5)	(642.3)	(770.2)	(413.0)	(871.1)	(512.3)
	Fuel price (€/L)	0.60 (0.10)	0.59 (0.10)	0.59 (0.11)	0.61 (0.10)	0.59 (0.10)	0.60 (0.10)
	Feed price (base	96.6	96.5	96.6	96.8	96.6	96.6
	100)	(2.4)	(2.4)	(2.4)	(2.3)	(2.4)	(2.4)
	Grassland (ha)	51.1 (41.0)	42.1 (31.5)	52.7 (38.6)	65.5 (47.8)	34.2 (25.8)	56.3 (39.2)
	Capital (1000€)	171.0 (155.9)	160.5 (146.8)	179.4 (163.7)	179.5 (160.8)	189.1 (161.8)	151.6 (145.9)
	Labor (AWU)	1.8 (1.0)	1.9 (1.0)	1.9 (1.0)	1.7 (1.0)	2.0 (1.1)	1.7 (1.0)
	Milk price	362.3	343.5	367.0	390.5	333.1	369.4
	(€/1000L)	(74.1)	(41.1)	(61.2)	(101.3)	(27.3)	(66.7)
	UAA (ha)	87.4 (58.1)	84.3 (55.3)	92.6 (60.0)	86.3 (57.8)	93.3 (60.6)	83.2 (55.8)
	Permanent	30.7	14.6	40.0	48.0	13.9	34.2
	pastures (ha)	(41.9)	(31.9)	(36.9)	(49.4)	(23.0)	(41.3)
	Number of dairy	58.0	63.2	57.9	48.4	70.5	53.5
	cows	(36.7)	(42.5)	(34.0)	(30.9)	(40.7)	(32.7)
	Weighted average. Standard deviation in parentheses.
	Source: The authors, based on 2016-2018 French FADN data.

Table 4 . 4 .

 44 Average enteric emissions of the sample according to the TIER2 and Eco-Methane baseline indicators.

		Plains outside the western region		Western plains			Mountains
	Scenario	1, 3, 5	1	3	5	2, 4, 6	2	4	6	7-11	7	8 to 11
	Corn in the fodder area (%)		> 30	30-10	< 10		> 30	30-10	< 10		≥10	< 10
	Sample share (%)	31.4	10.0	9.9	11.5	44.3	23.7	16.8	3.8	24.3	6.5	17.8
	Productivity (L/cow)	6719.8	7654.6	6944.4	5717.8	6976.0	7331.8	6789.3	5586.5	6201.8	6910.1	5943.8
	TIER2 (gCH4/L)	17.92 a	16.83 b	17.59 c	19.15 d	17.60 ce	17.17 f	17.75 ac	19.59 d	18.44 g	17.56 ch	18.77 i
	Eco-Methane baseline (gCH4/L)	16.07	15.75	15.83	16.56	16.24	15.92	16.43	17.38	16.55	15.96	16.76
	Mean values with different superscripts differ (p-value < 0.05).

Source: The authors, based on 2016-2018 French FADN and Bleu-Blanc-Coeur data.

Table 5 . 1 .

 51 Different market settings compared in the paper.

	Market settings	Goods Characteristics known by consumers
	Environmental label	good c private characteristic X
		good g private characteristic X and public characteristic Y
	Health Label	good c private characteristic X
		good g private characteristics X and H
	Health & environment label good c private characteristic X
		good g private characteristics X and H and public characteristic Y
	Source: own elaboration.

  As prices are equal to marginal costs, the market equilibrium conditions are defined as follows:

	𝜕𝑈 𝑖 𝜕𝑋 𝑖	+ 𝛼	𝜕𝑈 𝑖 𝜕𝐻 𝑖	+ 𝛽	𝜕𝑈 𝑖 𝜕𝑌	= 𝜆𝑝 𝑔 .	(5.9)
	𝛼𝜕𝑈 𝑖 𝜕𝐻 𝑖 𝑒ℎ ⁄ 𝜕𝑈 𝑖 𝜕𝑋 𝑖 +𝛽𝜕𝑈 𝑖 𝜕𝑌 𝑒ℎ ⁄ 𝑒ℎ ⁄	=	𝜕𝑇(𝑐,𝑔) 𝜕𝑔 ⁄ 𝜕𝑇(𝑐,𝑔) 𝜕𝑐 ⁄	-1 ,
								𝑔 (health and
	environmental label). In this first market setting, each consumer 𝑖 maximizes his utility function
	under his budget constraints:
	max 𝑐 𝑖 ,𝑔 𝑖 {𝑈 𝑖 | 𝑝 𝑐 𝑐 𝑖 + 𝑝 𝑔 𝑔 𝑖 ≤ 𝑟 𝑖 }.	(5.7)
	The first-order conditions are derived from the characteristics of the goods 𝑐 𝑖 and 𝑔 𝑖 , which are
	all known by consumers. The derivation of this model leads to the following first-order
	conditions:
	𝜕𝑈 𝑖 𝜕𝑋 𝑖	= 𝜆𝑝 𝑐 ,					(5.8)

  Each consumer 𝑖 maximizes his utility function 𝑈 𝑖 (𝑋 𝑖 , 𝑌, 𝐻 𝑖 ) under his budget constraint(5.7). The first-order conditions are derived in relation to the product characteristics known by the consumers, i.e., 𝑋 𝑖 and 𝐻 𝑖 . These conditions, which are associated with the producer's equilibrium, lead to the

	following market equilibrium condition:
	𝛼	𝜕𝑈 𝑖 𝜕𝐻 𝑖 ℎ ⁄ 𝜕𝑈 𝑖 𝜕𝑋 𝑖 ℎ ⁄	=	𝜕𝑇(𝑐,𝑔) 𝜕𝑔 ⁄ 𝜕𝑇(𝑐,𝑔) 𝜕𝑐 ⁄	-1 ,

  The technical difficulty is to design a PES resulting in sufficient ES in a specific area to meet this ecological threshold. While the literature emphasizes that promoting landscape approaches, hence encouraging farmers from the same area to work together, is necessary, the small amount of initiatives shows that implementation is difficult, in particular because farmers' acceptance of collective requirements in PES is low. To overcome this issue, bonus mechanisms are an opportunity to introduce incentives for collective action as top-ups of payment conditioned to individual commitments. Using a survey-based approach, we test ex-ante the acceptability of a sponsorship bonus delivered to participants who enroll new farmers from the eligible area, combined or not with a collective result bonus delivered to all participants for meeting an environmental target defined at the landscape scale. The bonus options are included as an attribute in a choice experiment for a hypothetical PES contract for improving surface water quality in catchment areas in the northwest of France. The choice experiment approach measures and breaks down preferences for specific attributes of PES design, in particular for the bonus option. In addition, we propose individual per-hectare payment levels that can exceed those currently proposed in AECM to measure the farmers'

willingness to accept which may go beyond income foregone. By doing so, we open the possibility for the hypothetical PES to be (partly) financed by (local) private or public contributors with a willingness to pay for water quality improvements (water catchment bodies, 123 local companies...). Results suggest that a sponsorship bonus by itself is cost-effective.

Table A2 . 2 .

 A22 Regions of the farms of the sample. Significance levels: *** p-value <0.001, ** p-value <0.01, * p-value<0.05, + p-value<0.1. Standard errors in parentheses. AWU : annual work unit. LU: livestock unit. AECM: Agri-Environment-Climate Measure. OFS: Organic farming support. Source: own elaboration.

	Mixed crops farming Pays de la Loire	-0.472 *** (0.022) 0.083 ** (0.028)	1.287 *** (0.252) 3.677 *** (0.274)	0.396 *** (0.023) 2.515 *** (0.051)	3.110 *** (0.188) 6.037 *** (0.545)
	Mixed livestock dominated by grazing livestock Bretagne	-0.315 *** (0.020) 0.609 *** (0.028)	1.883 *** (0.210) 3.920 *** (0.275)	0.483 *** (0.029) 1.799 *** (0.052)	0.142 (0.234) 6.028 *** (0.558)
	Region Mixed farming: field crops and grazing livestock, other Poitou-Charentes	% 0.395 *** (0.028)	Baseline 2.184 *** (0.268) 2.236 *** (0.051)	9.370 *** (0.553)
	Ile de France combination of crops and livestock Aquitaine	1.42 -0.212 *** (0.028)	-2.064 *** (0.281)	2.409 *** (0.050)	7.543 *** (0.541)
	Champagne-Ardenne Age (years) Midi-Pyrénées	6.23 -0.007 *** (0.000) -0.475 *** (0.028)	0.064 *** (0.002) -3.120 *** (0.281)	-0.018 *** (0.000) 2.223 *** (0.049)	0.010 ** (0.003) 8.293 *** (0.535)
	Picardie No general education Limousin	3.52 -0.350 *** (0.013) -0.372 *** (0.030)	-0.790 *** (0.107) -1.991 *** (0.289)	-0.515 *** (0.018) 2.351 *** (0.054)	-0.721 *** (0.166) 6.647 *** (0.568)
	Haute-Normandie Primary school certificate Rhône-Alpes	2.20 -0.476 *** (0.013) 0.049 + (0.028)	-1.222 *** (0.114) -2.121 *** (0.269)	-0.503 *** (0.018) 2.449 *** (0.050)	0.989 *** (0.186) 6.851 *** (0.536)
	Centre Secondary education (short) Auvergne	5.97 -0.320 *** (0.010) -0.293 *** (0.028)	-1.828 *** (0.089) -4.169 *** (0.276)	-0.319 *** (0.014) 2.286 *** (0.052)	-0.062 (0.130) 6.927 *** (0.553)
	Basse-Normandie Bourgogne Nord Pas de Calais Lorraine Alsace Franche-Comté Pays de la Loire Bretagne Poitou-Charentes Aquitaine Midi-Pyrénées Limousin Rhône-Alpes Auvergne Languedoc Roussillon Provence-Alpes-Côte d'Azur Corse Source: 2016-2019 French FADN data. Secondary education (long) Languedoc Roussillon Intercept Non-agricultural higher education Provence-Alpes-Côte d'Azur Decoupled payments (100€/ha) No agricultural education or training ≤120 h Corse Coupled payment for suckler cows (1,000€) Primary agricultural education Observed participation in AECM in 2015 Fuel price (€/l) Secondary agricultural education (short) Observed participation in OFS at t-1 Land lease (100€/ha) Secondary agricultural education (long) Observed participation in OFS in 2015 Standard gross production (100,000€) Agricultural higher education (short) Observed participation in AECM at t-1 Labour (AWU/ha) Agricultural higher education (long) 2016 Utilised agricultural area (100ha) Share of permanent grasslands 2017 Depreciation (10,000€/ha) Density of grazing livestock (LU/ha) 2018 Share of rented land Natura 2019 Less favoured area Organic certification ρ Cereals, oleaginous, protein crops, other field crops Ile de France σ Vegetable gardening, horticulture Champagne-Ardenne Number of observations Wine with quality label, other wine Picardie Payment observations Other permanent crops Haute-Normandie Log likelihood Dairy farming Centre AIC Beef farming Basse-Normandie Schwarz criterion Mixed cattle farming Sheep and goat farming Pigs and poultry farming, mixed livestock dominated by Franche-Comté granivores Alsace Lorraine Nord Pas de Calais Bourgogne Pseudo-R2 (McFadden)	3.90 4.99 3.40 2.54 2.25 1.98 8.16 8.31 5.69 7.62 8.40 2.55 6.66 4.59 5.25 3.84 0.54 -0.279 *** (0.010) 0.142 *** (0.028) -1.125 *** (0.041) 0.454 *** (0.028) 0.001 (0.001) -0.223 *** (0.019) 0.006 *** (0.001) -0.239 *** (0.019) 2.488 *** (0.007) 0.501 *** (0.025) -0.265 *** (0.017) -0.640 *** (0.012) -0.002 *** (0.000) -0.230 *** (0.017) -0.082 *** (0.002) -0.086 *** (0.017) 0.007 *** (0.001) -0.511 *** (0.008) 0.186 *** (0.004) 0.490 *** (0.010) -0.345 *** (0.006) -0.005 *** (0.001) -0.022 *** (0.004) -0.242 *** (0.006) 0.180 *** (0.008) 0.408 *** (0.009) -0.021 ** (0.007) 0.790 *** (0.009) -0.034 *** (0.005) -0.487 *** (0.009) 0.495 *** (0.032) -1.153 *** (0.026) 0.046 (0.029) 28,967 -0.457 *** (0.013) 0.400 *** (0.029) 2,442 -0.534 *** (0.021) -0.145 *** (0.031) -506,741 -0.103 *** (0.009) -0.091 ** (0.029) 1,013,733 0.047 *** (0.010) -0.528 *** (0.029) 1,015,228 0.167 *** (0.011) 0.159 *** (0.011) -0.399 *** (0.030) -0.311 *** (0.013) -0.063 + (0.033) 0.002 (0.029) 0.201 *** (0.030) -0.283 *** (0.028) 0.237	Participation decision (𝐷 𝑖 * ) -0.259 *** (0.014) 2.091 *** (0.050) -3.439 *** (0.064) Baseline -1.496 *** (0.087) 0.128 (0.283) 2.907 *** (0.388) 1.852 *** (0.277) 1.681 *** (0.051) 0.042 + (0.023) 0.006 *** (0.000) -3.305 *** (0.158) 0.0358 (0.026) Baseline 0.213 *** (0.001) -0.019 *** (0.001) -3.940 *** (0.145) -0.000 (0.025) 1.880 *** (0.218) -2.974 *** (0.134) 0.202 *** (0.023) -1.754 *** (0.096) 0.149 *** (0.034) 0.039 *** (0.005) -0.002 *** (0.000) -2.657 *** (0.132) -0.017 (0.023) 1.449 *** (0.010) 0.068 *** (0.017) -0.030 *** (0.003) -2.387 *** (0.135) 0.092 *** (0.024) -0.354 *** (0.013) 0.192 *** (0.021) -0.435 *** (0.023) Baseline -0.083 (0.063) -0.270 *** (0.010) 2.493 *** (0.037) 0.090 *** (0.006) 2.149 *** (0.088) -0.373 *** (0.016) -0.209 *** (0.054) -0.282 *** (0.009) -0.399 *** (0.079) -0.043 + (0.021) -1.014 *** (0.062) -0.143 *** (0.011) 0.032 (0.050) -349 *** (0.009) -1.230 *** (0.072) 0.020 + (0.010) 0.542 *** (0.064) -0.031 + (0.016) Baseline -0.779 *** (0.057) 0.853 *** (0.068) 2.285 *** (0.008) 0.229 *** (0.011) 0.121 *** (0.011) 0.466 *** (0.082) 0.021 (0.015) 2.264 *** (0.326) 2.342 *** (0.055) 5.619 *** (0.013) -0.396 (0.336) 0.238 *** (0.022) -1.344 *** (0.276) 1.505 *** (0.058) 28,967 0.152 (0.138) -0.055 ** (0.018) 0.692 * (0.283) 2.260 *** (0.054) 1,657 0.837 *** (0.214) 0.777 *** (0.020) 0.230 (0.299) 2.066 *** (0.056) -321,181 2.018 *** (0.078) 0.351 *** (0.016) 2.805 *** (0.280) 2.063 *** (0.052) 642,613 0.755 *** (0.076) 0.261 *** (0.018) 2.179 *** (0.272) 2.015 *** (0.052) 644,109 1.404 *** (0.091) 0.200 *** (0.025) 0.675 *** (0.088) 0.084 *** (0.018) -3.773 *** (0.285) 2.202 *** (0.054) -0.326 ** (0.117) 0.260 *** (0.019) -1.453 *** (0.290) 2.424 *** (0.054) 1.133 *** (0.277) 2.590 *** (0.053) -1.456 *** (0.297) 2.148 *** (0.054) -0.191 (0.273) 2.610 *** (0.051) 0.516	Acceptable payment -0.697 *** (0.131) 6.643 *** (0.537) (𝑃 𝑎𝑖 ) in 1,000€ 4.618 *** (0.550) -11.588 *** (0.680) 4.136 *** (0.238) 0.157 *** (0.018) 3.962 *** (0.229) 0.038 ** (0.013) 2.581 *** (0.206) -0.030 (0.287) 3.694 *** (0.209) -0.030 *** (0.006) 3.841 *** (0.210) -0.916 *** (0.114) 0.193 *** (0.023) -0.770 *** (0.091) 0.980 *** (0.267) -2.382 *** (0.128) -0.465 *** (0.083) 8.247 *** (0.062) 0.542 *** (0.101) -0.550 *** (0.079) -2.384 *** (0.349) -2.602 *** (0.139) 1.208 *** (0.091) 0.905 *** (0.168) -0.080 (0.091) 16.683 *** (0.580) 7.102 *** (0.021) 1.315 *** (0.137) 8.126 (0.600) 0.428 * (0.187) 7.822 (0.577) 0.976 *** (0.159) 5.321 (0.581) 3.661 *** (0.167) 9.058 *** (0.559) 3.161 *** (0.135) 5.635 *** (0.549) -1.521 *** (0.149) 3.617 *** (0.563) 8.818 *** (0.572) 0.559 ** (0.170) 14.228 *** (0.559) -0.378 * (0.147) 7.245 *** (0.587) -0.432 + (0.225) 8.352 *** (0.547)

Table A5 . 1

 A51 Eco-Methane scenarios attribution to the French regions Source: The authors, based on the French 2018 annual dairy survey and Bleu-Blanc-Coeur data. Analyse économique des paiements pour services environnementaux, entre label et mesure agro-environnementale Mots clés : services environnementaux, bien public, politique agro-environnementale, étiquetage alimentaire, consentement à payer, consentement à recevoirRésumé : Cette thèse de doctorat applique des approches microéconomiques empiriques et théoriques pour analyser l'efficacité des paiements pour services environnementaux dans le secteur agricole. J'évalue des leviers pour favoriser leur adoption par les agriculteurs à différentes échelles. Je montre empiriquement que cibler une partie des aides au revenu de la politique agricole commune vers un financement accru des mesures agro-environnementales et climatiques et du soutien à l'agriculture biologique favorise la participation à ces dispositifs. Ma principale contribution est de mettre en évidence qu'un bonus de parrainage dans les paiements pour services environnementaux est prometteur pour favoriser la participation d'une masse critique d'agriculteurs lorsqu'il existe des effets de seuils écologiques. Les résultats de cette thèse suggèrent aussi que des paiements basés sur les résultats, sous forme de bonus collectif ou de paiement proportionnel à un indicateur environnemental, sont efficaces à la condition que le niveau de paiement soit suffisamment incitatif.

	Auvergne		7 or 8			7 or 8
	Languedoc-Roussillon	11	1, 3 or 5
		30 34	1, 3 or 5 1, 3 or 5		10%	7 or 8
		66	1, 3 or 5
		48	7 or 8		90%
	Provence Alpes Côte d'Azur	5	7 or 11		87%
		4	1, 3 or 5
	Administrative Region	Department Scenarios 6 1, 3 or 5 13 1, 3 or 5	Production share in 2018 (volume) 13%	Attributed scenarios 7 or 11
	Ile de France	83	1, 3 or 5 1, 3 or 5			1, 3 or 5
	Champagne Ardennes	84	1, 3 or 5 1, 3 or 5			1, 3 or 5
	Picardie		1, 3 or 5			1, 3 or 5
	Haute Normandie		1, 3 or 5 Avec une	approche	1, 3 or 5 théorique, je
	Centre Basse Normandie Bourgogne Nord Pas De Calais		1, 3 or 5 m'intéresse à la demande et propose un 1, 3 or 5 2,4,6 outil, le label santé, pour augmenter le 2, 4 or 6 1, 3 or 5 consentement à payer des consommateurs 1, 3 or 5 1, 3 or 5 dans le cas particulier où la technologie de 1, 3 or 5 production jointe des services
	Lorraine	54	1,3 or 5 environnementaux est complémentaire à
	Alsace	55 57 88	59% l'amélioration de la qualité intrinsèque du 1,3 or 5 1,3 or 5 produit agricole en terme de santé. Je 1,3 or 5 7 or 11 contribue à la littérature en montrant que les 41% 1, 3 or 5 préoccupations de santé des 1, 3 or 5 consommateurs peuvent financer
	Franche-Comté	25 39	7 or 10 efficacement 7 or 10 environnementaux	les 76% et	services 7 or 10 compléter les
		70	1, 3 or 5 politiques agro-environnementales. 24%
	Pays de la Loire		2, 4 or 6			2, 4 or 6
	Bretagne		1, 3 or 5			1, 3 or 5
	Poitou-Charentes		1, 3 or 5			1, 3 or 5
	Aquitaine		1, 3 or 5			1, 3 or 5
	Midi-Pyrénées	46 12	7 or 8 7 or 8		60%
		9	1, 3 or 5
		31 32 65	1, 3 or 5 1, 3 or 5 1, 3 or 5		40%	7 or 8
		81	1, 3 or 5
		82	1, 3 or 5
	Limousin		1, 3 or 5			1, 3 or 5
	Rhône Alpes	1	1, 3 or 5
		7	1, 3 or 5
		26 38 42	1, 3 or 5 1, 3 or 5 1, 3 or 5		75%	1, 3 or 5
		69	1, 3 or 5
		73 74	7 or 8		25%

Titre :

Remerciements

Funding

This PhD was co-financed by the Economics and social sciences (ECOSOCIO) division of the INRAE, and the Horizon 2020 research and innovation programme of the European Union under Grant Agreement No. 817949 (CONSOLE project, https://console-project.eu/). This chapter was co-authored with Sabine Duvaleix (Institut Agro, SMART) and Pierre Dupraz (INRAE, SMART), and involved the following individual contributions: Fanny Le Gloux: conceptualisation, investigation, methodology, formal analysis, validation, original draft; Sabine Duvaleix: conceptualisation, methodology, supervision, validation, review and editing; Pierre Dupraz: conceptualisation, supervision, validation. The study was presented at the 14 th Annual Social Science Conference INRAE, SFER, CIRAD (7 th -8 th April 2021, online), and won a Best Poster Award at the 95 th Annual Conference of the Agricultural Economics Society

(29 th -30 th March 2021, online). The analyses also contributed to deliverables D2.6 (Eichhorn et al., 2022) and D3.1 (Dupraz et al., 2022) of the CONSOLE project (https://console-project.eu/).

A preliminary version of the article was published as a Working Paper (Le Gloux et al., 2021).

This present version has been submitted to the Journal of Dairy Science in September 2022 and is under revision.

167, 308-320. https://doi.org/10.1016/j.anifeedsci.2011.04.021 Greene, W.H., Hensher, D.A., 2003. A latent class model for discrete choice analysis: Contrasts with mixed logit. Transportation Research Part B 37, 681-698. https://doi.org/10.1016/S0191-2615(02)00046-2

(Le [START_REF] Gloux | Quels contrats pour valoriser les services environnementaux des agriculteurs ? Which contract types to value farmers' environmental services?[END_REF]. This present version has been submitted to the Journal of Environmental Planning and Management in November 2022 and is under revision.

Experimental design

A CE was conducted to measure farmers' preferences for a 5-year contract for which participants would enroll all their farmland, targeting the improvement of the water quality of rivers in northwestern France. The regions Brittany, Pays de la Loire, and most of the Normandy region are classified as Nitrate Vulnerable Zones under the Nitrates Directive [START_REF] Mte | Arrêté relatif au programme d'actions national à mettre en oeuvre dans les zones vulnérables afin de réduire la pollution des eaux par les nitrates d'origine agricole[END_REF]. While the Water Framework Directive targets good chemical and ecological status of European waters by 2027 [START_REF] Eu | Directive 2000/60/EC establishing a framework for Community action in the field of water policy[END_REF], only 13% of surface waters have a good ecological status in Pays de la Loire, 32% in Brittany and 29% in eastern Normandy (Agence de l'eau Loire-Bretagne, 2020a, 2020b; Agence de l'eau Seine-Normandie, 2018). Locally, some areas are particularly concerning, such as eastern Brittany (Ille-et-Vilaine department) with only 2% of surface waters with good ecological status (Département d'Ille-et-Vilaine, 2022).

The contracts proposed in the CE are characterized by [START_REF] Wunder | Revisiting the concept of payments for environmental services[END_REF] management requirements defining the environmental services to be delivered by farmers, (2) a per-hectare payment distributed to farmers individually on an annual basis if they comply with management requirements and [START_REF]Quelle est la surface de votre SAU en culture permanente/verger (en ha)[END_REF] a bonus option (Table 3.1).

The Hausman-McFadden test reveals the IIA assumption is violated and there are preference heterogeneities across respondents, suggesting the need to rely on ML (Equation (3.4)) or LC (Equation (3.5)) models to characterise preferences. To disentangle preference heterogeneities, we first apply a ML model with attributes and status-quo coefficients defined as random parameters, except for the individual per-hectare payment coefficient. Second, we characterise groups of respondents with similar patterns of preferences using a LC model.

The first ML specification without individual specific variables (ML1) shows the density of hedgerows and the level of the individual per-hectare payment significantly affects respondents' choice with the expected signs (negative effect for the level of hedgerows requirements and positive effect of the level of payment) (Table 3.4). Preferences for the requirement of soil cover are significantly positive, which can be explained by the already high proportion of farmers fulfilling the highest level. Most of our farmers being located in a Nitrates Vulnerable Zone, they must comply with existing regulation which already involves cover cropping during specific periods of the year. The positive parameter might reveal farmers' willingness to be compensated for the effort they already conduct. Farmers exhibit positive preferences for the bonus options, but only the sponsorship bonus by itself is significant. The collective environmental result bonus can be perceived as riskier, as it does not only depend on farmers' individual efforts but also the cumulated efforts of others, as well as other external factors affecting water quality. This result may also reflect that some respondents do not believe the environmental target can be achieved in their area or within the contract length (5 years).

The status quo was chosen in 13% of the choice situations (excluding protesters), and results suggest farmers tend to prefer choosing a contract rather than the opt-out option. The significance of the standard deviation coefficients shows strong preference heterogeneities for both management attributes, the status quo and the bonus option offering both the possibility of a sponsorship bonus and a collective environmental result bonus. The standard deviation of the sponsorship bonus preference parameter being not significant, we define the coefficient as non-random in the second specification. Behind the nonsignificant extra costs found in plain production basins lies a disparity depending on the type of fodder system (Table 4.5). Considering all plain farms (within and outside the western region), we compare the farms with a share of corn silage in the fodder area greater than 30% to the farms with a corn silage share of less than 30%. Extra-costs are significantly lower when the share of corn is high (or the share of grasslands low). Indeed, we find nonsignificant extra costs per additional hectare of grass for farms with more than 30% of corn in the fodder area but positive additional costs of 7.1€/1000 L/ha for the farms with less than 30%. Again, extra production costs per hectare of grass are lower for farms with higher productivity and lower marginal costs.

Our results suggest that the financial needs for dairy farms to incorporate more grass in their fodder crop rotation system are different from one system to another. In particular, dairy farms with already high shares of grasslands might require higher levels of economic incentives to adopt this climate change mitigation lever. The sources of additional variable costs can be an increase in energy consumption (machinery) and other expenses (seeds, fertilizers, etc.) related to pastures and alfalfa management. Joining a PES scheme and producing milk with more grasslands by replacing hectares of cereals with grass or by increasing the fodder area with new grass plots could represent a positive economic incentive in the most intensive lowland farms

Chapter 5. How can labeling for health concerns improve environmental public good provisioning?

This chapter addresses the issue of the underprovision of environmental public goods through the market. Value-chain included payments for environmental services (PES) aim at capturing the willingness to pay for environmental services (ES) of the stakeholders along the food chain, by differentiating goods produced with environment-friendly practices from those produce with so-called "conventional" practices. Through environment-friendly purchasing choices, which often involve the payment of a price premium, actors of the value-chain, and eventually consumers of food products send a price signal to farmers and boost ES jointly provided with agricultural products. Food labelling in particular, help consumers make more environmentfriendly consumption choices with information on the agricultural practices implemented for producing the goods available on the market. Contrary to dedicated schemes, value-chain included PES can not only capture the willingness to pay for ES, but also the type of food product, and any other characteristic attached to the private good that consumers value and are aware of. Therefore, developing this payment channel represents an opportunity to raise additional (indirect) contributions from consumers to ES provision.

This chapter focuses on the environmental performance of labeling strategies to promote an agricultural commodity characterized by the joint and complementary provisioning of a global environmental public good and a superior private characteristic, such as health benefits. In a theoretical analysis based on the impure public good model, we explore different market settings with an environmental label, a health label, and a label promoting both health and the environment. We model how the degree of information on public and private characteristics provided to consumers affects public good provisioning, and derive the conditions for an optimal provision. A simulation is performed to illustrate the impact of consumer preferences on the provisioning of environmental services at the market equilibrium. online). The analyses also contributed to the deliverable D4.4 [START_REF] Zavalloni | Deliverable D4.4: Report on performance and design of solutions for the provision of AECPGs in value chain perspective[END_REF] of the CONSOLE project (https://console-project.eu/).

The main condition on this result is the joint provision of private health and public environmental benefits that can occur with agricultural commodities produced using environmentally friendly agricultural practices. Indeed, crop management practices can impact the nutritional composition of agricultural products [START_REF] Hornick | Factors Affecting the Nutritional Quality of Crops[END_REF] and the environment [START_REF] Tuomisto | Does organic farming reduce environmental impacts? -A meta-analysis of European research[END_REF]. Livestock feeding practices can also affect the composition of animal products and greenhouse gas emissions. For instance, dairy cows fed a higher percentage of grass fodder or extruded linseed both produce milk with a higher omega-3 content, which is recommended for a healthy diet [START_REF] Weill | Effects of introducing linseed in livestock diet on blood fatty acid composition of consumers of animal products[END_REF] and decreases enteric methane emissions per liter of milk [START_REF] Weill | Method to evaluate the quantity of methane produced by a dairy ruminant and method for decreasing and controlling this quantity[END_REF]. Consumers have a willingness to pay for food, health and the environment. When joint provision arises, providing information on complementary private benefits could be effective in attracting additional consumers to contribute to environmental public good provisioning [START_REF] Grolleau | Too much of a good thing? Why altruism can harm the environment?[END_REF].

The rest of the paper is organized as follows. We start with a description of our theoretical framework, which is inspired by the impure public good model of [START_REF] Kötchen | Impure public goods and the comparative statics of environmentally friendly consumption[END_REF]. In the second part, we present the optimal conditions that characterize this economy from a social planner's perspective and an environmental or health agency's perspective. In the third and fourth sections, we derive the different market equilibrium conditions according to the level of information available to the consumer when an environmentally friendly product is labeled based on its private characteristic (health label), public characteristic (environmental label), or both (health and environment label). We then compare the different market settings in terms of environmental public good provisioning and distance to social and environmental optimality based on a simulation in the fifth section. Section six provides a conclusion.

Preliminaries

We start from a theoretical framework in which the utility function of consumers depends on the characteristics of the goods. This approach is widely used to model consumer behavior [START_REF] Gorman | A possible procedure for analysing quality differentials in the egg market[END_REF][START_REF] Lancaster | A new approach to consumer theory[END_REF], particularly in models of impure public goods [START_REF] Cornes | The comparative static properties of the impure public good model[END_REF][START_REF] Kötchen | Impure public goods and the comparative statics of environmentally friendly consumption[END_REF]. In this analytical framework, green products are impure public goods that generate both a private characteristic and a public characteristic. [START_REF] Kötchen | Impure public goods and the comparative statics of environmentally friendly consumption[END_REF] considers that the consumer has a choice between two goods, a conventionally produced good, which generates a private characteristic, and a green good produced from environmentally this last equation into the equilibrium condition (5.12), we obtain a new condition depending on the level of the public characteristic:

(5.14)

The market equilibrium does not correspond to a Pareto optimal allocation. Nevertheless, recalling the environmental agency optimum (Equation (5.5)), the market equilibrium of the health label leads to the optimal public good provision from the perspective of an environmental regulator under specific conditions (including the same level of preference for health and the environment). These conditions will be described in Section 5.5.

Comparison of public good provision

In this section, we assume a functional form of the utility function to compare the level of public good provision from the three types of labels (environmental label, health label, health and environment label) for a same product. We also perform a simulation to observe the evolution of the provision of public goods at the equilibrium of the different market settings according to the consumers' levels of preference for health and environmental benefits.

Public good demand function

To facilitate the comparison between the different market equilibria derived in the following sections and the optimality conditions, we assume that consumers are homogeneous and the utility function has a functional form as follows:

𝑈 𝑖 (𝑋 𝑖 , 𝑌, 𝐻 𝑖 ) = 𝜃 𝑋 ln 𝑋 𝑖 + 𝜃 𝑌 ln 𝑌 + 𝜃 𝐻 ln 𝐻 𝑖 .

(5.15)

where 𝜃 𝑋 , 𝜃 𝑌 and 𝜃 𝐻 correspond to the preference parameters for food, environment and health factors, respectively. This utility function is strictly increasing, twice continuously differentiable and strictly quasi-concave. This type of functional form, such as Cobb-Douglas preferences, considers homothetic preferences, which is classically assumed when deriving aggregate consumer demand from the utility maximization behavior of a representative rational consumer [START_REF] Caselli | A Representative Consumer Theory of Distribution[END_REF].

Source : own elaboration. The environmental label contributes to providing the public good if the price of good 𝑔 is low.

However, even if consumers have high environmental preferences, the strength of environmental labels in stimulating the consumption of good 𝑔 is lower than that of labels that show the improved nutrition/health benefits for consumers. The performance of health labels compared to the optima depends on the level of consumer preferences for the environment and health. Empirical evidence suggests that regarding food, consumer preferences for health, a private characteristic, tend to be higher than those for environmental quality (Aldanondo-Ochoa and [START_REF] Aldanondo-Ochoa | The private provision of public environment: consumer preferences for organic production systems[END_REF][START_REF] Rudd | Preferences for health and environmental attributes of farmed salmon amongst southern ontario salmon consumers[END_REF]. This suggests that 𝜃 𝑌 < 𝜃 𝐻 in most actual market settings; thus, there is a real opportunity for environmental public goods provision to demonstrate and provide information on the complementary health benefits of environmentally friendly food consumption. This case is shown on the left side of the graph, where the ratio to collect new data on fodder rotation systems and diet composition using the yearly questionnaire among Eco-Methane participants. Since Bleu-Blanc-Coeur measures their enteric methane emissions every month, it would allow the estimation of emission reductions as a function of diet and fodder rotation system information. If robust enough, this ES supply function could be applied to estimate emissions reduction with FADN data, together with extracosts.

Finally, the findings of the fifth chapter open up new questions on the characterization of complementary joint production of ES and quality/nutritional characteristics of food products.

In particular, I am interested in exploring the case of producers of protected designation of origin products for which agricultural practices are constrained with rules on natural resources management. A hypothesis is that for some quality products tied to the implementation of more extensive practices, the joint complementary provision of ES might be facilitated. This complementarity could be empirically observed if producers of protected designation of origin products or located in an area eligible to the label tend to engage more in AECM.

Appendices Appendix A1. Farm Accountancy Data Network sample coverage of farms with organic practices

Appendix A2. Descriptive statistics of the Farm

Accountancy Data Network sample

139

-100 m de linéaire de haies par hectare de SAU La couverture du sol :

La couverture du sol est déterminée selon le nombre de jours par an pendant lesquels vos terres ont un couvert végétal. Elle dépend de vos surfaces arables et de vos surfaces en prairies permanentes. (Cf. exemple de choix à la fin de ces explications)

3 niveaux vous seront proposés :

-Un taux de couverture du sol de 85%

-Un taux de couverture du sol de 90%

-Un taux de couverture du sol de 95%

Le paiement individuel :

Il s'agit du paiement que vous recevrez pour la mise en place de pratiques limitant l'érosion.

niveaux vous seront proposés :

-Un paiement de 150€/ha de SAU par an

Appendix A6. Instrumentation of grass fodder area and milk production in the estimation of milk production costs

Vector of instruments:

Appendix A8. Assumptions on the production technology of differentiated goods

We consider the producer uses a variable input 𝑧 (fertilizer, pesticides) in quantity 𝑧 𝑐 to produce good 𝑐 and in quantity 𝑧 𝑔 to produce good 𝑔 according to the production technologies. We assume each technology follows a translated quadratic form, strictly concave in 𝑧 [START_REF] Carpentier | Accounting for Heterogeneity in Multicrop Micro-Econometric Models : Implications for Variable Input Demand Modeling[END_REF][START_REF] Femenia | How to significantly reduce pesticide use: An empirical evaluation of the impacts of pesticide taxation associated with a change in cropping practice[END_REF]. The prices of these inputs are 𝑤 𝑐 and 𝑤 𝑔 , and we assume that 𝑤 𝑐 < 𝑤 𝑔 . The short-term producer's optimization program is written as follows: To represent the fact that the production of good 𝑔 is less polluting than the production of good 𝑐 , we consider that 𝜇 𝑔 = 𝜇 𝑐 and 𝜂 𝑔 < 𝜂 𝑐 , which means that less variable inputs that are considered polluting are needed to produce good 𝑔. We assume that 𝛾 𝑐 = 𝛾 𝑔 = 𝛾. We also assume that the marginal cost of good 𝑔 is higher than that of good 𝑐 for a given level of production, such as: