TWG5: Teacher education at the university

Marianna Bosch 1 , Carl Winsløw 2 1 Faculty of Education, Universitat de Barcelona, marianna.bosch@ub.edu 2 IND, Faculty of Science, University of Copenhagen, Denmark, winslow@ind.ku.dk

TWO MEANINGS

In mathematics education research, the teaching profession occupies a place of pride, both as an important partner, as an object of study, and as a consumer of the ideas and results that researchers produce. Historically, the development and inclusion of mathematics education positions at universities are inseparable from the professional education of teachers. The ever-increasing importance and challenges of mathematics in schools have also led to considerable scholarly and political attention to conditions for improving the pre-and in-service education of mathematics teachers. While secondary school teacher education has been university based in most Western countries for centuries, this is increasingly the case even for primary schools. Indeed, mathematics education researchers frequently exercise their teaching duties in university-based teacher education, usually giving specialised courses on mathematics education for future teachers. Considering that such courses are a specific form of university mathematics education, we have the first meaning of the title of this TWG.

On the other hand, university mathematics education as a field of practice is usually construed as the teaching of post-secondary mathematics at the university level, especially within general areas like algebra and analysis. In general, undergraduate mathematics courses are often shared by a large variety of study programmes and, in many institutions, future teachers take such basic mathematics along with students aiming for other professions. It is thus difficult or impossible to draw exact boundaries between university mathematics education and mathematics teacher education, and several contributions to this TWG focus explicitly on the connections between general (or "pure") mathematics teaching at university, and the specific needs and courses of school mathematics teachers. This is the second meaning of the title of this TWG.

A third meaning arises from considering the profession of teaching mathematics at the university. The challenges of students with university mathematics have unquestionably led to an increasing interest in the practices and preparation of their teachers, and this (partly hypothetical) meaning of the title of our TWG is also represented by one contribution to the group.

MATHEMATICS EDUCATION COURSES AT THE UNIVERSITY

As suggested by Csapodi's poster on a recent reform of Hungarian mathematics teacher education, many countries and institutions distinguish sharply between courses on "mathematics" and courses on "teaching". When this is the case, the latter can be more or less specialised on "mathematics teaching", and the specialised variants usually refer to mathematics education research as a scholarly base.

Barquero and Bosch present and discuss the idea of a study and research path in teacher education (SRP-TE), motivated by professional questions of a didactical nature, like "how to teach randomness and statistics in primary school". In an experimental setting within primary school teacher education at the University of Barcelona, the students first carry out a mathematical activity, which has been designed by the authors with inspiration from the classical bottle situation [START_REF] Brousseau | An experiment on the teaching of statistics and probability[END_REF]. They then analyse their work from a mathematical and didactics perspective and proceed to design a similar path for primary school pupils (with an eventual implementation in some cases. The authors reflect on the similarities and differences between the SRPs-TE and the study and research paths (SRPs) proposed to non-teachers university students (in engineering, science or administration degrees). They consider the possibility to extend some instructional strategies and resources designed for teacher education to non-teacher students, in particular those related to the analysis of the mathematical activities carried out.

Hakamata, Otaki, Fukuda and Otani also experimented a study and research path based on the bottle situation, but now in secondary mathematics teacher education at Kochi University. The design and aim are different from the above study: to detect what mathematical praxeologies could be realised by the students, given that they had some university background in probability and statistics. The authors create a reference praxeological model of what they consider as relevant from this background to explore the bottle situation and analyse the students' actual exploration in terms of this model. It turns out that students were able to mobilise some but not all of the anticipated elements of the model. The authors consider that students could have mobilised some of the missing elements with more explicit instruction from the teachers and that student errors in such an inquiry process may be important sources of learning.

LINKS BETWEEN UNIVERSITY AND SCHOOL MATHEMATICS

A majority of papers in this TWG consider, in one way or another, the links and gaps between university mathematics courses (or activities) that are not specific to future teachers and school mathematics or, more broadly, the activities of a school mathematics teacher. Most of the papers report on experiments to strengthen the links, while others seek to identify and explain the gaps.

Goor, Pinto and Karsenty present some aspects of the M-Cubed project in Israel, designed to explore interactions between mathematics researchers (called "mathematicians") and experienced secondary school teachers of mathematics, as they meet to discuss video-recorded lessons from secondary school. The mathematicians focus on the characteristics of the mathematical problem while the teachers concentrate more on aspects related to the observed interaction in the lesson at stake. The authors consider that such interactions can be fruitful experiences of boundary-crossing but that facilitators or brokers are needed to overcome what might otherwise be discontinuities in the interaction.

Pustelnik also investigated the perspectives of mathematicians (in the above sense), but this time concerning their activity as lecturers in mathematics courses for future secondary-level teachers. From interviews, it appears that some lecturers occasionally try to show how the contents they teach are related to school mathematics, but none have recent or specialised knowledge about the latter. In the German university where the lecturers teach, they give similar but separate lectures to "mathematics students", and "teacher-students" (different undergraduate programmes in Germany), but the lecturers believe the contents delivered in each case should be essentially the same.

Bübenbender-Kuklinski, Hochmuth and Liebendörfer examined, equally in the German context, the relevance for the teaching profession that mathematics teacher students attribute to mathematical domains which are mandatory in their undergraduate studies (such as calculus and linear algebra). They do so through a longitudinal quantitative study, which gives rise to interesting hypotheses, like students attributing less relevance to domains in which they feel insecure; however, supplementary qualitative data will be needed to confirm such causalities.

Hochmuth and Peters investigated, on their side, the qualities of the mathematical knowledge that German teacher students take away from their undergraduate studies. More specifically, in a graduate course specifically designed for these students, they found that the participants were largely unable to mobilise basic results from undergraduate analysis and linear algebra to carry out a qualitative analysis of ordinary differential equations, and to engage such analysis in modelling problems arising in other disciplines. The authors notice that both tasks are indeed highly relevant to the curriculum they prepare to teach.

The problems of connecting school mathematics and university mathematics are considered from an intervention perspective in three papers and one poster. Bauer and Müller-Hill propose a set of principles for designing tasks that could help teacherstudents in Germany to deepen and professionalize the mathematical knowledge learnt in undergraduate mathematics courses of linear algebra and analysis, particularly in relation to proof. These tasks are worked with by students in modules that run in parallel with the courses, bringing promising results.

Huo and Winsløw also present a list of task design principles for students of a Danish university in a capstone mathematics course, which, unlike all university mathematics courses they have taken, is designed specifically with the needs of teachers in mind. The goal of the design is to produce tasks that can develop and assess students' capacity to mobilise the mathematical knowledge studied at the university on secondary mathematics problems. Several examples of tasks are given and analysed according to the principles.

Viirmann and Jacobsen present a course design carried out at a Swedish university to cover mathematical and didactical content jointly and concurrently. The teachers (and authors) team teaches the course and personifies, through their research background in mathematics and mathematics education, the two strands of the course. The two teachers take turns to be the "main" teacher, and an example is given of how the other may inject comments and questions from his perspective is given, for instance, to highlight general perspectives from either university mathematics or didactics that apply to the topic at hand. The authors suggest that care should be taken in such a dialogue setting, not to lose the students.

The poster by Delori and Wessel presents an idea for connecting preservice teachers' knowledge of school algebra (like equation solving) and abstract algebra through design research, which at the time of writing was not yet carried out. The poster by Broley, Buteau and Müller outlines a sequence of modules, designed and tested at a Canadian university. One aim is to provide an experience of using coding to learn mathematics, which is particularly relevant to future teachers in times when new school curricula require pupils to get such an experience. Finally, the poster by Vinerean, Brandl and Liljekvist explain how preservice mathematics teacher's work with "Interactive Mathematical Maps" can help them gain a vision of mathematics as being constructed by humans and related to important problems.

EDUCATING UNIVERSITY MATHEMATICS TEACHERS

There were no contributions in TWG5 reporting on preservice education for university teachers of mathematics, but Gómez-Chacón, Hochmuth and Peters report on a workshop for a mixture of early career and more experienced university mathematics teachers from Spain, carried out in the context of the European PLATINUM project. The aim was to initiate participants to an inquiry-based approach to mathematics teaching and learning and to develop their skills to design mathematical tasks to be used in such an approach, based on collegial reflection, and taking into account concrete constraints in the participants' courses. The outcomes seem to confirm that task design could be an important and fruitful topic in in-service courses for university mathematics teachers, and (as to some extent demonstrated by previously outlined papers) a lever for implementing new results from university mathematics education research in practice.


Chloé Duvivier

Emma Cazou

Stéphanie Truchet-Aznar

Cédric Brunelle

Jean Dubé

When, where, and for what industries does

Keywords: Broadband, Establishment births, Urban gradient broadband, establishment births, urban gradient JEL classification: O18, O52, R11

come

Introduction

While the Internet can create new opportunities for non-central areas, the idea that it will put an end to distance [START_REF] Cairncross | The death of distance: 2.0: How the communications revolution will change our lives[END_REF] remains an exaggeration [START_REF] Camagni | ICTs and territorial competitiveness in the era of internet[END_REF][START_REF] Polèse | Is distance really dead? Comparing industrial location patterns over time in Canada[END_REF]. As well-known, greater market integration often harms peripheral areas with little prior exposure to competition. Moreover, while the Internet is a substitute for certain types of agglomeration economies, it is complementary to face-to-face interactions [START_REF] Büchel | Cities and the Structure of Social Interactions: Evidence from Mobile Phone Data[END_REF][START_REF] Leamer | The economic geography of the internet age[END_REF]. Therefore, while it may lead to the dispersion of some economic activities, the Internet may strengthen the concentration of others, and in particular that of knowledge-intensive activities.

Until now, little empirical work has been carried out, however, to understand the complexity of the spatial impact of the Internet on establishment births and several issues remain unresolved. First, to our knowledge, no study has examined the impacts of the Internet across the entire urban hierarchy, taking into account both the size and location (urban proximity) of areas 1 . Second, a key issue is whether broadband provision generates different sectoral effects across locations and, in particular, whether it may foster the dispersion not only of low-skilled and low-paid activities to non-central areas, but also that of (selected) knowledge-intensive activities. Third, the literature remains silent on whether costly ultrafast broadband generates additional benefits compared to lower-speed technologies [START_REF] Abrardi | Ultra-fast broadband investment and adoption: A survey[END_REF]. In particular, we may wonder whether ultrafast technologies, needed for more sophisticated digital tools, are really worthwhile in non-central areas given their limited absorptive capacity [START_REF] Salemink | Rural development in the digital age: A systematic literature review on unequal ICT availability, adoption, and use in rural areas[END_REF]. This issue is relevant given that many public broadband programs are specifically designed to promote fast broadband coverage in less densely populated areas.

This paper provides a comprehensive study on the effect of broadband on establishment births by analyzing how impacts vary across locations, industries, and speed levels. To assess whether effects vary according to the size of areas and their proximity to urban centers, we identify five types of areas: larger urban centers, small and middle urban centers, periurban areas, urban-influenced rural areas, and isolated rural areas. Moreover, broadband effects are estimated for six different industries, including basic nontradable industries (e.g., construction), basic tradable (e.g., retail) and knowledge-intensive services (e.g., high-order services). In 1 A notable exception is [START_REF] Mack | Variations in the Broadband-Business Connection across the Urban Hierarchy[END_REF] who uses seven different classifications of US counties to take into account both their population and proximity to large urban centers. The empirical analysis is carried out for 34,766 municipalities ("communes") in France from 2013 to 2017. Compared to a more aggregated analysis, the municipal level allows capturing broadband dispersion effects to smaller municipalities and periurban areas. The time period also matters for our study, as it corresponds to the implementation of the French Very High-Speed Broadband Plan, which has led to substantial broadband provision in all parts of the country2 . The effect of broadband access on establishment births is estimated using a negative binomial model. To mitigate endogeneity issues, we provide falsification tests.

The paper is organized as follows. The following section identifies the main channels by which broadband can affect establishment births and highlights how impacts are likely to vary across locations, industries, and speed levels. The methodology is presented in the third section and data in the fourth section. Econometric results are analyzed in the fifth section, followed by conclusions.

Broadband and establishment births

Broadband can affect establishment births in a given area in two ways. First, it can enable -or deter -new individuals from entering the market (effect on local entrepreneurship).

Second, it can weaken locational constraints, leading to a change in location choices of incumbent and new establishments (effect on firm location determinants).

Broadband and entrepreneurship

The Internet may affect business startups by creating new market opportunities, lowering entry barriers, and enhancing entrepreneurial capabilities.

Entrepreneurial opportunities

By allowing online trade, broadband increases market reach and thus the profitability of setting up new businesses. However, market openness goes both ways and only favors locations with comparative advantages. In isolated areas, increased market integration often harm

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retailers serving local markets, as they now find themselves in direct competition with online sellers offering more diversified product lines and lower-priced products [START_REF] Cumming | The differential impact of the internet on spurring regional entrepreneurship[END_REF][START_REF] Freathy | Coping with change: the implications of e-commerce adoption for island consumers[END_REF]. Negative effects have also been found for finance, insurance and real estate as ICT allow many tasks to be carried out centrally, and thus, lead to the shutdown of small local agencies in remote areas (Duvivier et al., 2018;[START_REF] Kandilov | Infrastructure investment and rural economic development: an evaluation of USDA's broadband loan program[END_REF][START_REF] Shideler | Broadband impact on small business growth in Kentucky[END_REF]. On the contrary, positive effects have been observed in rural areas close to urban agglomerations or with a preexisting cluster of activities [START_REF] Cumming | The differential impact of the internet on spurring regional entrepreneurship[END_REF][START_REF] Kim | Broadband internet and new firm location decisions in rural areas[END_REF]Mack, 2014-a).

The importance of online trade varies across industries. Broadband only generates new business opportunities for industries producing services or products tradable online, such as wholesale trade, and retail trade (excluding perishable items)3 . On the other hand, we would expect few changes for manufacturing, construction and for most consumer and producer services. While the latter are often "technically" deliverable online, such activities (e.g., finance, legal and accounting activities) often imply the exchange of uncodified information and trust, which strongly restricts their exchange potential online.

Lower entry barriers

Broadband may also foster entrepreneurship by reducing the costs associated with information access, communication, business coordination and training [START_REF] Audretsch | Infrastructure and entrepreneurship[END_REF][START_REF] Lamie | Positive Examples and Lessons Learned from Rural Small Business Adoption of E-Commerce Strategies[END_REF]. It can also lower fixed cost entry barriers, which sometimes constitute a major impediment for new entrants. First, banks are more likely to grant higher credit to firms that use more intensively ICT as it helps banks obtain better information on borrowers and constitutes a positive signal on firms quality and creditworthiness (Dalla Pelegrina et al., 2017).

Second, good broadband access allows firms to use sophisticated digital tools, such as cloud computing, which can reduce capital expenditures and sunk costs. In this case, ultrafast broadband access, instead of lower-speed first-generation technologies, is likely to provide benefits for businesses, as sophisticated digital applications require high-speed levels [START_REF] Nicoletti | Digital technology diffusion: A matter of capabilities, incentives or both?[END_REF]. This may explain why some studies find that ultrafast broadband access has a more beneficial impact on establishments than lower speed technologies [START_REF] Canzian | Broadband upgrade and firm performance in rural areas: Quasi-experimental evidence[END_REF][START_REF] Lapointe | Does speed matter? The employment impact of increasing access to fiber Internet[END_REF][START_REF] Mccoy | The impact of broadband and other infrastructure on the location of new business establishments[END_REF]Mack, 2014-b;[START_REF] Prieger | The Importance of Transportation, Broadband, and Intellectual Infrastructure for Entrepreneurship[END_REF][START_REF] Whitacre | Broadband's contribution to economic growth in rural areas: Moving towards a causal relationship[END_REF].

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w

Such advantages should primarily apply to industries where new firms require considerable financial outlays to enter the market, such as manufacturing and wholesale [START_REF] Lofstrom | Why are some people more likely to become small-businesses owners than others: Entrepreneurship entry and industry-specific barriers[END_REF]. Broadband is also likely more beneficial for technology-intensive industries, which use sophisticated digital tools. Thus, for manufacturing, empirical studies indicate high broadband effects on firm births in the high-tech manufacturing sector [START_REF] Audretsch | Infrastructure and entrepreneurship[END_REF]Mc Coy et al., 2018) but only small or insignificant effects on manufacturing as a whole [START_REF] Kim | Broadband internet and new firm location decisions in rural areas[END_REF][START_REF] Mack | Industry variations in the broadband business nexus[END_REF].

Entrepreneurial capabilities

Broadband can also raise entrepreneurial capabilities [START_REF] Audretsch | Infrastructure and entrepreneurship[END_REF]. The Internet fosters access to information and exchange of ideas, raises interactions with distant partners, and helps establish business contacts. By enabling information and coordination, broadband helps individuals to better understand market conditions and to conceive good ideas and products (e.g., creation of new market niches). Here, again, access to ultrafast broadband should provide additional benefits for businesses, as it allows high-resolution real-time collaboration and better access to information (faster file transfers, access to high-quality videos for online training) [START_REF] Ezell | The need for speed: The importance of nextgeneration broadband networks[END_REF].

Some authors expect broadband returns to be stronger in rural areas, where establishments need more digital tools to resolve their greater information and coordination issues [START_REF] Forman | How did location affect adoption of the commercial Internet? Global village vs. urban leadership[END_REF]Mack, 2014-b). However, broadband access by itself is often not sufficient for creating a good entrepreneurial context in remote rural areas where structural deficiencies (e.g., lack of skilled labor) may hinder new business creation [START_REF] Cumming | The differential impact of the internet on spurring regional entrepreneurship[END_REF][START_REF] Galloway | Can broadband access rescue the rural economy?[END_REF]. Therefore, the highest broadband returns are expected in "intermediate areas" that face high information and coordination issues but, at the same time, also offer relatively good initial conditions. In particular, small-connected peripheral cities, which are often service centers for surrounding rural areas and thus concentrate a minimum amount of professional and public services [START_REF] Meijers | Stretching the concept of 'borrowed size[END_REF], could become good locations for entrepreneurship.

Broadband could raise entrepreneurial capabilities more intensely in informationintensive industries, such as computer services, where interacting with other programmers and software developers is essential to obtain information and develop new ideas [START_REF] Audretsch | Infrastructure and entrepreneurship[END_REF]. However, while most studies find a positive link between broadband and knowledgeintensive business services (KIBS) creation [START_REF] Mack | The importance of broadband provision to knowledge intensive firm location[END_REF][START_REF] Mack | Industry variations in the broadband business nexus[END_REF], the impact does not appear to be stronger in this sector than in other sectors [START_REF] Mack | Variations in the Broadband-Business Connection across the Urban Hierarchy[END_REF]. This most likely arises from the fact that KIBS mainly relies on uncodified information and knowledge, which cannot be easily exchanged online.

Broadband and firms' location choices

Broadband access: a location factor on its own

As broadband can raise firms' productivity 4 [START_REF] Canzian | Broadband upgrade and firm performance in rural areas: Quasi-experimental evidence[END_REF], locations endowed with broadband benefit from a competitive advantage over others and thus enjoy a higher number of establishment births. However, as positive productivity effects have mainly been identified for industries employing highly skilled labor [START_REF] Akerman | The skill complementarity of broadband internet[END_REF], broadband availability is likely to be a location determinant only for these specific industries.

Broadband effects on firms' location choices

By fostering information flows, interactions with partners, and access to customers and labor, broadband may be seen as a substitute for agglomeration economies. In this way, establishments can be located at increasing distances from large urban centers and still enjoy a wide range of agglomeration externalities, including good access to labor (de Vos et al., 2020), metropolitan functions [START_REF] Meijers | Borrowing size in networks of cities: City size, network connectivity and metropolitan functions in Europe[END_REF], and customers and information [START_REF] Phelps | Small firms, borrowed size and the urban-rural shift[END_REF]. Internet-connected small cities close to large urban centers are likely to become particularly attractive places for firms because they can enjoy agglomeration economies while retaining the advantages of small cities 5 [START_REF] Dijkstra | The economic performance of European cities and city regions: Myths and realities[END_REF]. While this "borrowed size" effect [START_REF] Alonso | Urban zero population growth[END_REF] existed well before broadband, new technologies are likely to reinforce it by leading to an ever-increased integration between locations [START_REF] De Vos | Does broadband internet allow cities to 'borrow size'? Evidence from the Swedish labour market[END_REF][START_REF] Dijkstra | The economic performance of European cities and city regions: Myths and realities[END_REF][START_REF] Hesse | On borrowed size, flawed urbanisation and emerging enclave spaces: The exceptional urbanism of Luxembourg, Luxembourg[END_REF].

Two kinds of areas are likely to "borrow size" and to become particularly attractive destinations: areas close to major urban centers [START_REF] De Vos | Does broadband internet allow cities to 'borrow size'? Evidence from the Swedish labour market[END_REF][START_REF] Phelps | Small firms, borrowed size and the urban-rural shift[END_REF] and small and medium-sized cities benefiting from good communication network connectivity [START_REF] Hesse | On borrowed size, flawed urbanisation and emerging enclave spaces: The exceptional urbanism of Luxembourg, Luxembourg[END_REF][START_REF] Meijers | Borrowing size in networks of cities: City size, network connectivity and metropolitan functions in Europe[END_REF].

In addition, periurban areas and connected small cities are likely to become attractive destinations for some industries but not for others. Although virtual contacts can replace "conversations", the Internet is more a complement for "handshakes" and face-to-face 4 Broadband impact on productivity is, however, debated (e.g., de Stefano et al., 2018). 5 Once again, stronger integration can also lead to competition effects, especially in the smallest cities [START_REF] Meijers | Stretching the concept of 'borrowed size[END_REF][START_REF] Meijers | Borrowing size in networks of cities: City size, network connectivity and metropolitan functions in Europe[END_REF]. interactions [START_REF] Büchel | Cities and the Structure of Social Interactions: Evidence from Mobile Phone Data[END_REF][START_REF] Leamer | The economic geography of the internet age[END_REF]. Therefore, the need for face-to-face interactions often causes knowledge-intensive services to increasingly settle in large urban locations and city centers [START_REF] Duvivier | The great urban techno shift: Are central neighbourhoods the next silicon valleys? Evidence from three Canadian metropolitan areas[END_REF][START_REF] Polèse | Is distance really dead? Comparing industrial location patterns over time in Canada[END_REF],

and not in periurban areas and connected small cities.

Creative industries (e.g., artists, recording studios) may be one exception6 . Compared to other KIBS, they can more easily deliver their services online, provided a high-speed connection (Mack, 2014-b;[START_REF] Townsend | Broadband and the creative industries in rural Scotland[END_REF], and are more sensitive to good quality of life and inspiring working environment [START_REF] Anderson | Great expectations or small country living? Enabling small rural creative businesses with ICT[END_REF][START_REF] Townsend | Broadband and the creative industries in rural Scotland[END_REF].

Therefore, as broadband weakens location constraints, creative industries are increasingly expected to settle in non-central locations with high-speed connections.

Borrowed-size effects are also likely to reinforce the deconcentration of basic, lowskilled and low-paid activities to periurban and connected small cities. In particular, broadband is likely to accelerate the decentralization of back-office activities and land-consuming firms (e.g., wholesale trade), a trend that began well before the Internet.

Methodology

Estimation of broadband effects

The dependent variable in the model -the number of establishment births -is a nonnegative integer with a high frequency of zeros7 . Thus, we estimate a count-data model and, more precisely, a negative binomial model, as the distribution of the dependent variable shows signs of overdispersion (variance greater than the mean).

The model, estimated by the maximum likelihood, assumes that the number of establishment births (y it ) in municipality i at year t depends on broadband provision ( 𝐵𝐵 𝑖𝑡 -𝑠 )

and on a set of K characteristics of this municipality:

(𝑋 𝑘𝑖𝑡 -𝑠 ) with s=1;2 𝑦 𝑖𝑡 = f(𝐵𝐵 𝑖𝑡 -𝑠 , 𝑋 𝑘𝑖𝑡 -𝑠 ,Region 𝑖 ,𝑌𝑒𝑎𝑟 𝑡 )
We proceeded in four steps. In a first step, we estimate broadband effects assuming homogeneous impacts across locations and industries. To do that, we regress the total number of establishment births in municipality i in year t on our indicator of broadband (

) and

𝐵𝐵 𝑖𝑡 -𝑠 F o r P e e r R e v i e w
on a set of control variables ( . measures the share of premises with access to 𝑋 𝑘𝑖𝑡 -𝑠 ) 𝐵𝐵 𝑖𝑡 -𝑠 broadband of at least 3 Mbps and is lagged by one or two years to reduce endogeneity. We also control for a set of characteristics of municipalities described in Section 4. All control variables are lagged by one or two years to reduce reverse causality. We also introduce regional dummy (Region i ) and time fixed effects (Year t ) 8 .

In a second step, we test for heterogeneous broadband effects across locations by introducing interactive terms between the indicator of broadband (

) and dummy 𝐵𝐵 𝑖𝑡 -𝑠 variables for the five categories of areas: larger urban centers; small and middle urban centers; periurban areas; urban-influenced rural areas; and isolated rural areas.

In a third step, we investigate whether the impact varies across industries by estimating the two previously described models (steps 1 and 2) separately for the following six industries: manufacturing, construction, wholesale trade, retail trade, food and accommodation, and highorder services.

In a fourth step, to test whether broadband speed matters, we estimate the models described previously by splitting our broadband measure into two indicators (basic and fast broadband).

Endogeneity and spatial effects

Endogeneity and spatial effects are two major potential issues when estimating the economic effects of broadband access. Endogeneity can arise from both reverse causality (private operators are more likely to build infrastructures in municipalities with a higher number of firms, as it means a higher demand for broadband) and omitted variables (private operators are more likely to invest in economically dynamic municipalities, which are also more attractive to firms).

Previous studies have proposed different solutions to limit endogeneity. Some have employed instrumental variables, with the slope of terrain, household density and pre-existing telecommunication networks used as instruments [START_REF] Kolko | Broadband and local growth[END_REF][START_REF] Mack | The importance of broadband provision to knowledge intensive firm location[END_REF]. However, finding convincing instruments remains challenging. Some authors warn that these instruments may be poorly correlated with broadband access (weak instruments) and may have a direct impact on establishment births, in addition to their effect through broadband access (non-

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exogenous instruments). Other studies have used a fixed effects estimator to control for timeinvariant unobserved heterogeneity (e.g., [START_REF] Lapointe | Does speed matter? The employment impact of increasing access to fiber Internet[END_REF]. However, identification in fixed effects models is difficult for studies carried out over a limited period of time, as within-location variation in broadband over time is generally low [START_REF] Kim | Broadband internet and new firm location decisions in rural areas[END_REF]. Using fixed effects in the case of nonlinear count data models is even more problematic, as areas with no establishment creation over the period are dropped from the analysis9 .

In this study, we use several solutions to limit potential endogeneity. First, we restrict our analysis to establishment births and use lagged values of broadband availability (1-and 2year lagged values). Second, following [START_REF] Mccoy | The impact of broadband and other infrastructure on the location of new business establishments[END_REF], we estimate a series of models, including random effects models with regional and year fixed effects. Finally, to ensure that the results obtained arise from a causal relationship and not from unobserved heterogeneity, we undertake falsification tests. The test consists of randomly redistributing broadband coverage values across municipalities and then re-estimating the model using the permuted broadband variable. The operation is repeated 999 times. Finally, the estimated coefficient based on actual data (the original data set) is compared to the distribution of the 999 coefficients associated with the randomly redistributed broadband variable. If the coefficient associated with the "original" broadband variable is significantly different from the distribution of the 999 coefficients (i.e., belongs to the bottom or the top 5% of the distribution), we can conclude that the findings are most likely causal and not spurious. Note that the falsification tests are undertaken only to test for the robustness of the significant coefficients. This kind of falsification test is increasingly used in empirical analyses (e.g., [START_REF] Komarek | Crime and natural resource booms: Evidence from unconventional natural gas production[END_REF][START_REF] Oliveira | Commute duration and health: Empirical evidence from Brazil[END_REF].

Spatial autocorrelation is another potential issue. To account for spatial effects, we estimate an SLX model for two reasons. First, estimating an SLX model seems the best option when there is no consistent economic argument justifying the use of a specific spatial model [START_REF] Vega | The SLX model[END_REF]. Second, spatial econometric tools are still poorly developed in the case of count data models [START_REF] Glaser | A review of spatial econometric models for count data[END_REF]. To date, most studies have used SLX models, as they can be estimated using standard econometric estimators. Spatial autoregressive models (SAR) and spatial-error models are much less developed. For example, while some SAR models exist (e.g., [START_REF] Lambert | A two-step estimator for a spatial lag model of counts: Theory, small sample performance and an application[END_REF], they are not available for negative binomial distribution and

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for panel data. In this paper, we thus account for spatial effects by introducing several spatially lagged independent variables (see the next section).

Data and descriptive statistics

The study was carried out at the municipal level in France between 2013 and 2017.

Focusing on municipalities ("communes"), the smallest unit of analysis for which broadband and establishment data are publicly available, allows us to take into account most of the heterogeneity in broadband access across areas. More importantly, compared to more aggregated levels, municipal-level studies can better capture broadband dispersion effects (e.g., from the urban core to periurban areas), which are of first interest here. Following previous studies, we exclude the three largest municipalities (Paris, Marseille, and Lyon) to limit the influence of outliers (Mc Coy et al., 2018;[START_REF] Hasbi | Impact of very high-speed broadband on company creation and entrepreneurship: Empirical Evidence[END_REF]. Ultimately, our sample is composed of a panel of 34,766 municipalities.

To account for differences in broadband effects across locations, we use the "2010 division into urban areas" ("zonage en aires urbaines") established by the French Institute of Statistics (INSEE). The major advantage of this classification is that it allows us to take into account both the size and the integration of municipalities within larger urban centers. More precisely, the classification was elaborated in two steps: (i) by identifying urban centers (according to the number of jobs) and (ii) by defining the sphere of influence of each urban center. A municipality is considered to be under the influence of an urban center if at least 40% of its residents with a job work in neighboring urban center(s). Compared to other commonly used categorizations, it is not exclusively based on density or land cover criteria but takes into account the integration of municipalities within larger urban centers 10,11 . This approach is thus particularly relevant, given that broadband effects are expected to vary according to both size and urban influence. -Small and middle urban centers (1,500-10,000 jobs), -Urban-influenced rural areas (municipalities with at least 40% of their residents working in neighboring small and middle urban centers),

-Isolated rural areas.

Figure 1 shows the spatial distribution of municipalities across the five classes, with totals given for each.

[Figure 1]

Broadband data are from the observatory of the French Very High-Speed Broadband Plan, led by the French Digital Agency. The data provide the share of premises (homes, businesses, and public sites) that have access to the following four speed levels: at least 3 Mbps, 8 Mbps, 30 Mbps, and 100 Mbps. Based on these data, we create several indicators. First, we calculate, for each municipality, the share of premises that have access to at least 3 Mbps.

Second, to investigate whether the effects vary according to the speed level, we split this variable into two parts: the share of premises that have access to basic broadband (3-30 Mbps)

and the share that have access to fast broadband (>30 Mbps). These thresholds of broadband speeds correspond to those of the European Commission (European Commission, 2010) and are used in almost all European countries.

Unlike other studies, which often use measures of "availability" (e.g., a dummy indicating whether there are at least some broadband connections), our measure of "coverage" allows us to take into account the share of the municipality that truly benefits from broadband provision. This is particularly relevant here, given that broadband availability is often limited in rural municipalities. A drawback of the data, however, is that it gives information only on fixed broadband networks, a common feature in the literature 12 [START_REF] Bertschek | The economic impacts of broadband internet: A survey[END_REF]. This limitation is unfortunate, given that considerable hope has been placed in wireless broadband, especially in rural areas, and that an increasing number of agents use only mobile broadband and Whitacre, 2019). The lack of data on mobile broadband could underestimate broadband benefits for rural areas.

F o r P e e r R e v i e w (Manlove
Figure 2 displays the evolution of municipal broadband coverage between 2013 and 2017. The share of premises with access to at least 3 Mbps has increased over the period, from 59% to 69%, and has accelerated since 2015. Turning to the different speed levels, basic broadband coverage has slightly decreased (from 51% to 45%), whereas fast broadband coverage has increased (from 8% to 24%). This outcome is a direct consequence of the French Very High-Speed Broadband Plan, whose objective is to generalize access to fast broadband.

Thus, the plan has produced both a provision of fast broadband to unserved areas as well as a replacement of first-generation broadband networks with next-generation technologies in already covered areas.

Figures 3,4 and 5 show the evolution of broadband coverage across areas. As expected, broadband coverage varies across areas, with urban centers benefiting from better coverage than periurban areas, which in turn have more coverage than urban-influenced and isolated rural areas (Figure 3). The spatial digital divide has, however, decreased over time, with the difference between the most and the least covered areas decreasing from 35 to 25 percentage points. The reduction in the digital divide arises from the faster broadband provision in rural areas compared to urban centers. However, while access to at least 3 Mbps is quite stable over time in urban centers (Figure 3), these areas have benefited from a sustained increase in fast broadband over the period (Figure 4). Thus, in these already well-covered areas, broadband provision has consisted mainly of replacing basic broadband networks with next-generation technologies. Finally, there is a spatial digital divide in terms of both basic and fast broadband, with the gap being slightly more pronounced in terms of fast broadband (Figures 4 and5).

While urban-rural differences have slightly decreased over time for both speed levels, they remained quite important in 2017 (16 percentage points for basic broadband and 20 for fast broadband).

[ Classification NAF rev. 2), which is available for all nonagricultural firms. We consider establishment births instead of the total number of existing establishments for two reasons.

First, the creation of establishments is expected to suffer less from reverse causality (Mc Coy et al., 2018). Second, as broadband is a recent phenomenon, its effects are better identified using a sample of recently created establishments, which might have chosen their location because of broadband access. In addition, we choose to focus on establishments, not firms, to study the location choices of production units, whether or not they are decision-making units.

Based on the standardized European concept, creation of establishments includes three cases: (i) "ex nihilo creations", (ii) reactivations (after a break of more than one year), and (iii) take overs (with a change in at least two of the three following components: the legal decisionmaking unit, economic activity and/or location). The latter category, which, it can be argued, are not really births, allows capturing the potential effect of broadband on the relocation of existing establishments.

We carry out econometric estimations for all establishments and separately for the following six industries: manufacturing13 , construction, wholesale trade, retail trade, food and accommodation (a proxy for tourism), and high-order services. In some models, the latter are further disaggregated into three categories: creative industries; finance, insurance and real estate (FIRE); and other knowledge-intensive business services (other KIBS). The codes and descriptions of the industries are given in Table A.1 in the appendix. These industries account for almost all economic activities, with the exception of agriculture, transport, public administration, education, human health and social work activities. Table A.2 in the appendix provides descriptive statistics on establishment births by area and industry. As expected, births are highly concentrated in urban areas, especially in the largest urban centers and for high-order services.

In addition to broadband and establishment data, we use variables to characterize the socioeconomic conditions in each municipality. Specifically, we use annual data on the total number of jobs, total population, percentage of the population aged over 60, and percentage of individuals who have a university degree. In addition to these variables, we also control for annual travel time to the nearest railway station and to the nearest municipality with at least 20,000 inhabitants. Dummies are also introduced to control for the type of area (larger urban centers, small and middle urban centers, etc.) and for the 22 regions (corresponding to the NUTS 2 level). Regional dummies allow us to control for time-invariant unobserved regional factors, such as local economic policies. Finally, we introduce three spatially lagged independent variables: the number of jobs, the number of inhabitants, and the number of university graduates in municipalities that share a common border. Overall, the total set of control variables allows controlling for market opportunities, labor market conditions and population structure, as advised by Duvivier's (2019) meta-analysis of broadband and firm location. Table 1 provides a description of the variables.

[Table 1]

Results

Baseline results

Table 2 shows the estimation results for the baseline model, in which the broadband effect is assumed to be homogeneous across areas. Four equations are estimated, depending on the model used (pooling or random effects) and the lag between the dependent and independent variables (one or two years). The explanatory power of the models is satisfactory, with a pseudo-R² of 0.35 for the pooled regressions. The over-dispersion parameter (α) is statistically significant, indicating that the negative binomial model fits the data better than the Poisson model.

Overall, the control variables have the expected sign. Establishment births are more numerous in municipalities with more educated residents and higher employment and population levels. Births are also influenced by the characteristics of neighboring municipalities, which confirms the relevance of estimating an SLX model. Specifically, proximity to more populated and educated municipalities tends to favor births, probably due to better market access and ease of access to an educated labor force. In contrast, being close to municipalities with high employment levels has a negative impact, perhaps because of the spatial competition between neighboring municipalities in terms of firm location. More surprisingly, none of the two accessibility variables displays a consistent effect, and the share of seniors in the population is positively associated with establishment births. The results by industry (Table A.7. in the appendix) help illuminate this last result: an older population is Turning to the broadband variable, the estimated coefficient is significantly positive and similar for all four equations. The incidence rate ratio 14 of broadband is equal to approximately 1.03, i.e., an increase of 1% of broadband coverage raises the rate of establishments births by 1.03. The evidence of a positive effect of broadband on establishment births is in line with most previous studies [START_REF] Audretsch | Infrastructure and entrepreneurship[END_REF][START_REF] Lapointe | Does speed matter? The employment impact of increasing access to fiber Internet[END_REF][START_REF] Mccoy | The impact of broadband and other infrastructure on the location of new business establishments[END_REF][START_REF] Parajuli | Revisiting broadband and new firm dynamics[END_REF][START_REF] Prieger | The Importance of Transportation, Broadband, and Intellectual Infrastructure for Entrepreneurship[END_REF].

[Table 2]

[Table 3]

Table 3 shows that the effect of broadband availability varies greatly across areas (complete results reported in Table A.3 in the appendix).

First, while higher coverage leads to significantly more establishment births in both urban and periurban areas, we find no robust relation between broadband availability and establishment creation in rural areas. Alternatively, classifying municipalities according to density confirms that broadband access has little effect in the least densely populated areas (Table A.4. in the appendix). This result is in line with the (scant) literature that compare the effects of broadband between urban and rural areas, and concludes that broadband availability is more beneficial for urban areas [START_REF] Conley | Does Broadband Matter for Rural Entrepreneurs and Creative Class Employees?[END_REF][START_REF] Duvivier | Broadband and Firm Location: Some Answers to Relevant Policy and Research Issues using Meta-analysis[END_REF].

Second, we find significantly higher coefficients for middle and small urban centers compared to larger urban centers and periurban areas (see Wald tests in Table A.5). Thus, broadband effects vary not only between urban and rural areas but also along the whole urbanrural gradient. These results are consistent with [START_REF] Mack | Variations in the Broadband-Business Connection across the Urban Hierarchy[END_REF], who finds that intermediate areas are the main beneficiaries of broadband.

Before turning to industry-level results, we proceed to the falsification tests to check that our findings are not driven by omitted variables. Recall that the test only allows us to verify that significant coefficients do not capture a spurious correlation. As such, we carry out these tests to check the sensitivity of the broadband availability coefficients for all areas, larger urban centers, small and medium urban centers, and periurban areas but not for rural areas. As the calculations are very long (the tests require estimating each model 999 times), falsification tests 14 The incidence rate ratio is equal to the exponent of the coefficient. are performed only for our preferred specification, namely, random effects with one year-lagged broadband variable 15 . Table 4 presents the results. The broadband coefficients estimated in our baseline models are reported in Column (1). Column (2) reports the 95% confidence interval of the distribution of the 999 "permuted" coefficients. As shown in the table, in each of the four cases, the estimated coefficient based on actual data belongs to the top 2.5% of the distribution, indicating that unobserved heterogeneity does not drive our results.

As the results are robust across the different models, the following results are estimated with a random effects model with independent variables lagged by one year.

[Table 4]

Effects across industries

Table 5 reports broadband estimates by industry, assuming homogeneous broadband effects across areas (complete results in Table A.6 in the appendix). Most of our results confirm previous findings. Broadband has a significantly positive impact in most industries, with the highest effects for services consistent with [START_REF] Audretsch | Infrastructure and entrepreneurship[END_REF] and [START_REF] Shideler | Broadband impact on small business growth in Kentucky[END_REF].

Moreover, broadband does not appear to have a stronger impact on high-order services than on other services. There are at least two possible reasons. First, establishments in these technologyintensive activities are likely to be sensitive to fast broadband, and thus, the threshold used here (>3 Mbps) might not be high enough to act as a relevant factor in their location. Second, highorder services include various activities, which could be impacted differently by broadband access [START_REF] Duvivier | Broadband and Firm Location: Some Answers to Relevant Policy and Research Issues using Meta-analysis[END_REF].

We also find a significant effect on construction, similar to [START_REF] Hasbi | Impact of very high-speed broadband on company creation and entrepreneurship: Empirical Evidence[END_REF] and [START_REF] Parajuli | Revisiting broadband and new firm dynamics[END_REF]. Note that in addition to these short-run effects (broadband provision induces substantial infrastructure work), in the longer run, broadband access may also affect household location [START_REF] Deller | Broadband's relationship to rural housing values[END_REF] and thus the construction of new homes.

However, our estimates suggest that higher broadband coverage actually leads to significantly lower establishment births in manufacturing. Although some studies highlight that broadband has low, or even insignificant, effects on establishment births in manufacturing [START_REF] Kim | Broadband internet and new firm location decisions in rural areas[END_REF][START_REF] Mack | Industry variations in the broadband business nexus[END_REF], no study to our knowledge has found evidence of 15 This model allows both controlling for individual effects and keeping the highest number of observations. negative effects. A first possible explanation is that broadband fosters establishment births in higher-paying information-based industries, resulting in a crowding-out of manufacturing. The positive effect of broadband on high-order services (Column 6) provides support for this mechanism. Another likely explanation is that higher broadband coverage leads to stronger competition from online businesses, which may adversely affect establishments that serve the local market. While this kind of negative effect has only been highlighted to date for retail trade and FIRE (see Section 2), it can also apply to manufacturing, where almost 90% of firms sell goods on the local or regional market in France (compared to 94% for trade and 87% for finance and insurance) 16 . We expect this effect to apply mainly to rural areas, where small establishments cannot compete effectively with larger and more diversified online rivals. The following table validates this interpretation.

[Table 5] Table 6 presents the results for the six industries, assuming heterogeneous broadband effects across areas (complete results in Table A.7). First, the positive impact estimated for urban areas (see Table 3) arises from the fact that broadband significantly stimulates establishment births in services: retail trade, high-order services (only for middle and small centers), and food and accommodation. Note that larger centers are the only class for which broadband has no significant effect on high-order services, likely because what matters for these activities, in larger centers, is accessing fast broadband. This issue will be further investigated in the next section.

Second, broadband coverage tends to foster quite different industries in periurban areas, where there is a positive effect (although significant only at the 10% level) for construction and wholesale trade. Thus, it seems that broadband allows land-intensive establishments to relocate to periurban areas, where land prices are lower and may still benefit from easy access to larger centers. In addition, broadband also appears to favor the creation of high-order services in periurban areas.

Turning to rural areas, although we estimated that broadband effects were insignificant for both remote and urban-influenced rural areas (Table 3), the sectoral analysis brings out different patterns. On the one hand, few industries are impacted in urban-influenced areas, with 16 See the 2016 Community Innovation Survey (http://insee.fr/fr/statistiques/3597633?sommaire=3597637).

Page 17 of 33 Papers in Regional Science Papers in Regional Science broadband only significantly fostering high-order services. On the other hand, remote areas are differentially impacted, with some sectors positively affected and others negatively, which explains the global none-significant effect estimated in Table 3. More specifically, we find a negative effect on wholesale trade and, most of all, on manufacturing. The fact that broadband access negatively affects manufacturing in remote rural areas supports our previous explanation that local producers face increased competition from online sellers. However, the negative coefficient associated with wholesale trade suggests an additional explanation for manufacturing. By negatively affecting local wholesalers, broadband can lead to a loss of customers for local manufacturers, a non-negligible effect given that wholesaling and manufacturing are often closely linked in rural areas (food-processing industry) and that the food-processing industry is often one of the mainstays of local manufacturing.

In contrast, broadband has a positive effect in retail trade, tourism, and high-order services in remote areas. The positive impact of broadband availability on retail trade and tourist-based establishments in rural areas is in line with previous findings (Duvivier et al., 2018;[START_REF] Kandilov | Infrastructure investment and rural economic development: an evaluation of USDA's broadband loan program[END_REF].

Finally, the effect of broadband access on high-order services across areas is interesting.

As broadband has a positive impact in almost every area outside larger centers, this suggests that broadband provision may favor the dispersion of these highly concentrated activities, especially in areas offering a good quality of life [START_REF] Malecki | Digital development in rural areas: potentials and pitfalls[END_REF].

[Table 6]

Effects according to speed level

We further test whether broadband effects vary according to speed level by distinguishing between basic and fast broadband. Table 7 displays the results (complete results in Table A .8). Overall, there appears to be no great difference between the impact of basic and fast broadband. There are even some sectors (construction, food and accommodation) for which basic broadband has a higher impact. The only sector for which access to high-speed broadband has a significantly higher impact are high-order services and, more precisely, other knowledge-

F o r P e e r R e v i e w
intensive business services (which includes the software development sector), which use rather sophisticated broadband applications. 17 This paper examines the effect of the Internet on establishment births across locations, industries and speed levels. The empirical analysis is carried out for French municipalities over a period of significant broadband growth using count data models.

Considering overall establishment births, we find that broadband has a positive effect in larger urban centers, small and medium urban centers, and periurban areas but has no significant impact in rural areas (whether urban-influenced or isolated). In addition, industry-level results reveal that, in non-central areas, broadband can foster establishment births in basic (retail, tourism) but also in some knowledge-intensive industries (creative industry).

However, broadband impact on knowledge-intensive activities in non-central areas should not be overestimated. Mapping results suggest that broadband overwhelmingly stimulates creative activities in rural locations with favorable fundamentals, especially as regards natural amenities. Moreover, broadband has no significant impact on other knowledgeintensive activities (FIRE, other KIBS) in non-central areas.

Finally, there appears to be no great difference between the impact of basic and highspeed broadband connections, suggesting that basic broadband (3-30 Mbps) is sufficient in most cases. There are, however, two exceptions. First, fast broadband has a significantly stronger effect in larger urban centers with, we may assume, the necessary skilled workforce able to use sophisticated digital applications. Second, fast broadband shows a positive link with creative industries in rural areas. This points to the role of high-speed connection for attracting creative activities in areas with good quality of life.

Overall, the results suggest that while the digital revolution is unlikely to lead to major changes in the spatial distribution of economic activity, it can favor dispersion in some places (small and mi-sized centers, periurban areas, rural areas with good quality of life) and some industries (retail, tourism, creative businesses).

  test whether impacts vary according to speed level by comparing the effect of basic (3-30 Mbps) and fast broadband (>30 Mbps) provision.

Following-

  [START_REF] Détang-Dessendre | La population des villes et des campagnes : des mobilités qui comblent les disparités historiques ? Campagnes contemporaines[END_REF], we classify municipalities into five classes based on the 2010 division of urban areas: Larger urban centers (>10,000 jobs), -Periurban areas (municipalities with at least 40% of their residents working in neighboring larger urban centers),

  establishment births, we use annual data on the number of firms and establishments created (INSEE, REE/Sirene), disaggregated by industry (Aggregated

  retail trade and food and accommodation, most likely because seniors are important customers for consumer-related industries.

  Figure 1. Classification of Municipalities

Table 8

 8 presents broadband effects disaggregated by speed level and type of areas(complete results in Table A.10). When considering all industries (Column 1), faster speed levels matter more for areas that are higher up in the urban hierarchy. Indeed, in larger centers, only fast broadband has a significant impact, whereas in periurban areas only access to basic broadband matters. Small and medium centers are in an intermediate position, as both basic and fast broadband matter. This result show that high-speed connections are most likely to foster establishment births in locations with the necessary skilled workforce able to use and take advantage of advanced broadband. Wald tests of equality between coefficients reported in Table A.9.

	Page 19 of 33	Papers in Regional Science
	Interestingly, high-speed connection also shows a positive (although weak) link with
	establishment births in creative industry in rural areas, suggesting that attracting creators to
	these locations requires fast broadband provision. In addition, mapping rural municipalities
	with the highest number of births in creative industry points to the role of natural amenities
	(Figures A.1 and A.2 in the appendix). Indeed, new creators overwhelmingly locate in rural
	communities with adequate broadband services provided they have a good access to natural
	amenities (coastal, mountainous and wildest areas). On the contrary, rural municipalities with
	high-speed connections in northeastern France, with an industrial history and a less pleasant
	climate, does not appear to attract creators. Thus, while high-speed broadband can stimulate
	growth in knowledge-intensive activities in non-central locations, it is not expected to alter
	existing trends (in particular, the quest for natural amenities). In addition, broadband does not
	foster the dispersion of other high-order services (FIRE and other KIBS) to rural locations.
		[Table 7]
		[Table 8]
	6. Conclusion
		Papers in Regional Science

17

Table 2 .

 2 Homogeneous Effects across Areas -All industries

		(1)	(2)	(3)	(4)
		Pooling (.l)	Random Effects (.l)	Pooling (.2l)	Random Effects (.2l)
	BB	0.036 ***	0.026 ***	0.036 ***	0.032 ***
		(0.005)	(0.006)	(0.006)	(0.007)
	Employment	0.025 ***	0.021 ***	0.022 **	0.013
		(0.007)	(0.008)	(0.008)	(0.009)
	Employment_sq	0.014 ***	0.013 ***	0.014 ***	0.014 ***
		(0.001)	(0.001)	(0.001)	(0.001)
	Population	0.923 ***	0.916 ***	0.937 ***	0.952 ***
		(0.018)	(0.021)	(0.022)	(0.024)
	Population_sq	-0.008 ***	-0.007 ***	-0.009 ***	-0.010 ***
		(0.001)	(0.002)	(0.002)	(0.002)
	Seniors	0.370 ***	0.244 ***	0.369 ***	0.306 ***
		(0.029)	(0.032)	(0.034)	(0.035)
	University	1.326 ***	1.164 ***	1.379 ***	1.240 ***
		(0.035)	(0.041)	(0.042)	(0.047)
	Time_20,000+	0.007 **	0.009 **	0.003	-0.002
		(0.003)	(0.003)	(0.003)	(0.004)
	Time_railway	0.005 ***	-0.005 ***	0.004 **	-0.003
		(0.002)	(0.002)	(0.002)	(0.002)
	WPopulation	0.002 ***	-0.003 ***	0.003 ***	0.001 **
		(0.000)	(0.000)	(0.001)	(0.001)
	WEmployment	-0.000 ***	0.000 ***	-0.000 ***	-0.000 *
		(0.000)	(0.000)	(0.000)	(0.000)
	WUniversity	0.459 ***	0.810 ***	0.512 ***	0.772 ***
		(0.045)	(0.057)	(0.054)	(0.063)
	LargerCenters	-0.085 ***	-0.074 ***	-0.087 ***	-0.084 ***
		(0.008)	(0.010)	(0.009)	(0.011)
	SmallMiddleCenters	-0.078 ***	-0.080 ***	-0.084 ***	-0.085 ***
		(0.009)	(0.011)	(0.010)	(0.011)
	Periurban	-0.076 ***	-0.084 ***	-0.079 ***	-0.084 ***
		(0.007)	(0.008)	(0.008)	(0.008)
	UrbanInfluencedRural	-0.091 ***	-0.092 ***	-0.093 ***	-0.094 ***
		(0.007)	(0.008)	(0.008)	(0.008)
	Constant	-4.908 ***	-2.941 ***	-4.959 ***	-3.080 ***
		(0.052)	(0.069)	(0.060)	(0.077)
	Regional dummies	Yes	Yes	Yes	Yes
	Year dummies	Yes	Yes	Yes	Yes
	lnalpha	-2.710 ***		-2.670 ***
		(0.018)		(0.021)
	ln_r		4.904 ***		4.877 ***
			(0.029)		(0.033)
	ln_s		2.998 ***		2.969 ***
			(0.018)		(0.020)
	Observations	139,064	139,064	104,298	104,298
	Pseudo R 2	0.347		0.346
	AIC	591,432.17	577,076.55	442,781.81	433,294.02
	BIC	591,845.56	577,499.79	443,173.56	433,695.33
	Note: standard errors in parentheses. * p<0.1, ** p<0.05, *** p<0.01. Columns (1) and (2): broadband variable lagged by one year.
	Columns (3) and (4): broadband variable lagged by two years.

Table 3 .

 3 Heterogeneous Effects across Areas -All industries

		(1)	(2)	(3)	(4)
		Pooling (.l)	Random Effects(.l)	Pooling(.2l)	Random Effects(.2l)
	BB_LargerCenters	0.049 ***	0.068 ***	0.041 **	0.048 **
		(0.014)	(0.019)	(0.016)	(0.021)
	BB_SmallMiddleCenters	0.149 ***	0.122 ***	0.146 ***	0.122 ***
		(0.031)	(0.038)	(0.036)	(0.041)
	BB_Periurban	0.030 ***	0.020 **	0.033 ***	0.029 ***
		(0.007)	(0.009)	(0.008)	(0.009)
	BB_UrbanInfluencedRural	0.031 ***	0.019	0.027 **	0.021
		(0.011)	(0.013)	(0.013)	(0.015)
	BB_Isolated	0.033 **	0.013	0.038 **	0.031 *
		(0.013)	(0.014)	(0.015)	(0.016)
	Observations	139,064	139,064	104,298	104,298
	Pseudo R 2	0.347		0.346
	Note: standard errors in parentheses. * p<0.1, ** p<0.05, *** p<0.01. Columns (1) and (2): broadband variable lagged by one year.
	Columns (3) and (4): broadband variable lagged by two years.

Table 4 .

 4 Falsification Tests

		(1)	(2)
		"True" coefficient	95% Confidence Interval
	All areas	0.026	[-0.006; 0.006]
	Larger Urban Centers	0.068	[-0.011; 0.012]
	Small and Medium Urban Centers	0.122	[-0.016; 0.018]
	Periurban Areas	0.020	[-0.008; 0.007]
	Note: "Coefficient" refers to the coefficient estimated in the baseline model with
	random-effects and broadband lagged by one year (column (2) in tables 3 and 4

Table 5 .

 5 Homogeneous Effects across Areas -By industry Note: standard errors in parentheses. * p<0.1, ** p<0.05, *** p<0.01.

		(1)	(2)	(3)	(4)	(5)	(6)
		Manufacturing	Construction	Wholesale trade	Retail trade	Food-Accommodation	High-order services
	BB	-0.078 ***	0.027 **	0.006	0.073 ***	0.062 ***	0.041 ***
		(0.016)	(0.013)	(0.017)	(0.016)	(0.020)	(0.011)
	Observations	139,064	139,064	139,064	139,064	139,064	139,064

Table 6 .

 6 Heterogeneous Effects across Areas -By industry Note: standard errors in parentheses. * p<0.1, ** p<0.05, *** p<0.01.

		(1)	(2)	(3)	(4)	(5)	(6)
		Manufacturing	Construction	Wholesale Trade	Retail Trade	Food-Accommodation	High-order services
	BB_LargerCenters	0.015	-0.001	-0.006	0.150 ***	0.157 ***	0.040
		(0.051)	(0.035)	(0.041)	(0.041)	(0.061)	(0.028)
	BB_SmallMiddleCenters	-0.086	0.058	0.067	0.345 ***	0.298 ***	0.158 **
		(0.093)	(0.073)	(0.095)	(0.084)	(0.112)	(0.064)
	BB_Periurban	-0.042 *	0.030 *	0.039 *	0.025	0.021	0.030 **
		(0.023)	(0.017)	(0.023)	(0.021)	(0.030)	(0.015)
	BB_UrbanInfluencedRural	-0.038	0.020	-0.029	0.038	0.045	0.051 **
		(0.032)	(0.027)	(0.038)	(0.033)	(0.041)	(0.026)
	BB_Isolated	-0.240 ***	0.046	-0.090 **	0.154 ***	0.079 **	0.054 *
		(0.033)	(0.032)	(0.046)	(0.036)	(0.038)	(0.029)
	Observations	139,064	139,064	139,064	139,064	139,064	139,064
				Papers in Regional Science

Table 7 .

 7 Effects by Speed Level -Homogeneous across Areas Note: standard errors in parentheses. * p<0.1, ** p<0.05, *** p<0.01.

		(1)	(2)	(3)	(4)		(5)
		All Sectors	Manufacturing	Construction	Wholesale Trade	Retail Trade
	BasicBB	0.026 ***	-0.080 ***	0.040 ***	0.009	0.079 ***
		(0.007)	(0.017)	(0.013)	(0.018)	(0.016)
	FastBB	0.026 ***	-0.070 ***	-0.001	0.001	0.062 ***
	Observations	139,064	139,064	139,064	139,064	139,064
	Table 7. (Continued)
		(6)	(7)	(8)		(9)	(10)
		Food-Accommodation High-order Services Creative Industries	FIRE	Other KIBS
	BasicBB	0.072 ***	0.034 ***	0.041 *		0.044 **	0.030 *
		(0.021)	(0.012)	(0.023)		(0.022)	(0.015)
	FastBB	0.038	0.053 ***	0.066 ***		0.018	0.063 ***
		(0.025)	(0.013)	(0.024)		(0.024)	(0.017)
	Observations	139,064	139,064	139,064	139,064	139,064

Table 8 .

 8 Effects by Speed Level -Heterogeneous Effects across Areas

		(1)	(2)	(3)	(4)	(5)
		All Sectors	Manufacturing	Construction	Wholesale Trade	Retail Trade
	BasicBB_LargerCenters	0.028	0.035	0.019	0.001	0.165 ***
		(0.021)	(0.055)	(0.038)	(0.045)	(0.045)
	FastBB_LargerCenters	0.075 ***	0.007	-0.014	-0.009	0.142 ***
		(0.019)	(0.052)	(0.036)	(0.042)	(0.041)
	BasicBB_SmallMiddleCenters	0.140 ***	-0.133	0.126	0.200 *	0.324 ***
		(0.042)	(0.104)	(0.080)	(0.106)	(0.092)
	FastBB_SmallMiddleCenters	0.104 **	-0.048	-0.011	-0.033	0.355 ***
		(0.041)	(0.101)	(0.079)	(0.102)	(0.089)
	BasicBB_Periurban	0.032 ***	-0.045 *	0.046 **	0.030	0.043 *
		(0.009)	(0.025)	(0.018)	(0.025)	(0.023)
	FastBB_Periurban	-0.001	-0.036	-0.004	0.048 *	-0.006
		(0.011)	(0.030)	(0.022)	(0.028)	(0.027)
	BasicBB_UrbanInfluencedRural	0.019	-0.069 **	0.030	-0.028	0.035
		(0.014)	(0.035)	(0.029)	(0.042)	(0.035)
	FastBB_UrbanInfluencedRural	0.016	0.050	-0.018	-0.035	0.040
		(0.020)	(0.051)	(0.042)	(0.057)	(0.049)
	BasicBB_Isolated	0.016	-0.213 ***	0.031	-0.077	0.140 ***
		(0.015)	(0.035)	(0.034)	(0.050)	(0.038)
	FastBB_Isolated	-0.002	-0.315 ***	0.074	-0.123 *	0.181 ***
		(0.021)	(0.054)	(0.048)	(0.066)	(0.050)
	Observations	139,064	139,064	139,064	139,064	139,064

Table 8

 8 Note: standard errors in parentheses. * p<0.1, ** p<0.05, *** p<0.01.

	. (Continued)
		(6)	(7)	(8)	(9)	(10)
		Food-	High-order	HOS: Creative	HOS: FIRE	HOS: Other KIBS
		Accommodation	Services (HOS)	Industries
	BasicBB_LargerCenters	0.136 **	0.008	0.009	0.023	0.003
		(0.066)	(0.031)	(0.051)	(0.052)	(0.036)
	FastBB_LargerCenters	0.157 **	0.051 *	0.046	-0.045	0.081 **
		(0.061)	(0.028)	(0.047)	(0.049)	(0.033)
	BasicBB_SmallMiddleCenters	0.285 **	0.142 **	0.340 **	0.094	0.095
		(0.123)	(0.071)	(0.135)	(0.120)	(0.090)
	FastBB_SmallMiddleCenters	0.295 **	0.173 **	0.357 ***	0.089	0.116
		(0.118)	(0.068)	(0.128)	(0.113)	(0.086)
	BasicBB_Periurban	0.066 **	0.034 **	0.043	0.030	0.035 *
		(0.032)	(0.016)	(0.031)	(0.030)	(0.021)
	FastBB_Periurban	-0.059	0.025	0.026	0.035	0.023
		(0.038)	(0.018)	(0.035)	(0.033)	(0.023)
	BasicBB_UrbanInfluencedRural	0.028	0.043	0.061	0.044	0.046
		(0.044)	(0.028)	(0.056)	(0.053)	(0.038)
	FastBB_UrbanInfluencedRural	0.074	0.071 *	0.130 *	0.094	0.052
		(0.061)	(0.038)	(0.075)	(0.069)	(0.051)
	BasicBB_Isolated	0.088 **	0.044	-0.000	0.079	0.054
		(0.040)	(0.032)	(0.063)	(0.059)	(0.043)
	FastBB_Isolated	0.031	0.077 *	0.152 *	0.101	0.053
		(0.056)	(0.042)	(0.082)	(0.074)	(0.057)
	Observations	139,064	139,064	139,064	139,064	139,064

The plan was adopted in 2010, with the objective of covering 100% of homes by 2022. Since 2013, two complementary networks have been deployed. Private operators provide optical fiber in densely populated municipalities (approximately

municipalities). In less densely populated areas, infrastructure is constructed by public authorities.

In addition, even if tourist services are not deliverable online, broadband provision can increase entrepreneurial opportunities for this sector by allowing tourist operators to gain visibility and facilitating distant reservations(Duvivier et al., 2018).

See TableA.1 in the appendix for a definition of creative industries.

The proportion of municipalities with zero creation varies between 18% and 75%, depending on the industry and year.

We do not include municipal fixed-effects because in count data models, areas with no establishment creation over the period are dropped from the analysis. See below.

Papers in Regional Science Papers in Regional Science

In our case, estimating a fixed effects count data model leads to the removal of between 3% and 49% of the observations, depending on the industrial sector.

The "municipal density classification", which is the other common classification, distinguishes between four types of municipalities based on their population density but does not take into account urban influence. To check the robustness of results, this other classification will also be used; see Section 5.

Broader-based definitions are also commonly used. For example, the OECD definition of functional urban areas distinguishes between urban cores, their surrounding areas and peripheral places. The "2010 division into urban areas" proposes a more disaggregated classification, distinguishing between three types of peripheral areas (small and medium cities, urban-influenced rural areas, and remote rural areas).

In a previous version of the study, we further distinguished between low-tech and high-tech manufacturing but no differences were found between the two.

We obtained data on mobile broadband coverage (3G and 4G) from the French Electronic Communications, Postal and Print media distribution Regulatory Authority (Arcep). However, the data, delivered by private operators largely overestimates real coverage, especially in rural areas. As a result, we choose to not control for mobile broadband.


Ph Evon

D Colas

P Y Pontalier

L Rigal

The twin-screw extrusion technology, an original solution for the extraction of proteins from sunflower and alfalfa

Keywords: Twin-screw extrusion, Protein extraction, Sunflower, Alfalfa

Twin-screw extrusion has been used for the protein extraction from sunflower and alfalfa. Thermo-mechanical fractionation and aqueous extraction are conducted simultaneously to collect separately a liquid extract and a solid raffinate.

From sunflower whole plant, squeezing in the reversed screws is favored by the fibers abundance in the stalk, and it enables L/S separation. Protein yield is 44%, in the best conditions, and lipids are partly co-extracted. Water-soluble proteins are in an aqueous extract and in two O/W emulsions due to their surface-active properties. Hence, the oil is coextracted in the form of emulsions stabilized by proteins at interface.

Proteins can be collected in the aqueous extract by isoelectric precipitation. Emulsions are usable for oil production. Their demulsification with ethanol produces a precipitate rich in proteins with low denaturation level.

From alfalfa whole plant, the highest protein yield in the aqueous extract (called green juice) is 25% when water is added in the extruder. Water-soluble and water-insoluble green juice proteins can be fractionated thanks to L/L extraction in sunflower oil and ammonium sulfate precipitation.

Some other molecules are co-extracted (polysaccharides, phenolic compounds). They can be purified with ultrafiltration or chromatography. ).' :

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