Nicholas Attwood
email: nicholas.attwood@imt-atlantique.fr

Franc ¸ois Gallee

Patrice Pajusco
email: patrice.pajusco]@imt-atlantique.fr

Marion Berbineau
email: marion.berbineau@univ-eiffel.fr

Experimental mmWave channel sounding in the 60 GHz band in railway environments

Keywords: channel sounder, mmWave, antennas, propagation, measurements, railways

Railways are facing an ever increasing needs for safe and secure wireless communications with the generalisation of automatic and driverless trains. In this context, frequency scarcity is a real bottleneck. To overcome this blockage, opportunities offered by mmW frequency bands are explored. Due to the specificity of environments, researches conducted for general 5G and beyond deployments can not be transposed easily. Channel sounding in the mmW bands in real railways environments should be conducted. In this context, this paper presents preliminary experimental results in a railway environment with a relative low cost and reconfigurable channel sounder operating at 60 GHz.

I. INTRODUCTION

Trains are entering the era or full automation in order to increase capacity, reliability and quality of service. To this ends, the needs for safe and secure wireless communications systems is increasing drastically. A new communication system called Future Railway Mobile Communication System (FRMCS) is under development. It will be based on 5G New Radio (NR) standard. In this context, it should cope with spectrum scarcity for Railway applications. This has motivated the exploration of the millimeter-wave (mmWave) frequencies. Developments for high data rate and very low latency are very active between 24 GHz and 100 GHz [START_REF] Shafi | 5g: A tutorial overview of standards, trials, challenges, deployment, and practice[END_REF], [START_REF] Shah | 5g for vehicular communications[END_REF]. These bands can answer the needs for high-speed, high data rate and ultra low latency mobile applications and other railway safety applications such as Train-to-Infrastructure (T2I), Trainto-Train (T2T) and intra Train identified in [START_REF] Mottier | How rail transport could benefit from 5g[END_REF]. Among these applications we can mention high demanding ones such as virtual coupling of trains (platoons of trains) from different manufacturers based on T2T wireless communications [START_REF] Goikoetxea | Roadmap towards the wireless virtual coupling of trains[END_REF]. These wireless links should experience very low probability of failure, high data rate, sometimes ultra low latency in the context of important communication range constraints due to specific propagation conditions in the mmWave band in typical railways environments well known to be harsh with multiple scatters and reflectors due to tracks, pylons, ballast, trains stopped or in movement.

Characterization and modelling of Railway radio channel in the mmWave frequency bands are needed for the development and analysis of Train to everything (T2X) communication systems in this band. This are the main goals of the mmW4Rail project supported by the French national research agency.

It involves the definition of new channel models based on measurements in railway environments in the 60 GHz band and performance evaluation in these channels. In this paper, we will present a new channel sounder operating in the mmWave bands able to perform dynamic measurements and the results obtained during a first measurement campaign in a typical Railway environment in France. The paper is organized as follows. Section II highlights the related works concerning measurements in Railway environments in the mmWave band and the existing channel sounders. Section III details the channel sounder developed and the validation stage. Section IV presents the measurements scenarios. Section V describes and analyses the measurements results. Conclusion and perspectives are then proposed in Section VI.

II. RELATED WORK ON CHANNEL CHARACTERIZATION IN MMWAVE BANDS

Channel characterization and modelling in the mmWave bands is a very active field of research in the context of developments for 5G and beyond. Nevertheless, only few of these works focus on railway domain. Stationary MIMO (Multiple Input Multiple Output) propagation measurements at mmWave in underground mine with a VNA (Vector Network Analyser) are presented in [START_REF] Ghaddar | Mm-waves propagation measurements in underground mine using directional MIMO antennas[END_REF]. Influence of railway environment on antenna performances at mmWave frequencies is analysed in [START_REF] Seetharamdoo | Influence of railway environment on antenna performances at mm-wave frequencies[END_REF]. Static measurements with regional trains for T2T communications are reported in [START_REF] Yang | Propagation measurements with regional train at 60 GHz for virtual coupling application[END_REF]. Dynamic measurements at 60 GHz using a channel sounder based on a classical RUSK sounder and mmWave front-end are reported in [START_REF] Soliman | Design and Evaluation of a Millimeter Wave Channel Sounder for Dynamic Propagation Measurements[END_REF]. The results highlight two mains contributions: the LOS (Line Of Sight) component and a ray reflected on the ground. The impact of wagon vibration on the channel is evaluated in [START_REF] Soliman | Design and Evaluation of a Millimeter Wave Channel Sounder for Dynamic Propagation Measurements[END_REF]. Influence of typical railway objects in a mmWave propagation channel is analyzed in [START_REF] He | Influence of Typical Railway Objects in a mmWave Propagation Channel[END_REF] for T2I and intra train communications. Twelve of the most common railway materials are characterized experimentally and the corresponding electromagnetic parameters are obtained to calibrate a 3-D ray tracing (RT) simulator. Influence of atmospheric attenuation on the channel characteristics for high speed railway at the mmWave is discussed in [START_REF] Ma | Influence of Meteorological Attenuation on the Channel Characteristics for High-Speed Railway at the Millimeter-Wave Band[END_REF].

III. DESCRIPTION OF THE CHANNEL SOUNDER

This section presents the architecture of the SISO (Single Input Single Output) mmWave channel sounder developed in the framework of the mmWave project for measurements in the 60 GHz band in railway environments. First, existing channel sounders are presented. Then the hardware configuration, the software part and the calibration process are described.

A. Existing Channel sounders in the mmWave band

With, increasing complexity of wireless systems, more and more channel parameters are required to model correctly the radio channels. These parameters are extracted from the statistical variations of either the channel time-variant impulse response or its time-variant frequency response in SISO or MIMO configuration. Channel sounders can be differentiated according to the used waveform, the number of antennas, the operational frequency, the bandwidth related to time resolution and their capability to extract various channel properties. Mainly four types of excitation signals are considered in sounding techniques [START_REF] Salous | Radio Propagation Measurement and Channel Modelling[END_REF]: pulse waveform, pseudo random binary sequences, frequency chirp, OFDM (Orthogonal Frequency Division multiplexing) signals. A few number of mmWave channel sounders have been proposed in the literature due to the high component cost, the calibration difficulties and the complexity of the mmWave front-end RF to have a good sensitivity [START_REF] Maccartney | A flexible millimeter-wave channel sounder with absolute timing[END_REF]. In [START_REF] Ghaddar | Mm-waves propagation measurements in underground mine using directional MIMO antennas[END_REF] the authors considered a VNA. A wideband digital sweep 2x2 MIMO channel sounder at 60 GHz is presented in [START_REF] Salous | Wideband MIMO Channel Sounder for Radio Measurements in the 60 GHz Band[END_REF]. However, this sounder is not suitable for measurements in railway context. Recently, [START_REF] Soliman | Design and Evaluation of a Millimeter Wave Channel Sounder for Dynamic Propagation Measurements[END_REF] presents dynamic measurements at 60 GHz based on the RUSK channel sounder and mmWave front-end. The frontend up and down converters allow the channel sounder to operates with a center frequency between 55.2 and 70.2 GHz. This sounder is used in railway environments. An industrial mmWave channel sounder is developed by Keysight Technologies [START_REF] Keysight | 5G channel sounding, reference solution[END_REF]. The excitation signal is a wide-band signal correlation with switching antennas. In the sub 6 GHz band, several MIMO channel sounders based on Software Defined Radio boards have been developed. We can refer to some interesting examples to [START_REF] Maas | Channel sounding for the masses: Low complexity gnu 802.11b channel impulse response estimation[END_REF], [START_REF] Gahadza | Implementation of a channel sounder using gnu radio opensource sdr platform[END_REF], [START_REF] Pajusco | Massive antenna array for space-time channel sounding[END_REF]. Today, to our knowledge, there is no flexible and open source SDR based channel sounder operating in the 60 GHz band.

B. Channel sounder Hardware Configuration

The SISO channel sounder developed by IMT Atlantique in the framework of M5hestia and mmW4Rail projects is build upon components from Analog Device. This equipment is modular, relatively low cost and open source. The 60 GHz frequency band is obtained by using the RF front-end board HMC6300. It covers the frequency from 57 to 64 GHz with a maximum channel bandwidth of 500 MHz. The input and output signals are a differential baseband modulated signal. The modulated signal is generated by a Rohde & Schwarz SMBV100B. The output signal of the HMC6300 board is also a baseband signal received by the USRP X310 for a digital processing. For long distance, a power amplifier could be added and provide an output power of 25 dBm at 60 GHz.

On the transmitter side, a base-band chirp signal and a clock signal at 71.42857 MHz are generated. The clock frequency is chosen to allow a 250 MHz band. An USRP X310 allows to synchronize the signal generator with a GPS signal. The chirp signal is used for the measurements. A PC control all the process. On the receiver side, an other USRP X310 is used for synchronisation and signal processing. Figure 1 illustrates the transmitter and the receiver.

C. Channel sounder Software Configuration

The different components of the channel sounder are controlled with computers thanks to an ad'hoc open source software devoppped in Python language. The equation of the chirp signal c(t) is given by (1) where T is the duration of the chirp. Only one frequency is emitted. The signal corresponds to 6000 frequency samples. The sampling frequency is equal to 600 MHz. Consequently, the signal duration is equal to 10 µs that corresponds to the maximal time window for the measurements. The bandwidth is equal to 160 MHz, then the spatial resolution is equal to 6.25 ns. Table I recaps the main characteristics of the channel sounder.

c(t) = A exp i2π( δf 2T t-δf 2 )t if 0 ≤ t < T 0 else (1)

D. Channel sounder measurement principle

The channel sounder developed permits the measurement of the channel complex impulse responses (CIR) thanks to the transmitted chirp signal c(t), following equation [START_REF] Shah | 5g for vehicular communications[END_REF].

Y M easure (f ) =X(f )H T X (f )H RX (f ) × G T X (f )H P rop (f )G RX (f ) H (2)
where H T X and H RX are respectively the complex channel transfer functions (CTF) at transmitter and receiver side, G T X and G RX are the transmitter and receiver antenna gain respectively, H is the transmission transfer function and H P rop the propagation transfer function. X and Y M easure are the emitted and received signal spectra respectively.

E. Channel sounder calibration principle

The calibration can be done with a back-to-back measurement with a cable connecting the transmitter and receiver parts. An other solution in the mmWave band is to perform a measurement in open space with a sufficient distance between Tx and Rx to consider that the far field case is established. The measurements were done at 1 m. X Ref erence is given by equation ( 3).

X Ref erence (f ) = X(f )H T X (f )H RX (f ) (3)
where X Ref erence is the reference signal spectrum and X is the spectrum of the signal generated by the R&S SMJ equipment.

IV. MEASUREMENTS DESCRIPTION

A. Railway environment considered

A first measurements campaign was conducted at Centre d'Essais Ferroviaire (C.E.F) near Valenciennes in France. This trial center is dedicated to rolling stock performance testing. Several railway lines can be used depending on the on-going tests. We had access to a specific track named VES2 as illustrated on figure 2. The other tracks were occupied by other trains corresponding to a station scenario. The communication system was installed in P1 at the end of the platform. The acquisition were performed from S 1 to S 9 as shown on figure 2.

B. Measurements scenarios description

The channel sounder transmitting part, Tx, was installed on a small carriage able to travel on the tracks to perform dynamic measurements. A measurement consists of a set of 1 250 000 CIR recorded over 12 m. The carriage is pulled in order to avoid any masking effect between Tx and Rx. The receiving part, Rx, is fixed at 0.9 m height in P1. There is a train parked at 1 m far from P1 as shown in figure 3. Both Tx and Rx horn antennas offer a 5dBi gain and can be used in vertical or horizontal polarization. Tx and Rx are synchronized with GPS disciplined oscillators.

V. PRELIMINARY RESULTS

A. Post-Treatment description

In order to reduce the total number of CIR and to increase the signal to noise ratio, a first coherent average is performed in order to reduce the size of the file to be treated. At the end, the file contains one CIR every λ 10 associated with all the measurement parameters. The complex CTF is obtained with [START_REF] Ghaddar | Mm-waves propagation measurements in underground mine using directional MIMO antennas[END_REF]. Then the CIR are obtained with a inverse Fourier Transform considering a Hanning window as follows:

h(t, τ ) = T F -1 [H(f )W indow hanning ] (4)
H(f ) = Y M easure (f ) X Ref erence(f ) (5)
The Power Delay Profile (PDP) estimation is an average of the individual delay profiles defined as the power of the CIR at time t i following equation ( 6) [START_REF] Salous | Radio Propagation Measurement and Channel Modelling[END_REF]:

P DP (τ ) = 1 N N i=1 |h(τ, t i )| 2 (6)
where N is the number of CIR considered. A certain number of impulse responses are averaged in order to cope with the random character of the channel and to guarantee a stationary area if the average length is sufficiently long. This average reduce the noise peak as explain in [START_REF] Salous | Radio Propagation Measurement and Channel Modelling[END_REF]. A large number of N impulse responses ensure a noise smoothing. From the PDP, different parameters can be extracted as the first arrival delay, the maximal excess delay, the average delay, the RMS (Root Mean Square) delay spread and the associated coherence bandwidth. The PDP is obtained by a sliding average along the length of the measurement. The window size is 30λ and it is applied over 10λ. The Doppler spectrum is computed for fixed delays corresponding either to line-of-sight (LOS) component or multi paths. The Fourier transform is applied on the CIRs over a distance equal to 30λ. The process is repeated each 10λ up to the end of the measurement length.

Doppler i = T F [h iN +(1,...,N ) (δ τ )] (7)
where Doppler i is the i th delay Doppler and δ τ is all index that correspond to LOS or multipath component.

B. Measurements analysis

This section analyzes two measurement examples performed in horizontal polarization with 5 dBi gain antenna horn (both at TX and RX). The measurements performed between S8 and S9 then between S2 and S3 are presented (cf figure 2). The average gain over the whole bandwidth G wb is depicted in the figure 5. The fading is also visible and the average gain is close to the Friis attenuation. Examples of PDP are given in figure 6. The time spreading of the PDP is usually low (Red curve), but can increase in some locations (Black curve). The corresponding Doppler is represented in the 7. The Doppler shift of the main path is corrected according to the measurement configuration (direction and speed of the TX). However, it is interesting to notice that multipath comes from other direction and spreads the Doppler shape. A possible explanation could be reflected rays on the two trains stopped on each side of the measurement line (canyon effect). 2) Measurements between S2 ans S3: Another measurement between the section S2 and S3 is presented. The mean distance of this section is around 90m from the RX system. The average gain is depicted in the figure 8. Fast and slow fading is also observed. The PDP at two distance 85.8 m and 86 m are presented on the figure 9. Some path are clearely identifiable at 86 m but not at 85.8 m. According to the distance, the multipath environment changes very quickly. This could be explained by the interaction with the environment at mmWave frequency. On the figure 10, the Doppler Shift is not spread. This means that the DOA (Direction of Arrival) of the reflected paths are closed to the LOS path.

VI. CONCLUSION SDR based channel sounder at 60 GHz has been

in open source by IMT Atlantique in the framework of the mmW4Rail project. The channel sounder considered uses USRP X310 and allows dynamic measurements at relative low-cost. A measurements campaign was performed at the Centre d'essais Ferroviaires in Valenciennes (France) in railway environments allowing us to characterise a tunnel effect between two trains stopped. We have presented preliminary resultat with the PDP and power loss along the path, the PDP and Doppler shift at specific position. This preliminary analysis has permitted to identify fading occured, despite the 60 GHz LOS condition.

Fig. 1 .

 1 Fig. 1. TX and RX modules of the IMT-Atlantique Channel Sounder

Fig. 2 .

 2 Fig. 2. Map of the C.E.F center.

Fig. 3 .

 3 Fig. 3. Environment of the measurements

1 )

 1 Measurements between S8 and S9: The first example was performed between S8 and S9 location. The PDP along the measurement path is plotted in figure4. The main path delay is shifted along the path due to the TX-RX distance change. Despite the LOS propagation condition, the main path presents fading. It means that several path exists and interferes in the path.

Fig. 4 .

 4 Fig. 4. Evolution of the main peak during the measurement between S8 and S9

Fig. 5 .Fig. 6 .Fig. 7 .

 567 Fig. 5. Evolution of G wb between S8 and S9.

Fig. 8 .Fig. 9 .Fig. 10 .

 8910 Fig. 8. Evolution of G wb between S2 and S3.

ACKNOWLEDGMENT

This work is done under the mmW4Rail project financed by the French Research Agency (ANR) under Grant ANR-20-CE22-0011-01 and ANR-20-CE22-0011-02.


Michela Limardi

Recall Bias of Environmental Campaigns

Keywords: NGOs, Environmental Campaigns, Pro-environmental behavior JEL: Q50, Q48

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Environmental campaigns aim to increase the environmental awareness of individuals and induce a pro-environmental behavior. Many resources are devoted to the organization of environmental * University of Lille (RIME) and University of Paris 1 (CES), email: michela.limardi@univ-paris1.fr 1 campaigns, but still little is known about the actual effectiveness of those campaigns. One of the methods used to assess the effectiveness of environmental campaigns is to conduct a survey, after the end of the campaign, and ask if an individual remembers it. The higher the percentage of respondents remembering it, the more effective the campaign is considered to be. This method is normally used in the advertising literature on how to measure the success of campaigns. However, it is worth considering that recalling environmental campaigns might be related to some specific individual characteristics of the respondents.

The main idea of this article is that a bias may exist in recalling environmental campaigns according to the environmental behavior of individuals. This bias may affect ex-post evaluations of environmental campaigns. We want to measure this potential bias and investigate the main reasons behind that. We use an original survey conducted by a French non-profit organization, Cyclamed, in the Paris region to assess the effectiveness of its drug recycle campaigns. Cyclamed, which is responsible for drug disposal in France, regularly carries out environmental campaigns throughout the subway system in the Paris region. This is the region where drug recycling is the lowest in France. The aim of these campaigns is to increase the number of individuals recycling their unused or expired drugs. First, we conduct a Probit analysis of the probability of an individual remembering the campaign. Then we apply the difference-in-difference method, which allows us to estimate the difference between individuals who were exposed to the campaigns and those who were not, interacted with an individual dummy of the individual's recycling behaviour prior to the campaign.

Our findings show that there is a systematic recall bias of the campaigns according to the environmental behavior of an individual. Respondents who recycle drugs systematically remember the campaigns more than those who do not. They also appreciate the campaigns more than the non-recycling respondents and find them clearer and more convincing on the utility of recycling drugs for the environment. Interestingly, this effect does not depend on how often they were exposed to the subway campaign. This Recall bias of environmental campaigns might then reduce their potential impact by attracting the attention of people who are already interested in an environmentally-friendly behavior. This implies that deeper reflection is needed in order to find the right message to successfully reach the target group of environmental campaigns, i.e. individuals with low environmental awareness. objective of many firms today is to provide a "green" image of their products to consumers. Studies show the effectiveness of this kind of green advertising according to different mechanisms [START_REF] Minor | Csr as reputation insurance: Primum non nocere[END_REF][START_REF] Cabral | The economics of trust and reputation : A primer[END_REF][START_REF] Kahn | Do greens drive hummers or hybrids? environmental ideology as a determinant of consumer choice[END_REF][START_REF] Barrage | Advertising and environmental stewardship: Evidence from the bp oil spill[END_REF]. Several studies in the business literature consider recall as a measure of the effectiveness of advertising slogans [START_REF] Molian | i am a doughnut': Lessons for the sloganeer[END_REF][START_REF] Dass | A study of the antecedents of slogan liking[END_REF][START_REF] Kohli | Are you in good hands?: slogan recall: what really matters[END_REF]. [START_REF] Kohli | Are you in good hands?: slogan recall: what really matters[END_REF] shows how the amount of media exposure have the biggest influence on slogan recall. However, few studies exist on the effectiveness of environmental campaigns conducted by the state or environmental non-profit organizations to raise environmental awareness. As far as we know, this is the first study that investigates the recall bias of an environmental campaign according to the environmental behavior of an individual, a factor that might reduce the potential impact of the campaign.

Empirical Analysis

Descriptive statistics

Cyclamed has conducted three campaigns in the subway system in the region of Paris: in February 2019, November 2019 and March 2020. Each campaign consisted in several posters placed in the subway and lasts one week. 1 A survey is conducted after the end of each campaign to assess its effectiveness. We use data collected through these campaign evaluation surveys, which provides cross-sectional data and information of individual characteristics: income, job, home city, age, sex, the size of the household and if the individual is responsible of the drug recycling in the household. Our main variable of interest is the recycling behavior of the respondent before the campaign and whether or not they remembers the campaign. The variable recycle equals one if the respondent recycle drugs and zero otherwise; the variable recall equals one if the respondent remembers the campaign and zero otherwise. For each campaign, Table 1 shows the number of people surveyed (Column 1), the percentage of people recycling drugs (Column 2) and the percentage of people who remember the poster campaigns (Column 3). Almost 70 percent of the people surveyed recycle drugs and 36 percent of the sample remember the campaign.2 In 1 The posters used in the three campaigns are included in the Appendix.

the survey, the respondents were also asked to identify the organization (non-profit, profit or the State), that carried out the drug recycling campaign. Table 1 shows the percentage of people attributing the campaign to Cyclamed (Column 4), other NGOs (Column 5), the State (Column 6), pharmacies (Column 7) or Citeo (Column 8), a private organization that manages the disposal of other products. In the question concerning the organization that conducted the campaign, the response option of the State and Citeo was introduced in the survey of the last campaign, March 2020. On average, almost 40 percent of people attributes the campaigns to the right organization, Cyclamed.

Identification Strategy

In France, people can recycle unused or expired drugs by bringing them to any pharmacy.3 Cyclamed is a French Non-profit Organization that is in charge of the national system of drug disposal. It has been authorized by the State to manage the entire process. 4 Therefore there is no other competitor in the drug disposal sector in France that could act as an external driver for the strategies of Cyclamed, such as the amount of resources to be devoted to environmental campaigns.

Cyclamed's objective is to increase the number of people recycling drugs. The annual financial resources of Cyclamed are provided by pharmaceutical firms according to the "polluter pays" principle. Therefore, it does not even face the issue of providing certain outcomes to increase donations as other environmental Non-profit organizations do. Each year Cyclamed devotes almost 30 percent of its total annual budget to awareness-rising campaigns.

The Cyclamed campaigns are placed throughout the subway system in Paris region (Ile de France) for one week. After the end of the campaign a survey is conducted. More than the half of the individuals (60 percent) in the sample were surveyed the day after the end of the campaign while the other 40 percent were surveyed two days after. We exploit this time delay in the survey in order to estimate the recall bias. We use also the information on the recycling behavior of the individual, and the frequency of using the subway in the last week, to identify the impact of the participant's recycling behaviour on the recall bias of the campaign. We estimate the following model:

P r(recall itd = 1) = F (α + β 1 recycle i + β 2 exposure i + β 3 X i + η t + η d + idt ) (2.1)
where recall is a dummy variable that equals one if the individual i remembers the campaign and zero otherwise. Variable exposure can take values between 1 and 3 corresponding to the answers to the question on the number of trips taken on the subway in the previous week: exposure equals 3 if the answer is "every day", 2 if the answer is "yes, between 2 and 5 " and 1 if the answer is "yes, just one". We control for a set of respondents' characteristics: income, sex, age, job, household size. We put in all regressions campaign fixed effects η d and department fixed effects η d . We cluster the standard error at department level. Finally, idt is the error term.

Second, we exploit a set of questions in the survey to assess the attractiveness of the campaign.

The interviewer shows the posters to the respondents and they have to assign a degree of attractiveness to each poster. We exploit these answers in order to identify a potential mechanism of the recall bias. We perform a difference in difference analysis. Our treatment are people potentially exposed to the subway campaign.The variable T exposure is a dummy variable that equals one if the respondent took the subway at least once during the Cyclamed campaign, and zero if he did not take the subway in the previous week. We run the following equation:

Y itd = α + β 1 norecycle i + β 2 T exposure i + β 3 norecycle i * T exposure i + β 4 X i + η t + η d + idt (2.2)
where Y is the level of attractiveness of a poster for an individual i that can take values between 1 and 10, where 1 means people completely disagree and 10 people completely agree to the following three sentences: "The message of the posters is clear" (Clear), "I like these posters" (Like), "These posters are convincing on the utility of recycling drugs for the environment" (Env).

The variable norecycle equals 1 if the respondent did not recycle drugs prior to the campaign and zero otherwise. We interact the exposure dummy T exposure with the dummy of the individual's recycling behavior norecycle. We control as before for a set of respondents' characteristics: income, sex, age, job, sizehousehold. We put in all regressions campaign fixed effects η d and department fixed effects η d . We cluster the standard error at department level. Finally, idt is the error term.

Results

The results of our baseline estimation (2.1) are reported in Table 3. Columns (1) to (3) report the estimations of a specification that pools all respondents. The coefficient of our variable of interest recycle is positive and highly significant in all specifications. There is a systematic recall bias of the campaigns according to an idnividual's environmental behavior. In Column ( 4) and ( 5) we split the sample in individuals surveyed the day after the end of the campaign (column 4) and individuals surveyed two days after the end of the campaign (column 5). It is interesting that for people interviewed two days after the end of the campaign, the magnitude of the variable recycle becomes even larger than the variable exposure. However, the recall bias can be different if the respondent knows Cyclamed even if he does not recycle drugs. Table 4 shows the results of the probit regression when we control for variables related to the attribution of the campaigns namely cyclamed, NGO, State, pharmacies and citeo. The attribution to the right organization, Cyclamed, positively affects the probability of recalling the campaign, however the variable recycle remains positive and highly significant. In contrast, a wrong attribution to another N GO (such as Greanpeace, Unicef, WWf) or the State reduces the probability of recalling the campaign. 5This recall bias might be related to the type of message delivered. Table 2 presents the mean values of the variables recall, exposure, Clear, Env and Like for people recycling drugs and not recycling drugs. There is a statistically-significant difference in the average values of the two groups for the three variables concerning the assessment of the campaigns by the respondents.

Importantly, there is no statistically significant difference in the average value of the variable exposure. The results of equation 2.2 are reported in Table 5. The results show that individuals who do not recycle drugs systematically appreciate the campaigns less and find the posters less clear and convincing on the utility of recycling drugs for the environment than individuals who do recycle drugs. Interestingly, this effect does not depend on the exposure to the subway campaign.

Conclusion

In this paper we have studied the potential recall bias of environmental campaigns, using data from original surveys conducted in the region of Paris after the end of drug disposal campaigns. First, we perform a Probit analysis, to estimate the probability of an individual remembering the campaign.

Then we apply the difference-in-difference method, which allows us to estimate the difference between individuals who were exposed to the campaigns and those who were not, interacted with an individual dummy of the individual's recycling behaviour prior to the campaign.

Our findings show that there is a systematic recall bias of the campaigns according to the environmental behavior of an individual. Respondents who recycle drugs remember more the campaigns than respondents who do not. This recall bias might be related to the type of message delivered. We find that respondents recycling drugs appreciate the campaigns more and find them clearer and more convincing on the utility of recycling drugs for the environment than nonrecycling individuals. Interestingly, this effect does not depend on the degree of exposure to the subway campaign. Recall bias of environmental campaigns may then reduce the potential impact of an environmental campaign by drawing the attention of people already concerned with an environmentally-friendly behavior. More research, like focus group analysis of advertising product campaigns, is needed to identify the most appropriate message of environmental campaigns to successfully capture the attention of the right target audience, i.e. non recycling individuals. exposure can take values between 1 and 3 corresponding to the answers to the questions on the number of trips taken on the subway in the previous week: equals 3 if the answer is "every day", 2 if the answer is "yes, between 2 and 5 " and 1 if the answer is "yes, just one". The variables Clear, Like, Env have values between 1 and 10, where 1 means people completely disagree and 10 people completely agree to the following three sentences: "The message of the posters is clear" (Clear), "I like these posters" (Like), "These posters are convincing on the utility of recycling drugs for the environment" (Env). The dependent variable recall equals 1 if respondent remembers the campaigns and zero otherwise; recycle equals one if respondent recycles drugs and zero otherwise; exposure can take values between 1 and 3 corresponding to the answers to the questions on the number of trips taken on the subway in the previous week: equals 3 if the answer is "every day", 2 if the answer is "yes, between 2 and 5 " and 1 if the answer is "yes, just one". variables cyclamed, NGO, State, pharmacy and citeo have values between 0 and 1, where 1 means people attribute the campaign respectively to each organization. The dependent variables Clear (column 1), Like (column 2), Env (column 3), have values between 1 and 10, where 1 means people completely disagree and 10 people completely agree to the following three sentences: "The message of the posters is clear" (Clear), "I like these posters" (Like), "These posters are convincing on the utility of recycling drugs for the environment" (Env). norecycle equals one if respondent does not recycle drugs and zero otherwise. The variable Texposure is a dummy variable that equals one if the respondent took the subway at least once during the Cyclamed campaign, and zero if he did not take the subway in the previous week. Control variables include: job, revenue, studies, sex. Standard error in parentheses, with * indicating significance at 0.10, ** indicating significance at 0.05 and *** indicating significance at 0.001. Cluster at department level.

Table 1 :

 1 Recycle, Recall and Attribution of Cyclamed Campaigns: percentage of respondents

	campaign	nb observations recycle recall cyclamed NGO State pharmacy citeo
		(1)	(2)	(3)	(4)	(5)	(6)	(8)	(9)
	February 2019	1044	0.66	0.28	0.47	0.29	n.a.	0.23	n.a.
	November 2019	1039	0.72	0.38	0.40	0.40	n.a.	0.20	n.a.
	March 2020	1045	0.73	0.40	0.36	0.16	0.30	0.14 0.03
	Average	1042.67	0.71	0.36	0.41	0.28	0.10	0.19 0.01
	recycle equals one if respondent recycles drugs and zero otherwise; recall equals 1 if respondent remembers the campaigns and
	zero otherwise; variables Cyclamed, NGO, State, Pharmacy and Citeo have values between 0 and 1, where 1 means people at-
	tribute the campaign respectively to each organization.

Table 2 :

 2 Assessment of the advertising campaign. People recycling drugs compared to people not recycling drugs

	recycle	recall	exposure	Clear	Env	Like
	(1) Not recycle	.2721382	1.641469	6.844809	6.403141	6.291209
		(.0146335) (.0409303 )	(.0756644)	.0985914	(.077121)
	(2) recycle	.3914623	1.634423	7.756264	7.625414	7.378043
		(.0104035) (.0261046)	(.0430389)	.0518164	(.0444077)
	(3) Difference	-.1193241	.0070454	-.9114555	-1.222272	-1.08683
		(.0186396 ) (.0482178 )	(.0826433)	.1037569	( .0848744)
	(4) t-test diff	-6.4017***	0.1461 -11.0288*** -11.7802*** -12.8052***
	recycle equals one if respondent recycles drugs and zero otherwise; recall equals 1 if respondent remembers
	the campaigns and zero otherwise.

  Control variables include: job, revenue, studies, sex. Standard error in parentheses, with * indicating significance at 0.10, ** indicating significance at 0.05 and *** indicating significance at 0.001. Cluster at department level.

Table 5 :

 5 OLS regression -pooled cross section

	Dependent variable: Clear (1), Like (2), Env (3)
		1	2	3
		Coef./se	Coef./se	Coef./se
	Texposure*Norecycle	0.473	0.354	0.643
		(0.31)	(0.33)	(0.41)
	Texposure	0.163	0.304**	0.210
		(0.13)	(0.11)	(0.18)
	norecycle	-1.186*** -1.209*** -1.576***
		(0.24)	(0.25)	(0.35)
	r2	0.271	0.300	0.342
	N	3054	3031	2045
	Campaign fixed effect	Yes	Yes	Yes
	Department fixed effect	Yes	Yes	Yes
	Control variables	Yes	Yes	Yes

This average 70 percent corresponds to the percentage of people declaring recycling drugs in the region of Paris in other surveys conducted by Cyclamed.

In France it is mandatory under the law for pharmacies to accept unused or expired drugs and individuals are not paid for that.

The drug disposal process consists of collecting unused and expired drugs in the pharmacies and transporting them to recycling platforms. They are then incinerated in an environmentally-friendly process to release energy.

This result supports our premise, where a bad attribution corresponds to less clear information.

The dependent variable recall equals 1 if respondent remembers the campaigns and zero otherwise; recycle equals one if respondent recycles drugs and zero otherwise; exposure can take values between 1 and 3 corresponding to the answers to the questions on the number of trips taken on the subway in the previous week: equals 3 if the answer is "every day", 2 if the answer is "yes, between 2 and 5 " and 1 if the answer is "yes, just one". Sample in column (4) corresponds to individuals surveyed the day after the end of the campaigns, in column (5) individuals surveyed two days after the end of the campaigns. Control variables include: job, revenue, studies, sex. Standard error in parentheses, with * indicating significance at 0.10, ** indicating significance at 0.05 and *** indicating significance at 0.001. Cluster at department level.


Michela Limardi
email: michela.limardi@univ-paris1.fr

Morgane Tanvé
email: morgane.tanve@univ-lille.fr

Anti-Environmental Behavior: Disregard or Lack of Information?

Keywords: NGOs, Environmental Policy, Anti-environmental behavior JEL: Q50, Q48

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The main motivations behind an individual environmental behavior are still under debate. Why do we recycle? Why do we recycle more paper than drugs? A basic decision rule is to adopt a behavior as long as its utility exceeds its cost [START_REF] Bertrand | What's advertising content worth? evidence from a consumer credit marketing field experiment[END_REF]. However, the utility of adopting a behavior is not always known. Environmental campaigns can encourage the adoption of a behavior in providing information on: the available recycling facilities; the utility of the behavior, valuing the action (i.e. the utility that can be derived from it); the cost of adopting the behavior.

We are interested here in the potential role of delivering an information on the available recycling facilities to non-recycling individuals. The aim of this study is to investigate if an antienvironmental behavior might depend on some social values (preferences) or a lack of information.

First, we build a simple model to understand the potential role of environmental campaigns on the revision of individual's beliefs. Following [START_REF] Bertrand | What's advertising content worth? evidence from a consumer credit marketing field experiment[END_REF], we formalize three different mechanisms of the effect of an environmental campaign on the individual behavior: informative, complementary and persuasive. In our study, these mechanisms will have different impacts according to the degree of environmental awareness of an individual. The level of an individual environmental awareness might play a role on the utility and the cost of a recycling action [START_REF] Czajkowski | Social norms, morals and self-interest as determinants of pro-environment behaviours: The case of household recycling[END_REF]. For an individual with a low environmental awareness an informative campaign can be less or more effective than for a high environmental awareness individual.

We use an original survey conducted by a French Non-profit Organization to assess the effectiveness of its drug recycle policies to test our theoretical results. We conduct first a probit analysis of the probability that an individual recycle drugs. Then, we exploit a question in the survey where the interviewer provides the information to non recycling respondents on how it works the drugs recycle process and why is it important for the environment. We estimate then the difference among non recycling respondents with respect to their intent to change their behavior, once this information is received.

We find that the information does not provide any incentive to change the behavior to non recycling respondents with a low degree of environmental awareness, while it has a positive impact for non-recycling respondents with a higher degree of environmental awareness. Our interpretation is that the impact of an environmental campaign depends on the motivation behind an anti-2 environmental behavior. If there are people who are aware of environmental issues and they would like to change their behavior but they do not have the information, informative campaigns can be more effective. While for individuals with low environmental awareness, persuasive campaigns can be effective in building awareness about an environmental issue. Different types of environmental campaigns, informative versus persuasive, might then have different impact according to the environmental awareness of individuals.

There exists a large literature on the role of environmental advertising in the private sector.

The objective of the firm is to provide a "green" image of their products to the consumers. Studies show the effectiveness of this kind of green advertising according to different mechanisms [START_REF] Minor | Csr as reputation insurance: Primum non nocere[END_REF][START_REF] Cabral | The economics of trust and reputation : A primer[END_REF][START_REF] Kahn | Do greens drive hummers or hybrids? environmental ideology as a determinant of consumer choice[END_REF][START_REF] Barrage | Advertising and environmental stewardship: Evidence from the bp oil spill[END_REF]. However, still few studies exist on the effectiveness of environmental campaigns conducted by the state or environmental NGOs to raise environmental awareness. We provide here an analysis of an informative campaign conducted by a Non-profit organization. There exist also a large volume of literature that shows the effects of informative campaigns on the consumer behavior [START_REF] Carlsson | Behavioral spillover effects from a social information campaign[END_REF][START_REF] Ito | The persistence of moral suasion and economic incentives: Field experimental evidence from energy demand[END_REF][START_REF] Ferraro | Using Nonpecuniary Strategies to Influence Behavior: Evidence from a Large-Scale Field Experiment[END_REF]. Our contribution is to show that the impact of an informative campaign might depend on the "type"of the receiver, i.e. his degree of environmental awareness. A better understanding of the motivations behind anti-environmental behavior might help to design more effective environmental campaigns (informative versus persuasive).

The remainder of the paper is organized as follows. In Section 2 we present a conceptual framework of an environmental camapign; in Section 3 we present the data and method used to identify the impact of an informative campaign according to the environemental awareness of an individual. The section 4 presents the results and the last section concludes.

Conceptual Framework

In a disposal system where there is no pecuniary reward for recycling or fines to pay (no punishment) such as drugs recycling in France, an individual recycles because of intrinsic motivation 1 .

1 Several studies explain the role of intrinsic motivation in an individual recycling decision citepNyborg201 3 A basic decision rule is that an individual recycles if and only if:

U i (r) -c i > 0 (1)
where U i (r) is the individual's utility gain from recycling and c i is the cost of recycling.

The utility may derive from some environmental awareness of the individual, while the cost of recycling are the cost of getting the information and/or realize the action. Let allow the possibility that environmental campaigns affect individuals behavior2 . We follow [START_REF] Bertrand | What's advertising content worth? evidence from a consumer credit marketing field experiment[END_REF] and we adapt the three different mechanisms of the effect of advertising on the consumer behavior to environmental campaigns3 . A first mechanism is informative environmental campaigns, where the individual has uncertainty about the utility gain , such as the value of the action or the credibilitytrust about the recycling disposal process. In this case, environmental campaigns will affect the individual's expectations about the utility and cost. Then, the individual will recycle if

E u t (M it )[U i (r)] -E t (M it ) c [c i ] > 0 (2)
where expectations E at time t are affected by the environmental campaigns content (C) that individual i receives. In our case, for exmaple, transmitting the information that Cyclamed is a non-profit organization and how it manages the drug recycle disposal can increase the level of trust in the recycling process and then the individual's expectations of the value (the utility) of recycling drugs. In the annual survey conducted by Cyclamed, this type of message is delivered by the interviewer, and this is the channel that we investigate in our empirical analysis. A second possibility is complementarity to recycle: individuals have fixed preferences and environmental campaigns confirm or not the belief of the individual. So, individual recycles if:

U i (r, r * C i ) -c i > 0 (3)
This could be the case for some recycling behavior that will affect the "social" status of an individual. This mechanism is not adapted to the drugs recycle, where the social approval is not determinant in the individual decision process. Finally, a third mechanism is persuasive environmental campaigns. As stated by [START_REF] Bertrand | What's advertising content worth? evidence from a consumer credit marketing field experiment[END_REF], "persuasion can operate directly on preferences by manipulating reference points,[...], providing motivation to make (rather than procrastinate) choices, or simplifying the complexity of decision making". Individuals decide to recycle or not according to

D i (u i (r), E i ) -c i > 0 (4)
where D i (u i (r), E i ) is the effective decision, rather than the true utility (Bertand 2010). Our idea is that these mechanisms will have different impacts according to the degree of environmental awareness of an individual i. The level of an individual environmental awareness might play a role on the utility and the cost of a recycling action. For an individual with a low environmental awareness an informative campaigns can be less or more effective than for a high environmental awareness individual. In our empirical analysis, we want precisely to test this mechanism.

3 Data and empirical method

Data and Descriptive statistics

In France recycling is voluntary based, no sanctions or payments are foreseen. Recycling paper, plastic and glass is now well established among people. People have to sort their waste and put it in separate bins located close to their residence. A waste disposal system is then organized by each municipality. However, there are other products, like batteries, drugs, bulbs, where the disposal system is established but more costly for people, because they have to move in a specific place and they have to know first where they can do it.

People can recycle unused or expired drugs by bringing them to any pharmacy. In France it is mandatory under the law for pharmacies to accept unused or expired drugs and individuals are not paid for that. Cyclamed is a French Non-profit Organization that is in charge of the national system of drug disposal. It has been authorized by the State to manage the entire process. The drug disposal process consists of collecting unused and expired drugs in the pharmacies and transporting them to recycling platforms. They are then incinerated in an environmentally-friendly process to release energy. Cyclamed's objective is to increase the number of people recycling drugs. The annual financial resources of Cyclamed are provided by pharmaceutical firms according to the "polluter pays" principle. Therefore, it does not face the issue of providing certain outcomes to increase donations as other environmental Non-profit organizations do. Moreover, there is no other competitor in the drug disposal sector in France that could act as an external driver for the strategies of Cyclamed, such as the amount of resources to be devoted to environmental campaigns [START_REF] Limardi | Recall bias of environmental campaign[END_REF].

Cyclamed conducts each year a campaign about drugs recycling at national level broadcast on the French television. A survey is conducted one month after the end of each campaign to investigate the individual behavior about recycling drugs and other waste disposal. Our main dataset comes from these surveys for the following years 2017-2020. This is a national representative survey of more than 1000 respondents4 , which provides cross-sectional data and information of individual characteristics: income, job, home city, age, sex and the size of the household. The survey asks a series of questions about the recycling behavior of the respondents for different waste (glass, paper, plastic, pulps, batteries and drugs) and why they think is important recycling drugs.

The question is framed in the following way: "For each type of waste, indicate how often you sort them to put them in bins or to bring them back to the appropriate places". Table 1 and Table 2 show the percentage of respondents recycling glass, paper and plastic (Table 1) and pulp, batteries and drugs (Table2). In Table 1 around 90 percent of the individuals recycle paper, glass and plastic, while the average of recycling drugs, pulps and battery is lower, around 70 percent. The difference in the waste disposal system in France might explain the difference in the percentage of people recycling.5

Identification strategy and empirical method

Cyclamed conduct annually a survey to investigate the recycling behavior of french people6 .

We exploit a question in the survey addressed to all respondents declaring not recycling drugs as an informative environmental campaign. The interviewer first provides the information about Cyclamed and then he explains how it works the drugs recycling process in France. The question is framed in the following way: "Cyclamed is an association (French Law 1901), which manages and coordinates a disposal system of unused drugs for the purpose of health and environmental safety.

Cyclamed encourages people to return unused drugs, whether expired or not, to pharmacies. Drugs are incinerated to provide energy and disposed in an environmentally friendly manner". Then the interviewer asks if the respondent will start recycling drugs after receiving this information. The question is framed in this way: "And do you intend, now that I have told you about Cyclamed, to return your unused drugs to your pharmacy in the future?". The respondent may choose between :

"yes for sure, yes probably, no probably and no for sure". On average 52 percent replies "Yes for sure", 37 percent replies "Yes probably" and 10 percent replies "Probably not" and "Not for sure" (Table 3). 7 We exploit this variation in the answer to investigate why the same information gives different incentives to change the behavior within the non-recycling sample.

We want to test if the different degree of environmental awareness of an individual might affect the impact of an informative campaign. We use the answer to the following question that is addressed to all respondents (recycling and non recycling): "I will now quote to you a number of motivations that have been given to me about recycling unused drugs. For each of them, tell me if you totally agree, somewhat agree, don't really agree or totally disagree", as a measure of the environmental awareness of the respondent. The "motivations" stated are the following: "This prevents drugs from ending up in landfills"; "This contributes to the protection of the environment"; "This avoids the risk of water pollution"; "This makes it possible to supply energy by incineration"; "This limits the risk of poisoning within the household". 8 We build dummy variables corresponding to these answers. The variable protenv equals 1 if the respondent "totally agree"' or "somewhat agree" to the statement: "This contributes to the protection of the environment", and zero if don't really agree or totally disagree". The variable landf ill equals 1 if the respondent "totally agree" or "somewhat agree" to the statement "This prevents drugs from ending up in landfills", and zero if "don't really agree or totally disagree". The variable pollution equals 1 if the respondent "totally agree" or "somewhat agree" to the statement "This avoids the risk of water pollution";, and zero if "don't really agree or totally disagree". The variable riskhousehold equals 1 if the respondent "totally agree" or "somewhat agree" to the statement "This limits the risk of poisoning within the household", and zero if "'don't really agree or totally disagree". The variable energy equals 1 if the respondent "totally agree" or "somewhat agree" to the statement "This makes it possible to supply energy by incineration", and zero if "don't really agree or totally disagree".

We exploit then a question related to the knowledge of the respondent of the drug disposal system. Importantly, this question is addressed to all respondents before the question concerning the information about Cyclamed and the explanation on how it works the drugs disposal system in France. The question is framed as following: "Do you know an organization whose objective is to dispose unused drugs?". We build a dummy variable knoworg that equals 1 if the answer is "'yes" and zero otherwise.

We compare first non-recycling respondents declaring changing the behavior for sure after receiving the information with respect to recycling respondent. Second, we compare non-recycling respondents declaring not changing the behavior after receiving the information with respect to recycling respondent. Table 6 and Table 7 show the difference in mean of the two groups. What is interesting here is that there is no statistical difference in mean between recycling respondents and non-recycling respondent that will change for sure their behavior (Table 6) for the motivations of recycling drugs, while there is a statistical difference in mean for the variable knoworg. On the contrary, the difference in mean of the variables of the motivations are highly statistical significant between recycling respondents and non-recycling respondents who will not change their behavior (Table 7), while there is no statistical difference in mean for the variable related to the knowledge of the organization.

First, we estimate the probability of recycling of an individual, to find some determinant of the recycling behavior. We estimate the following model:

P r(recycle itd = 1) = F (α + β 1 knowOrg i + β 2 ST recycle i + β 3 Hrecycle i + +β 3 X i + η t + η d + idt ) (5)
where recycle is a dummy variable that equals one if the individual i recycle drugs and zero otherwise. ST recycle and Hrecycle are dummy variables related to the recycling behavior of the respondent for other types wastes: glass, paper and palstic (ST recycle); pulp and battery (Hrecycle). We control for a set of respondents' characteristics: income, sex, age, job, household. We put in all regressions campaign fixed effects η d and department fixed effects η d .

We cluster the standard error at region level. Finally, idt is the error term.

Second, we estimate the probability of declaring changing the behavior after receiving the information about Cyclamed and the drugs disposal system in France within the non-recycling respondents9 . We estimate the following model:

P r(changebehavior itd = 1) = F (α + β 1 knowOrg i + β 2 ST recycle i + +β 3 Hrecycle i + β 3 X i + η t + η d + idt ) (6)
where changebehavior is a dummy variable equals 1 if the respondent declares to change the behavior once he receives the information about Cyclamed. We control as before for a set of respondents' characteristics: income, sex, age, job, size household. We put in all regressions campaign fixed effects η d and department fixed effects η d . We cluster the standard error at region level. Finally, idt is the error term.

Finally, we estimate the probability of considering the following motivations for recycling drugs important or not. We measure this probability for the three different groups ("I will change for sure", "I will probably change", "I will not change") within the non recycling respondents compared to the recycling individuals in the sample. We build a categorical variable comparison that equals 1 if the respondent reply "I will for sure" change the behavior once he receives the information, equals 2 if the respondent reply "I will probably" change the behavior once he re-ceives the information, equals 3 if the respondent reply "I will not" change the behavior once he receives the information. The value zero corresponds to respondent recycling drugs. We estimate the following model:

P r(motivations itd = 1) = F (α + β 1 comparison i + α + β 1 knowOrg i + +β 2 ST recycle i + β 3 Hrecycle i + β 3 X i + η t + η d + idt ) (7)
where motivations is a dummy variable equals 1 if the respondent declares that recycling drugs is important for the reasons listed above (protecting environment, avoiding drugs in the landfills, producing energy, reducing risk at home, avoiding water pollution) and zero otherwise.

We control also here for a set of respondents' characteristics: income, sex, age, job, size household.

We put in all regressions campaign fixed effects η d and department fixed effects η d . We cluster the standard error at region level. Finally, idt is the error term.

Results

Table 4 shows the results of equation 5. In this equation we want to test just some determinants of the recycling behavior. The variable ST recycle and Hrecycle are positive and higly signinficant.

This means that recycling other type of waste (glass, etc;) increase the probability of recycling drugs. It is interesting also that knowing an organization that manage the drug disposal in France increase the probability of recycling drugs (variable knowOrg is positive and highly significant).

The results of our baseline estimation (6) are reported in Table 5. Columns (1) to (3) report the estimations of a specification that pools all non-recycling respondents. The coefficients of the variables ST recycle, Hrecycle are positive but not significant in all specifications, while the variable knowOrg is negative and highly significant. This means that non-recycling respondents who do not know the organization before receiving the information will increase the probability of changing the behavior and this is true given their recycling behavior for other types of wastes.

Finally, the results of equation 7 are reported in Table 8. Columns (1) to (5) report the estimation for the different motivations for recycling drugs (protenv, pollution, landf ill, risk, energy). It is interesting that for all these motivations there is no difference between non-recycling respondents declaring they will for sure change the behavior (Icomparison1) after receiving the information and recycling respondents. While there is a statistical difference for the two other groups (who will probably change the behavior-Icomparison2and who will not change the behavior-Icomparison3) compared to the recycling respondents. It seems that individuals who declare they will change the behavior for sure are similar to recycling respondent in the level of environmental awareness. They need just an information about the existence of a trustful waste disposal mechanism to behave pro-environmentally.

Conclusion

In this paper we have studied the potential impact of an informative campaign according to the environmental awareness of an individual, using data from original surveys conducted in France once per year, after the end of drug disposal campaigns. We conduct first a probit analysis of the probability that an individual recycle drugs. Then, we exploit a question in the survey where the interviewer provides the information to non recycling respondents on how it works the drugs recycle process and why is it important for the environment. We estimate then the difference among non recycling respondents with respect to their intent to change their behavior, once this information is received.

Our findings show that an informative message has an impact just on individual with an high environmental awareness. It could be interesting for future research to test if a persuasive environmental campaign can be more effective to induce a change in the behavior of individual with a low environmental awareness.

Table 1 :

 1 Percentage

		of people recycling glass, plastic
	and paper by campaign
	campaig nb observations glass plastic paper
	2017	1004.00 0.91	0.89	0.92
	2018	1004.00 0.90	0.88	0.89
	2019	1041.00 0.93	0.91	0.93
	2020	2265.00 0.92	0.90	0.90
	Total	1548.73 0.91	0.90	0.91
	Table 2: Percentage of people recycling battery, pulp and drugs
	by campaign
	campaign nb observations battery pulp drugs
	2017	1004.00	0.81 0.74		0.71
	2018	1004.00	0.80 0.73		0.70
	2019	1041.00	0.86 0.78		0.73
	2020	2265.00	0.82 0.77		0.67
	Average	1548.73	0.82 0.76		0.69

Table 3 :

 3 People declaring to start recycling drugs or not after the information about the existence of the NGO Cyclamed

	campaign	Non-recycling Sure Probably Noway
	2017	0.29	0.48	0.39	0.13
	2018	0.30	0.53	0.34	0.12
	2019	0.26	0.54	0.36	0.10
	2020	0.25	0.52	0.37	0.11
	Average	0.27	0.52	0.37	0.12
	Sure is a dummy variable equals one if the respondent declares changing for
	sure his behavior; Probably is a dummy variable equals one if the respon-
	dent declares changing probably his behavior; Noway is a dummy variable
	equals one if the respondent declares he will not chage his behavior

Table 4 :

 4 Individual characteristics and the prob of recycling drugs. Probit

	Dependent variable: recycle
		1	2	3
		Coef./se	Coef./se	Coef./se
	sizehousehold	0.100*** 0.092*** 0.090***
		(0.02)	(0.01)	(0.01)
	Age	0.019*** 0.017*** 0.016***
		(0.00)	(0.00)	(0.00)
	STrecycle		0.196*** 0.187***
			(0.06)	(0.06)
	Hrecycle		0.588*** 0.579***
			(0.06)	(0.06)
	knowOrg			0.159***
				(0.03)
	r2
	N	5279	5279	5279
	Campaign fixed effect	Yes	Yes	Yes
	Departement fixed effect	No	Yes	Yes
	The dependent variable recycle is equal to 1 if the individual recycle always
	or often drugs; zero otherwise. The variable knowOrg= 0 if people do not
	know the organization and =1 if people know the organization. Standard
	error in parentheses, with * indicating significance at 0.10, ** indicating
	significance at 0.05 and *** indicating significance at 0.001.

Table 5 :

 5 Determinants of the probability of behavior change. Probit

	Dependent variable: changebehavior
		1	2	3
		Coef./se	Coef./se	Coef./se
	sizehousehold	-0.012	-0.013	-0.006
		(0.01)	(0.01)	(0.02)
	Age	-0.013*** -0.013*** -0.012***
		(0.00)	(0.00)	(0.00)
	STrecycle		0.134	0.138
			(0.10)	(0.10)
	Hrecycle		0.067	0.090
			(0.12)	(0.12)
	knowOrg			-0.426***
				(0.16)
	r2
	N	1565	1565	1565
	Campaign fixed effect	Yes	Yes	Yes
	Departement fixed effect	No	Yes	Yes
	The dependent variable changebehavior is equal to 1 if the individual replies
	"yes I will change (for sure and/or probably behaviour" ; zero otherwise. The
	variable knowOrg= 0 if people do not know the organization and =1 if peo-
	ple know the organization. Standard error in parentheses, with * indicating
	significance at 0.10, ** indicating significance at 0.05 and *** indicating sig-
	nificance at 0.001. Cluster at the departement level.

Table 6 :

 6 Utility (motivations) of drugs recycling. Individuals recycling drugs compared to individuals not recycling drugs who will for sure change their behavior after the reception of the information

	recycle behaviour	landfill	protenv	pollution	riskfoyer	energy	knoworg
	(1) Not-Recycling (sure)	.9213026	.9470828	.9280868	.8819539	.743555	.1411126
		(.0099253) (.0082519 ) (.0095227) (.0118935) (.0160959) (.0128325)
	(2) Recycling	.9253123	.9535578	.9402499	.8938077	.7542097	.2569256
		(.004333) (.0034685) (.0039067) (.0050779) (.0070965) (.0072017)
	(3) Difference	-.0040098	-.0064751	-.012163 -.0118538	-.0106547	-.115813
		(.0106543) (.0085868) (.0097158) (.0125353) ( .0174199) (.0170907)
	(4) t-test diff	-0.3764	-0.7541	-1.2519	-0.9456	-0.6116 -6.7764***

Table 7 :

 7 Utility (motivations) of drugs recycling. Individuals recycling drugs compared to individuals not recycling drugs who will not change their behavior after the reception of the information

	recycle behaviour	landfill	protenv	pollution	riskfoyer	energy	knowOrg
	(1) Not-Recycling (noway)	.6056338	.556338	.5915493	.4647887	.4225352	.2957746
		(.0411572)	(.0418394 )	(.0413957)	(.0420031) (.0415992)	(.038435)
	(2) Recycling	.9253123	.9535578	.9402499	.8938077	.7542097	.2569256
		(.004333)	(.0034685 )	(.0039067)	(.0050779) (.0070965) (.0072017)
	(3) Difference	-.3196785	-.3972198	-.3487006	-.429019	-.3316745	.0388491
		(.0234913)	(.0194705)	(.0214825)	(.027136) (.0370467) (.0374403)
	(4) t-test diff	-13.6084*** -20.4011*** -16.2319*** -15.8099*** -8.9529***	1.0376

Table 8 :

 8 Probability of considering these motivations for recycling drugs important. Probit.The variable knowOrg= 0 if people do not know the organization and =1 if people know the organization. The variable Icomparison is a categorical variable that equals 1 if sure, 2 if probably, 3 if noway and zero for recycling respondents. Standard error in parentheses, with * indicating significance at 0.10, ** indicating significance at 0.05 and *** indicating significance at 0.001.

	Dependent variable: Protenv (1); Pollution(2); landfill (3); risk(4); energy(5); knowOrg (6)
		1	2	3	4	5	6
		Coef./se	Coef./se	Coef./se	Coef./se	Coef./se	Coef./se
	Icompariso1	0.028	0.032	0.022	-0.038	-0.003 -0.257***
		(0.08)	(0.09)	(0.07)	(0.07)	(0.05)	(0.06)
	Icompariso2	-0.253***	-0.140*	-0.151** -0.381*** -0.229*** -0.200***
		(0.10)	(0.07)	(0.07)	(0.06)	(0.08)	(0.06)
	Icompariso3	-1.548*** -1.279*** -1.187*** -1.370*** -0.867*** 0.413***
		(0.08)	(0.08)	(0.10)	(0.06)	(0.10)	(0.13)
	STrecycle	0.104	0.087 0.404***	0.127**	0.129** 0.305***
		(0.09)	(0.07)	(0.05)	(0.05)	(0.06)	(0.07)
	Hrecycle	0.149*** 0.244***	0.146**	-0.023	0.066 0.259***
		(0.04)	(0.03)	(0.06)	(0.06)	(0.08)	(0.05)
	knowOrg	0.124 0.318*** 0.271***	0.047 0.111***
		(0.09)	(0.08)	(0.09)	(0.05)	(0.04)
	Age	0.002	0.004**	-0.006**	-0.003	-0.000 0.012***
		(0.00)	(0.00)	(0.00)	(0.00)	(0.00)	(0.00)
	sizehousehold	0.012	0.015	0.010	-0.012	0.003	0.045**
		(0.02)	(0.02)	(0.03)	(0.03)	(0.01)	(0.02)
	r2
	N	5012	5068	5184	5234	5268	5276
	Campaign fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
	Departement fixed effect	Yes	Yes	Yes	Yes	Yes	Yes

This is a way of formalizing advertising in the behavioral decision-making and economics of advertising literature[START_REF] Bertrand | What's advertising content worth? evidence from a consumer credit marketing field experiment[END_REF]

The role of different messages of environmental campaigns, informative versus persuasive, to induce a proenvironmental behavior on the individual behavior is well established in the literature of social psychology.

For year 2020 there are more than 2000 respondents because Cyclamed carried out also interviews by internet. The previous interviews (year 2017-2019 were conducted by telephone.

It could be indeed considered more costly to recycle drugs, pulps and batteries, because people have to go to the "appropriate" place and find the information about this place.

The Survey is conducted at the beginning of each year

We aggregate the answers "Probably not" and "Not for sure", to consider the difference between respondents that would like to change their behavior with respect to those that would not.

In this study, the last motivation can be considered as a measure of an extrinsic motivation of drugs recycling, while the others as a measure of an intrinsic motivation.

Here, we make the difference between individuals replying "Yes" with respect to those replying "No".