Abstract
Individual subsidy payments that are conditional on a collective contribution threshold could provide a viable resolution to the insufficient and dispersed adoption of agri-environmental contracts aiming at attaining environmental quality targets. Indeed, in a decontextualized laboratory experiment based on a threshold public goods game (TPGG), Le Coent et al. (2014) offer promising results regarding a conditional subsidy compared to an unconditional subsidy (i.e., the standard subsidy in existing agri-environmental schemes). In this article, we propose to improve the external validity of these results by transposing this laboratory experiment to a lab-in-the-field setting with farmers. To do so, we carry out a contextualized lab-in-the-field experiment with farmers by explicitly mentioning agri-environmental contracts and water quality. Our results show that farmers cooperate even more successfully than students and sustain more efficient outcomes over time. In a between-subject comparison, our results indicate that average group contributions under the conditional and the unconditional subsidy mechanisms are not significantly different. We find that this is due to two behavioral responses (perceived risks and initial beliefs on others’ contributions) in the conditional subsidy treatment, which show to have opposing effects on contributions that cancel each other out. The conditional incentive mechanism thus shows promising potential as a tool for agri-environmental policy since it avoids the pay-for-nothing trap of the unconditional subsidy mechanism without discouraging contributions.
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Data is available upon request from the authors.
Code availability
Code is available upon request from the authors.
Notes
Rebate rules are used to compensate subjects for their excess contributions when aggregate contributions are above the threshold.
It would be interesting to study the impact of the introduction of a conditional subsidy in a context in which an unconditional subsidy already exists. Unfortunately, we did not run the necessary control treatment sequence with unconditional subsidy in both successive sequences to control for potential order effects or learning impact across sequences.
References
Alekseev, A., Charness, G., & Gneezy, U. (2017). Experimental methods: When and why contextual instructions are important. Journal of Economic Behaviour and Organization, 134, 48–59.
Barbut, L., & Baschet, J. F. (2005). L’évaluation de la politique de soutien à l’agroenvironnement. Notes et Études Économiques, 22, 37–68.
Bchir, M. A. (2014). From the lab to the field: An experimental investigation of the provision of a club good. Journal of Behavioral and Experimental Economics, 51, 57–67.
Benz, M., & Meier, S. (2008). Do people behave in experiments as in the field?—Evidence from donations. Experimental Economics, 11(3), 268–281.
Bocquého, G., Jacquet, F., & Reynaud, A. (2014). Expected utility or prospect theory maximisers? Assessing farmers’ risk behaviour from field-experiment data. European Review of Agricultural Economics, 41(1), 135–172.
Cadsby, C. B., & Maynes, E. (1998). Choosing between a socially efficient and free-riding equilibrium: Nurses versus economics and business students. Journal of Economic Behavior & Organization, 37(2), 183–192.
Camerer, C. (2011). The promise and success of lab-field generalizability in experimental economics: A critical reply to Levitt and List. Available at SSRN 1977749.
Cour des Comptes Européenne. (2011). L’aide agro-environnementale est-elle conçue et gérée de manière satisfaisante? Rapport special n°7, 83.
Dessart, F., Barreiro-Hurlé, J., & van Bavel, R. (2019). Behavioural factors affecting the adoption of sustainable farming practices: A policy-oriented review. European Review of Agricultural Economics, 46(3), 417–471.
Drichoutis, A. C., & Koundouri, P. (2012). Estimating risk attitudes in conventional and artefactual lab experiments: The importance of the underlying assumptions. Economics, 6(1).
Dupraz, P., Latouche, K., & Turpin, N. (2007). Programmes agri-environnementaux en présence d’effets de seuils. Cahiers d’Economie et de Sociologie Rurales, 82–83, 6–32.
Dupraz, P., Latouche, K., & Turpin, N. (2009). Threshold effect and co-ordination of agrienvironmental efforts. Journal of Environmental Planning and Management, 52(5), 613–630.
Engel, C., & Rand, D. G. (2014). What does “clean” really mean? The implicit framing of decontextualized experiments. Economics Letters, 122(3), 386–389.
Fischbacher, U., & Gächter, S. (2010). Social preferences, beliefs, and the dynamics of free riding in public goods experiments. American Economic Review, 100(1), 541–556.
Frey, B. S., & Meier, S. (2004). Social comparisons and pro-social behavior: Testing” conditional cooperation” in a field experiment. American Economic Review, 94(5), 1717–1722.
Greiner, B. (2004). An online recruitment system for economic experiments. In Forschung und wissenschaftliches Rechnen 2003. GWDG Bericht, No. 63, pp. 79–93.
Grüner, S., Lehberger, M., Hirschauer, N., & Musshoff, O. (2022). How (un-)informative are experiments with “standard subjects” for other social groups? - The case of agricultural students and farmers. Australian Journal of Agricultural and Resource Economics, 66(3), 471–504.
Harrison, G. W., & List, J. A. (2004). Field experiments. Journal of Economic Literature, 42(4), 1009–1055.
Holt, C. A., & Laury, S. K. (2002). Risk aversion and incentive effects. American Economic Review, 92(5), 1644–1655.
Isaac, R. M., Schmidtz, D., & Walker, J. M. (1989). The assurance problem in a laboratory market. Public Choice, 62(3), 217–236.
Kuhfuss, L., Préget, R., Thoyer, S., & Hanley, N. (2016). Nudging farmers to enrol land into agrienvironmental schemes: The role of a collective bonus. European Review of Agricultural Economics, 43(4), 609–636.
Le Coent, P., Préget, R., & Thoyer, S. (2014). Why pay for nothing? An experiment on a conditional subsidy scheme in a threshold public good game. Economics Bulletin, 34(3), 1976–1989.
Levitt, S. D., & List, J. A. (2007a). What do laboratory experiments measuring social preferences reveal about the real world? Journal of Economic Perspectives, 21(2), 153–174.
Levitt, S. D., & List, J. A. (2007b). On the generalizability of lab behaviour to the field. Canadian Journal of Economics/Revue Canadienne d’Économique, 40(2), 347–370.
Limbach, K., & Rozan, A. (2022). Coordinating farms in collective agri-environmental schemes: The role of conditional incentives. Miméo.
List, J. A. (2007). Field experiments: A bridge between lab and naturally occurring data. The BE Journal of Economic Analysis & Policy, 6(2).
Maart-Noelck, S. C., & Musshoff, O. (2014). Measuring the risk attitude of decision-makers: Are there differences between groups of methods and persons? Australian Journal of Agricultural and Resource Economics, 58(3), 336–352.
Marks, M., & Croson, R. (1998). Alternative rebate rules in the provision of a threshold public good: An experimental investigation. Journal of Public Economics, 67(2), 195–220.
Muradian, R. (2001). Ecological thresholds: A survey. Ecological Economics, 38, 7–24.
Nguyen, C., Latacz-Lohmann, U., Hanley, N., Schilizzi, S., & Iftekhar, S. (2022). Spatial coordination incentives for landscape-scale environmental management: A systematic review. Land Use Policy, 114(105936), 1–15.
Oréade-Brèche. (2005). Evaluation des mesures agro-environnementales. Rapport final. https://www.cbd.int/financial/pes/france-pesagro.pdf. Accessed 28 Oct 2022.
Perrings, C., & Pearce, D. (1994). Threshold effects and incentives for the conservation of biodiversity. Environmental & Resource Economics, 4, 13–28. https://doi.org/10.1007/BF00691930
Runge, C. F. (1984). Institutions and the free rider: The assurance problem in collective action. The Journal of Politics, 46(1), 154–181.
Saldarriaga-Isaza, A., Villegas-Palacio, C., & Arango, S. (2019). Chipping in for a cleaner technology: Experimental evidence from a framed threshold public good game with students and artisanal miners. Journal of Behavioral and Experimental Economics, 78, 10–16.
Sauter, P., Hermann, D., & Mußhoff, O. (2015). Risk attitudes of foresters, farmers and students: An experimental multimethod comparison (No. 1514). Diskussionsbeitrag.
Sen, A. (1967). Isolation, assurance and the social rate of discount. The Quaterly Journal of Economics, 81, 112–124.
Stoop, J., Noussair, C. N., & Van Soest, D. (2012). From the lab to the field: Cooperation among fishermen. Journal of Political Economy, 120(6), 1027–1056.
Thoyer, S., & Préget, R. (2019). Enriching the CAP evaluation toolbox with experimental approaches: Introduction to the special issue. European Review of Agricultural Economics, 46(3), 347–366. https://doi.org/10.1093/erae/jbz024
Uthes, S., & Matzdorf, B. (2013). (2013) Studies on agri-environmental measures: A survey of the literature. Environmental Management, 51, 251–266. https://doi.org/10.1007/s00267-012-9959-6
Viceisza, A. C. G. (2016). Creating a lab in the field: Economics experiments for policymaking. Journal of Economic Surveys, 30, 835–854.
Vollmer, E., Hermann, D., & Mußhoff, O. (2017). Is the risk attitude measured with the Holt and Laury task reflected in farmers’ production risk? European Review of Agricultural Economics, 44(3), 399–424.
Zavalloni, M., Raggi, M., & Viaggi, D. (2019). Agri-environmental policies and public goods: An assessment of coalition incentives and minimum participation rules. Environmental and Resource Economics, 72(4), 1023–1040.
Funding
Funding has been received from the Agence de l'eau Rhin-Meuse which provided financial support to the lab-in-field experiments.
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PL, RP, and ST designed and conducted the lab experiments. KL and AR adapted the experimental protocol and conducted the lab-in-field experiments. KL and RP analyzed the data and issued the first draft of the manuscript. ST and AR contributed to editing and rewriting parts of the manuscript. All authors read and approved the final manuscript.
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Appendix: instructions for the lab-in-field experiment
Appendix: instructions for the lab-in-field experiment
Instructions US-CS treatment
The experiment you are about to participate in is intended to study decisions on agricultural practices in Alsace. All your answers will be treated anonymously. You will indicate your choices on your iPad and your earnings during the experiment will be communicated to you at the end of the experiment. From now on, you are asked not to speak. If you have a question, raise your hand, and an experimenter will come and answer you privately.
During the whole experience, your earnings will be expressed in points. At the end of the experience, the total number of points you have earned will be converted into euros according to the following rule:
The experiment consists of 3 parts. Your payout for this experiment will be equal to the sum of your payout for part 1 and your payout for one of the other two parts (2 or 3). In other words, one of the last two parts will be drawn to be paid in addition to the first part.
At the end of part 3 we will summarize all the points you have earned in the different parts and we will draw a part (between part 2 and part 3). You will then be informed of your final winnings, in euros, for the experience.
In addition to the profits linked to the experience and to compensate you for your travel, a participation fee of 15 euros will be paid at the end of the experience. Before each part, you will have to answer a series of questions which aim to check your understanding of the instructions. The answers given to these questions are not taken into account in the calculation of your earnings.
Part 1
In this part, you will be asked to make a decision for each of the 10 different games. Read carefully to identify the difference between the games. For each of these games you will have to choose between A and B.
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If you choose A, you will receive a sure gain of 20.5 points.
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If you choose B, you will have a given percentage chance of receiving 40 points and a given percentage chance of receiving only 1 point. This percentage varies in the different games as shown in the table below:
Table 7
You will need to indicate your choice for each of the 10 games. Once you have made your choices, press the OK button.
Payment
To calculate your win for the part, one of the 10 games will be drawn. If you chose A for this game, you will automatically receive 20.5 points. If you chose B, your winnings will be the result of a random draw according to the announced probabilities. Your winnings will be shown at the end of the experiment.
Part 2 (sequence 1)
For this part, groups of 4 farmers are randomly formed. You cannot identify the other members of your group and they cannot identify you. Your winnings will depend on your decisions and the decisions of the other 3 members of your group.
In this part, we ask you to consider that you have 20 ha of useful agricultural area (UAA) located in a drinking water catchment area (CAA). Since each group is composed of 4 farmers, it is assumed that the CAA is 80 ha in total (4 times 20 ha). The catchment area has high nitrate concentrations. Your farming activities may have an impact on the water quality of the catchment.
You have the opportunity to change your farming practices to reduce nitrate releases. Now think of at least two practices that can reduce the amount of nitrates in groundwater that you already know about.
For simplicity, we will refer to these as low-input best practices (LIBPs). These practices can lead to a reduction in your individual profit, but they can also lead to an improvement in the water quality. These costs and benefits will be explained later.
You have the option of committing all or part of your 20 ha of UAA to LIBP, the rest of your hectares being uncommitted and devoted to conventional agriculture.
If half or more of the UAA of the CAA is committed to LIBP, i.e., 40 ha or more, then the water quality of the catchment is significantly improved, which generates a benefit for all farmers in your group.
This part consists of 10 periods. Each period has the same initial conditions. The farmers in your group will remain the same in each period until the end of the part. At the beginning of each period, you and the 3 other farmers in your group are each allocated 20 ha located in the CAA. At each period, you have the possibility of committing all or part of your 20 ha to LIBP to improve the water quality of the catchment. The uncommitted hectares remain in conventional agriculture. You are free to commit any whole number of hectares between 0 and 20.
Payment
Each hectare not involved in LIBP earns you 1 point. Thus, if you maintain 6 ha of your UAA as is, your gain is 6 points and you alone earn these 6 points.
If 40 ha or more are committed to LIBP at the level of the CAA, then the water quality of the catchment is improved, and each hectare committed to LIBP (by you or one of the farmers in your group) yields a benefit of 0.3 points to each of the farmers in the CAA (see Table 9: earnings table). If the converted area is less than 40 ha, then the water quality improvement is not sufficient and no points are earned by anyone.
A subsidy mechanism is based on the number of hectares individually committed to LIBP. The subsidy amount is 0.3 points per hectare that you commit to LIBP, regardless of whether you reach the 40-ha threshold. The table in Table 10 allows you to calculate your subsidy based on the number of hectares committed.
Example 1
You decide to engage 12 ha of your UAA in LIBP, so 8 ha of this area remains associated with conventional practices. Let us assume that the 3 other farmers in your group commit a total of 38 ha to LIBP. The total surface area committed within the catchment area thus reaches 50 ha (38 + 12). Since the 40-ha threshold is exceeded, the water quality improvement yields a benefit of 0.3 × 50 = 15 points for each farmer in the CAA.
Thus, your total gain includes these 15 points plus 8 points from the 8 uncommitted hectares (20 − 12), as well as the subsidy equal to 0.3 points per committed hectare since the threshold of 40 ha committed by the group is reached, i.e., 0.3 × 12 = 3.6 points. Your total gain for the period is therefore 26.6 points (15 + 8 + 3.6).
Example 2
You commit 8 ha of your UAA to LIBP, so 12 ha of this area remain associated with conventional practices. Let us assume that the other 3 farmers commit a total of 8 ha to LIBP. The total area committed within the catchment area is therefore 16 ha (8 + 8), and the 40-ha threshold is not reached. The improvement in water quality is not sufficient and therefore does not earn any points (benefit = 0 points).
Thus, you earn 12 points from the 12 uncommitted hectares (20 − 8), plus the subsidy equal to 0.3 points per committed hectare, i.e., 0.3 × 8 = 2.4 points. Your total gain for the period is therefore 14.4 points (12 + 2.4 + 0).
Estimated total number of hectares committed to LIBP by the other 3 farmers in the CAA
You will need to estimate the total number of hectares committed to LIBP by the other 3 farmers in the CAA each period. Your gain from this estimate depends on the difference between your estimate and the exact area actually committed by the other members of the group. The closer you are to the actual number of hectares, the higher your gain will be. Table 8 gives you your gain according to the difference between the estimate and the actual number:
Example 1
You estimated that the other 3 farmers would commit 31 hectares to LIBP. At the end of the period, it turns out that they have indeed committed 31 hectares. You therefore gain 5 points (see estimation table).
Example 2
You estimated that the other 3 farmers would commit 31 hectares to LIBP. At the end of the period, it turns out that they have committed 33 hectares. The difference between your estimate and the actual number is 2 hectares. You therefore gain 3 points (see estimation table).
Conduct of a period
Each period, you will first have to indicate on your iPad a whole number between 0 and 20 corresponding to the number of hectares that you personally decide to commit to LIBP. The hectares not committed to LIBP will then represent the remaining area devoted to conventional agriculture.
Then, you will have to write down the number of hectares that you think the three farmers in your group will commit in total to LIBP. The number must be an integer between 0 (if you think the other 3 farmers will not commit any hectares to LIBP) and 60 ha (if you think the other 3 farmers will each commit their 20 ha to LIBP).
When all the farmers have made their decision, your decision (number of hectares committed to LIBP) will be displayed on your iPad, as well as the total number of hectares committed at the level of the CAA, the amount of subsidy obtained, the amount obtained by remaining in conventional agriculture, the possible benefit linked to the improvement of the water quality of the catchment, and thus your total gains for the period.
PART 3 (Sequence 2)
The composition of the groups is identical to that of the previous part and will remain unchanged until the end of the experiment. As in part 2, at the beginning of each of the 10 periods, each farmer in the CAA has a UAA of 20 hectares that he can partially or totally commit to LIBP, for an area between 0 and 20 hectares. The gains relative to the benefit, as well as those relative to the uncommitted area, are identical to those of part 2. Annex I is therefore still used to calculate these gains.
The difference with part 2 is that the subsidy mechanism has changed. In this round, the amount of subsidy you receive is 0.3 points per hectare that you yourself have committed, only if the total area committed by the group reaches or exceeds 40 hectares. The table in Appendix II (see page 8) still allows you to calculate your subsidy based on the number of hectares committed. If the 40 hectare threshold is not reached by the group, then you will not receive the grant.
Example 1:
You decide to engage 12 hectares of your UAA in LIBP, so 8 hectares of this area remain associated with conventional practices. Let's assume that the 3 other farmers in your group commit a total of 38 hectares to LIBP. The total surface area committed within the catchment area thus reaches 50 hectares (38 + 12). Since the 40-hectare threshold is exceeded, the water quality improvement yields a benefit of 0.3 × 50 = 15 points for each farmer in the CAA.
Thus, your total gain includes these 15 points plus 8 points from the 8 uncommitted hectares (20—12), as well as the subsidy equal to 0.3 points per committed hectare since the threshold of 40 hectares committed by the group is reached, i.e. 0.3 × 12 = 3.6 points. Your total gain for the period is therefore 26.6 points (15 + 8 + 3.6).
Example 2:
You commit 8 hectares of your UAA to LIBP, so 12 hectares of this area remain associated with conventional practices. Let's assume that the other 3 farmers commit a total of 8 hectares to LIBP. The total area committed within the catchment area is then 16 hectares (8 + 8) and the threshold of 40 hectares is not reached. The benefit related to the improvement of water quality is not sufficient and therefore does not earn any points (benefit = 0 points).
Thus, your total gain is 12 points from the 12 uncommitted hectares (20—8), and the subsidy is not paid to you since the 40-hectare threshold committed by the group is not reached (subsidy = 0 points). Your total gain for the period is therefore 12 points (12 + 0 + 0).
Conduct of a period:
The progress is identical to that of part 2 (the previous part).
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Limbach, K., Rozan, A., Le Coent, P. et al. Can collective conditionality improve agri-environmental contracts? From lab to field experiments. Rev Agric Food Environ Stud 104, 311–340 (2023). https://doi.org/10.1007/s41130-023-00198-2
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DOI: https://doi.org/10.1007/s41130-023-00198-2
Keywords
- Agri-environmental schemes
- Threshold public goods game
- Collective conditionality
- Lab-in-the-field experiment