Abstract
When designing schemes such as conditional cash transfers or payments for ecosystem services, the choice of whom to select and whom to exclude is critical. We incentivize and measure actual contributions to an environmental public good to ascertain whether being excluded from a rebate can affect contributions and, if so, whether the rationale for exclusion influences such effects. Treatments, i.e., three rules that determine who is selected and excluded, are randomly assigned. Two of the rules base exclusion on subjects’ initial contributions. The third is based upon location and the rationales are always explained. The rule that targets the rebate to low initial contributors, who have more potential to raise contributions, is the only rule that raised contributions by those selected. Yet by design, that same rule excludes the subjects who contributed the most initially. They respond by reducing their contributions even though their income and prices are unchanged.
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Notes
RESECON, Land and Resource Economics Network, is an environmental economics listserve (resecon.org).
RESECON 2013/01/24 New Forest Trends’ Ecosystem Marketplace report State of Watershed Payments 2012.
The labels given here for these rules are characterizations that we feel are descriptive for the reader. We did not use them with the participants so as not to generate any signals about expected behavior (script available on request).
We tried to have the subjects link the rebate directly to their decision, i.e., not see this as seed money or as matching funds (as discussed in, e.g., List and Lucking-Reiley 2002). Thus, the refunded money was handed to the subjects (unlike what is done within a matching-donation setup). This may bring us closer to the operational feel or framing of conservation payment programs (see Eckel and Grossman 2003 on the importance of framing).
REDD+ stands for Reduced Emissions from Deforestation and Forest Degradation and the plus adds conservation to the mix. This is a key strategy to reduce emissions resulting from land use change and deforestation. For more information, see: https://unfccc.int/land_use_and_climate_change/redd/items/7377.php.
Two databases were used for the sampling frame: (1) all 2011 applications received before May 2011 by the National Forestry Financing Fund (FONAFIFO), the authority responsible for payments for ecosystem services program in Costa Rica and (2) a farm census from 2006 and 2007 by the Ministry of Livestock and Agriculture (MAG).
Due to lack of socio-economic data on the general population of landowners in Costa Rica, it is not possible to formally prove that our sample is representative of the country. Still, given the carefully constructed databases and protocols used to contact landowners, we are confident our sample is as representative as feasible.
List (2008) discusses informed consent in the social sciences. We did not ask for consent to be in an experiment, as we wanted to observe behavior in a setting that was as realistic as possible. The experiment certainly met all ethical norms: anonymity, no additional risk, and while there were no direct research benefits, direct payments were given and ideally societal benefit from increased knowledge occurs from the result of this research.
The enumerator observed the contributions, thus an “experimental demand effect” might affect contributions (e.g., Hoffman et al. 1996; Zizzo 2010). However, the difference-in-difference approach addresses this issue. Moreover, our enumerators were carefully trained not to hint what constituted appropriate behavior.
For the exact wording, the original script in Spanish (and/or the English translation) is available on request.
Between-subject comparisons are tested using parametric statistical tests (t-test). However, to account for the small sample size, we also run non-parametric tests (i.e., the Mann-Whitney test) and find similar results to those discussed here.
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Acknowledgments
We are grateful for valuable comments from two anonymous referees, and from Paul Ferraro, Olof Johansson-Stenman, Mattias Sutter, Peter Martinsson, Martin Kocher, Louis Preonas, and participants in seminars at University of Costa Rica, University of Gothenburg, Columbia University, AERE conference, EfD Initiative, EAERE conference, and EEA meeting. Financial support from the Tinker Foundation for this project is gratefully acknowledged, as is support from Sida to the Environmental Economics Unit at the University of Gothenburg and to CATIE through the Environment for Development Initiative and funding from CRED, and the NSF DMUU center at Columbia University.
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Alpízar, F., Nordén, A., Pfaff, A. et al. Unintended Effects of Targeting an Environmental Rebate. Environ Resource Econ 67, 181–202 (2017). https://doi.org/10.1007/s10640-015-9981-2
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DOI: https://doi.org/10.1007/s10640-015-9981-2