Abstract
Standard economic theory predicts that, when the donation price and all other factors are equal, there should be no difference in individuals’ donation behavior under matching and rebate schemes. For example, a 1:1 matching is equivalent to a 50% rebate. In the former scheme, when one chooses to donate 5000 JPY to a charity, the same amount will be added to this donation, thus making the total amount donated to the charity 10,000 JPY. In the latter scheme, when one chooses to donate 10,000 JPY to a charity, half of the amount will be refunded, making the actual donation expenditure 5000 JPY. Similarly, a 2:1 matching is equivalent to a 33% rebate, and a 4:1 matching is equivalent to a 20% rebate. However, Eckel and Grossman (2003) experimentally reveal that donation rates and average donation expenditures for matching are higher than for rebate. Sasaki, Kurokawa, and Ohtake (2021) use a Japanese nationwide sample and report the findings consistent with Eckel and Grossman (2003).
This study’s purpose is to determine in a randomized controlled trial how treatment effects of matching and rebate change when people can self-select whether to use such schemes or not. Most traditional policy research using randomized controlled trials has measured the causal effects of mandatory policy assignment. However, implementing a policy intervention in a mandatory manner is rare in the real world. This is because mandatory implementation requires a system that enables a policy to be applied to all individuals involved and monitors their adherence to it. Also, a policy must be made mandatory by law, and implementation costs tend to be extremely high. In practice, policies are often applied to only those who choose to accept them, in particular by employing an opt-in scheme, where a policy is not applied by default, but rather only upon request.
Under conditions with self-selection, overall policy impacts will vary depending on the heterogeneous effects across individuals and which individuals self-select to receive the policy. For example, if a policy is widely accepted by people for whom a large (or significant) positive policy effect appears, the overall policy impact will become larger than if the policy intervention was mandated, and thus the policy function more efficiently due to self-selection. Conversely, if those who are likely to experience small or negative effects choose to receive a policy intervention, the overall policy impact will become relatively small, and self-selection will prevent it from functioning efficiently. To accurately understand the real-world implications of policy interventions, it is essential to ascertain the influence of self-selection on policy efficiency. Recent field experimental studies have begun to measure policy intervention effects after considering self-selection, particularly in electricity markets (Wang et al. 2020; Fowlie et al. 2021; Ito et al. 2021; Ida et al. 2022).
This study adds to this emerging literature stream new evidence in the context of charitable giving by measuring the treatment effects of matching and rebate, while considering self-selection.
References:
- Eckel, C.C., & Grossman, P.J. (2003). Rebate versus matching: does how we subsidize charitable contributions matter?. Journal of Public Economics, 87(3-4), 681-701.
- Fowlie, M., Wolfram, C., Baylis, P., Spurlock, C. A., Todd-Blick, A., & Cappers, P. (2021). Default effects and follow-on behaviour: evidence from an electricity pricing program. The Review of Economic Studies, 88(6), 2886–2934.
- Ida, T., Ishihara, T., Ito, K., Kido, D., Kitagawa, T., Sakaguchi, S., & Sasaki, S. (2022). Choosing who chooses: selection-driven targeting in energy rebate programs. National Bureau of Economic Research. (No. w30469).
- Ito, K., Ida, T., & Tanaka, M. (2021). Selection on welfare gains: experimental evidence from electricity plan choice. National Bureau of Economic Research. (No. w28413).
- Sasaki, S., Kurokawa, H., & Ohtake, F. (2022). An experimental comparison of rebate and matching in charitable giving: The case of Japan. The Japanese Economic Review, 73(1), 147-177.
- Wang, W., Ida, T., & Shimada, H. (2020). Default effect versus active decision: evidence from a field experiment in Los Alamos. European Economic Review, 128, 103498.