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When does less information translate into more giving to public goods?

Billur Aksoy () and Silvana Krasteva ()
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Billur Aksoy: Rensselaer Polytechnic Institute
Silvana Krasteva: Texas A&M University

Experimental Economics, 2020, vol. 23, issue 4, No 9, 1148-1177

Abstract: Abstract This paper theoretically and experimentally investigates the impact of information provision on voluntary contributions to a linear public good with an uncertain marginal per-capita return (MPCR). Uninformed donors make contribution decisions based only on the expected MPCR (i.e. the prior distribution), while informed donors observe the realized MPCR before contributing. The theoretical analysis predicts that the impact of information on average contributions crucially depends on the generosity level of the population, modeled as a stochastic change in the pro-social preferences. In particular, a less generous population increases contributions substantially in response to good news of higher than expected MPCR and reduces contributions relatively little in response to bad news of lower than expected MPCR. The opposite is true for a more generous population. Thus, the theory predicts that information provision increases (reduces) average contributions when the population is less (more) generous. This prediction finds strong support in a two-stage lab experiment. The first stage measures subjects’ generosity in the public good game using an online experiment. The resulting measure is used to create more and less generous groups in the public good lab experiment, which varies the information provided to these groups in the lab. The findings are in line with the theoretical predictions, suggesting that targeted information provision to less generous groups may be more beneficial for public good contributions than uniform information provision.

Keywords: Information provision; Linear public good game; Other-regarding preferences; Lab experiment (search for similar items in EconPapers)
JEL-codes: H41 C72 C90 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10683-020-09643-1

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