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Estimation of Treatment Effects in Repeated Public Goods Experiments

by Jianning Kong 1 and Donggyu Sul 2,*
School of Economics, Shandong University, Shandong 250100, China
School of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, TX 75080, USA
Author to whom correspondence should be addressed.
Econometrics 2018, 6(4), 43;
Received: 16 February 2018 / Revised: 9 October 2018 / Accepted: 26 October 2018 / Published: 29 October 2018
(This article belongs to the Special Issue Celebrated Econometricians: Peter Phillips)
This paper provides a new statistical model for repeated voluntary contribution mechanism games. In a repeated public goods experiment, contributions in the first round are cross-sectionally independent simply because subjects are randomly selected. Meanwhile, contributions to a public account over rounds are serially and cross-sectionally correlated. Furthermore, the cross-sectional average of the contributions across subjects usually decreases over rounds. By considering this non-stationary initial condition—the initial contribution has a different distribution from the rest of the contributions—we model statistically the time varying patterns of the average contribution in repeated public goods experiments and then propose a simple but efficient method to test for treatment effects. The suggested method has good finite sample performance and works well in practice. View Full-Text
Keywords: repeated public goods games; asymptotic treatment effects; trend regression repeated public goods games; asymptotic treatment effects; trend regression
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Kong, J.; Sul, D. Estimation of Treatment Effects in Repeated Public Goods Experiments. Econometrics 2018, 6, 43.

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