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Estimation of Treatment Effects in Repeated Public Goods Experiments

by Jianning Kong 1 and Donggyu Sul 2,*
1
School of Economics, Shandong University, Shandong 250100, China
2
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; https://doi.org/10.3390/econometrics6040043
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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