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Analyzing repeated-game economics experiments: robust standard errors for panel data with serial correlation

Listed author(s):
  • Vossler, Christian A.

The purpose of this study is to provide guidance to those who analyze data from repeated-game experiments. In particular, I propose the use of heteroskedasticity-autocorrelation consistent (HAC) covariance estimators for panel data, which allows researchers to conduct hypothesis tests without having to place structure on the heteroskedasticity and/or serial correlation likely present in econometric models. Through Monte Carlo experiments I explore the properties of three panel HAC covariance estimators within a linear regression framework, including a new HAC covariance estimator proposed in this study, for a range of cross-section (

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File URL: https://mpra.ub.uni-muenchen.de/38862/1/MPRA_paper_38862.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 38862.

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Date of creation: Jan 2009
Handle: RePEc:pra:mprapa:38862
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  5. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
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  7. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
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  9. Donald W.K. Andrews, 1988. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Cowles Foundation Discussion Papers 877R, Cowles Foundation for Research in Economics, Yale University, revised Jul 1989.
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  16. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291, December.
  17. Nava Ashraf & Iris Bohnet & Nikita Piankov, 2006. "Decomposing trust and trustworthiness," Experimental Economics, Springer;Economic Science Association, vol. 9(3), pages 193-208, September.
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