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

Christian Vossler

MPRA Paper from University Library of Munich, Germany

Abstract: 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 (

Keywords: applied econometrics; laboratory experiments; monte carlo simulations; robust inference (search for similar items in EconPapers)
JEL-codes: C12 C33 C9 (search for similar items in EconPapers)
Date: 2009-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Chapter: Analyzing repeated-game economics experiments: robust standard errors for panel data with serial correlation (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:38862

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