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

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Keywords
  • C9 - Design Of Experiments
  • C12 - Hypothesis Testing: General
  • C33 - Models With Panel Data
  • Longitudinal Data
  • Spatial Time Series

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 (

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