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

Vossler, Christian A. (2009): Analyzing repeated-game economics experiments: robust standard errors for panel data with serial correlation.

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 (

• Item Type: MPRA Paper
• Language: English
• Keywords: applied econometrics; laboratory experiments; monte carlo simulations; robust inference
• Subjects: C - Mathematical and Quantitative Methods > C9 - Design of Experiments; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General; C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C33 - Panel Data Models ; Spatio-temporal Models

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