Do you know your biases? A Monte Carlo analysis of dynamic panel data estimators

Vadim Kufenko and Klaus Prettner

Department of Economics Working Papers from Vienna University of Economics and Business, Department of Economics

Abstract: We assess the performance of widely-used dynamic panel data estimators based on Monte Carlo simulations of a dynamic economic process. Knowing the true underlying coefficient of the autoregressive term, we show that most estimators exhibit a severe bias even in the absence of measurement errors, omitted variables, and endogeneity issues. We analyze how the bias changes with the sample size, the autoregressive coefficient, and the estimation options. Based on our insights, we recommend i) carefully choosing appropriate estimators given the underlying structure of the data and ii) scrutinizing the estimation results based on the insights of simulation studies.

Keywords: Theory-Based Monte Carlo Simulation; Dynamic Panel Data Estimators; Estimator Bias; Robustness of Empirical Results (search for similar items in EconPapers)
JEL-codes: C10 C13 C33 C52 C53 O47 (search for similar items in EconPapers)
Date: 2021-09
New Economics Papers: this item is included in nep-ecm, nep-isf and nep-ore
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Working Paper: Do you know your biases? A Monte Carlo analysis of dynamic panel data estimators (2021)
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