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Inference in Unbalanced Panel Data Models with Interactive Fixed Effects

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  • Daniel Czarnowske
  • Amrei Stammann

Abstract

In this article, we study the limiting behavior of Bai (2009)'s interactive fixed effects estimator in the presence of randomly missing data. In extensive simulation experiments, we show that the inferential theory derived by Bai (2009) and Moon and Weidner (2017) approximates the behavior of the estimator fairly well. However, we find that the fraction and pattern of randomly missing data affect the performance of the estimator. Additionally, we use the interactive fixed effects estimator to reassess the baseline analysis of Acemoglu et al. (2019). Allowing for a more general form of unobserved heterogeneity as the authors, we confirm significant effects of democratization on growth.

Suggested Citation

  • Daniel Czarnowske & Amrei Stammann, 2020. "Inference in Unbalanced Panel Data Models with Interactive Fixed Effects," Papers 2004.03414, arXiv.org.
    • Handle: RePEc:arx:papers:2004.03414
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    References listed on IDEAS

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