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Incidental Parameters Problem in Panel Data Models

In: HIGH-DIMENSIONAL ECONOMETRICS AND IDENTIFICATION

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  • Chihwa Kao
  • Long Liu

Abstract

One great opportunity that panel data offers us is the ability to control for unobserved heterogeneity through including individual effects and time effects. In this chapter, we consider the fixed effects approach to treat the unobserved heterogeneity as parameters to be estimated, therefore allows arbitrary correlation between the unobserved heterogeneity and the regressors. However, estimation of the unobserved heterogeneity also brings in the incidental parameters problem. This chapter discusses the incidental parameters problem in the context of a dynamic panel model under different setups. In Sec. 5.1, we use Neyman and Scott (1948) to illustrate the incidental parameters problem. In Sec. 5.2, we first explain the Nickell bias and then explore different asymptotic results under stationary and nonstationary panels. In Sec. 5.3, we further introduce time effects and consider different cases where individual effects and time effects are additive. Section 5.4 concludes. For nonlinear panels with incidental parameters, see Arellano and Bonhomme (2011), Fernández-Val and Weidner (2018), and Kao and Wang (2019) for reviews…

Suggested Citation

  • Chihwa Kao & Long Liu, 2019. "Incidental Parameters Problem in Panel Data Models," World Scientific Book Chapters, in: HIGH-DIMENSIONAL ECONOMETRICS AND IDENTIFICATION, chapter 5, pages 129-153, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789811200168_0005
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    Keywords

    Large Dimensional; Large Panel; Identification; High-Dimensional Econometrics; Econometrics; Statistics; True Signal; High-Dimensional Data; Panel Data Model; Panel Data; Panel Spurious Regressions; Autocorrelation Parameter; Dynamic Linear Panels; Incidental Parameters;
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    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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