Incidental Parameters Problem in Panel Data Models
Chihwa Kao and
Long Liu
Chapter 5 in High-Dimensional Econometrics and Identification, 2019, pp 129-153 from World Scientific Publishing Co. Pte. Ltd.
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…
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 (search for similar items in EconPapers)
JEL-codes: C01 C1 (search for similar items in EconPapers)
Date: 2019
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