Estimation and Inference in Large Heterogenous Panels with Cross Section Dependence

By M. Pesaran. Social Science Research Network, 2003

211 citations recorded by the source corpus.

This paper presents a new approach to estimation and inference in panel data models with unobserved common factors possibly correlated with exogenously given individual-specific regressors and/or the observed common effects. The basic idea behind the proposed estimation procedure is to filter the individual-specific regressors by means of (weighted) cross-section aggregates such that asymptotically as the cross-section dimension (N) tends to infinity the differential effects of unobserved commond factors are eliminated. The estimation procedure has the advantage that it can be computed by OLS applied to an auxiliary regression where the observed regressors are augmented by cross sectional averages of the dependent variable and the individual specific regressors. It is shown that the proposed correlated common effects (CCE) estimators for the individual-specific regressors (and its pooled counterpart) are asymptotically unbiased as N approaches infinity, both when T (the time-series dimension) is fixed, and when N and T tend to infinity jointly. A generalization of these results to multi-factor structures is also provided. The estimation and inference in dynamic heterogenous panels with a residual factor structure will be addressed in a companion paper.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/9d36eacfb2f6b8c9998440fcea8a8855c9dd638b

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In Economics and Econometrics

Citations in the corpus

A simple panel unit root test in the presence of cross-section dependence (2007, unknown): “Then following the line of reasoning in Pesaran (2006), the common factor ft can be proxied by the cross-section mean of yit, namely yt D N 1 ∑N jD1 yjt, and its lagged value(s), yt 1, yt 2, . . . for N sufficiently large.”
Income inequality, human capital, natural resource abundance, and ecological footprint in ECOWAS member countries (2021, unknown): “Unit root properties (Pesaran, 2003, 2007 including crude oil, gas and minerals such as gold and bauxite in commercial quantities.”
Panel data analysis—advantages and challenges (2007, unknown): “=( f1t ,...,f rt). Pesaran (2004, 2005) suggests a simple”
Random Coefficient Panel Data Models (2004, background): “…model cross section dependence include Holtz-Eakin, Newey, and Rosen (1988), Ahn, Lee and Schmidt (2001), Robertson and Symons (2000), Bai and Ng (2002), Coakley, Fuertes and Smith (2002), Pesaran (2002, 2003), Phillips and Sul (2002), Moon and Perron (2003), and Moon, Perron and Phillips (2003).”
A bootstrap procedure for panel data sets with many cross‐sectional units (2008, unknown): “Pesaran (2002), whose Monte Carlo experiments are very similar to ours.”
General Diagnostic Tests for Cross Section Dependence in Panels (2020, unknown): “and using (10), (15), ( 16 ) it is easily seen that the denominator of (19) is equal to 1+ op(1) (as T and N →∞ ). Hence, using these results in (7), and after some algebra we obtain”