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Large panel data models with cross-sectional dependence: a survey

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  • Alexander Chudik
  • M. Hashem Pesaran

Abstract

This paper provides an overview of the recent literature on estimation and inference in large panel data models with cross-sectional dependence. It reviews panel data models with strictly exogenous regressors as well as dynamic models with weakly exogenous regressors. The paper begins with a review of the concepts of weak and strong cross-sectional dependence, and discusses the exponent of cross-sectional dependence that characterizes the different degrees of cross-sectional dependence. It considers a number of alternative estimators for static and dynamic panel data models, distinguishing between factor and spatial models of cross-sectional dependence. The paper also provides an overview of tests of independence and weak cross-sectional dependence.

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Bibliographic Info

Paper provided by Federal Reserve Bank of Dallas in its series Globalization and Monetary Policy Institute Working Paper with number 153.

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Date of creation: 2013
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Handle: RePEc:fip:feddgw:153

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Cited by:
  1. Ruge-Leiva, Diego-Ivan, 2014. "International R&D Spillovers and Unobserved Common Shocks," MPRA Paper 56718, University Library of Munich, Germany.
  2. Westerlund, Joakim & Norkute, Milda, 2014. "A Factor Analytical Method to Interactive Effects Dynamic Panel Models with or without Unit Root," Working Papers 2014:12, Lund University, Department of Economics.
  3. Westerlund, Joakim & Reese, Simon, 2014. "Estimation of Factor-Augmented Panel Regressions with Weakly Influential Factors," Working Papers 2014:8, Lund University, Department of Economics.

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