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Diagnostic Tests of Cross Section Independence for Nonlinear Panel Data Models

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Author Info
Cheng Hsiao () (University of Southern California)
M. Hashem Pesaran () (CIMF, Cambridge University, University of Southern California and IZA)
Andreas Pick () (CIMF, Cambridge University)

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Abstract

In this paper we discuss tests for residual cross section dependence in nonlinear panel data models. The tests are based on average pair-wise residual correlation coefficients. In nonlinear models, the definition of the residual is ambiguous and we consider two approaches: deviations of the observed dependent variable from its expected value and generalized residuals. We show the asymptotic consistency of the cross section dependence (CD) test of Pesaran (2004). In Monte Carlo experiments it emerges that the CD test has the correct size for any combination of N and T whereas the LM test relies on T large relative to N. We then analyze the roll-call votes of the 104th U.S. Congress and find considerable dependence between the votes of the members of Congress.

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Publisher Info
Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 2756.

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Length: 21 pages
Date of creation: Apr 2007
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Handle: RePEc:iza:izadps:dp2756

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Related research
Keywords: cross-section dependence; nonlinear panel data model;

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data
C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models

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This page was last updated on 2009-12-14.


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