Diagnostic Tests of Cross Section Independence for Nonlinear Panel Data Models
نویسنده
چکیده
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. JEL C12, C33, C35
منابع مشابه
Diagnostic Tests of Cross Section Independence for Limited Dependent Variable Panel Data Models∗
This paper considers the problem of testing for cross section independence in limited dependent variable panel data models. It derives a Lagrangian multiplier (LM) test and shows that in terms of generalized residuals of Gourieroux, Monfort, Renault and Trognon (1987) it reduces to the LM test of Breusch and Pagan (1980). Due to the tendency of the LM test to over-reject in panels with large N ...
متن کاملA New Diagnostic Test for Cross–Section Independence in Nonparametric Panel Data Models
In this paper, we propose a new diagnostic test for residual cross–section independence in a nonparametric panel data model. The proposed nonparametric cross–section dependence (CD) test is a nonparametric counterpart of an existing parametric CD test proposed in Pesaren (2004) for the parametric case. We establish an asymptotic distribution of the proposed test statistic under the null hypothe...
متن کاملA New Diagnostic Test for Cross–Section Uncorrelatedness in Nonparametric Panel Data Models
In this paper, we propose a new diagnostic test for residual cross–section uncorrelatedness in a nonparametric panel data model. The proposed nonparametric cross– section uncorrelatedness (CU) test is a nonparametric counterpart of an existing parametric cross–section dependence (CD) test proposed in Pesaran (2004) for the parametric case. We establish asymptotic distributions of the proposed t...
متن کاملGeneral Diagnostic Tests for Cross Section Dependence in Panels
General Diagnostic Tests for Cross Section Dependence in Panels This paper proposes simple tests of error cross section dependence which are applicable to a variety of panel data models, including stationary and unit root dynamic heterogeneous panels with short T and large N. The proposed tests are based on average of pair-wise correlation coefficients of the OLS residuals from the individual r...
متن کامل