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Testing in a Random Effects Panel Data Model with Spatially Correlated Error Components and Spatially Lagged Dependent Variables

Ming He () and Kuan-Pin Lin ()
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Ming He: Department of Economics, University of Washington, Seattle, WA 98195, USA
Kuan-Pin Lin: Department of Economics, Portland State University, Portland, OR 97201, USA

Econometrics, 2015, vol. 3, issue 4, 1-36

Abstract: We propose a random effects panel data model with both spatially correlated error components and spatially lagged dependent variables. We focus on diagnostic testing procedures and derive Lagrange multiplier (LM) test statistics for a variety of hypotheses within this model. We first construct the joint LM test for both the individual random effects and the two spatial effects (spatial error correlation and spatial lag dependence). We then provide LM tests for the individual random effects and for the two spatial effects separately. In addition, in order to guard against local model misspecification, we derive locally adjusted (robust) LM tests based on the Bera and Yoon principle (Bera and Yoon, 1993). We conduct a small Monte Carlo simulation to show the good finite sample performances of these LM test statistics and revisit the cigarette demand example in Baltagi and Levin (1992) to illustrate our testing procedures.

Keywords: individual random effects; spatial error correlation; spatial lag dependence; lagrange multiplier (LM) test; (robust) LM test (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2015
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