testing in a random effects panel data model with spatially correlated error components and spatially lagged dependent variables

Clicks: 143
ID: 231712
2015
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Ranked #29 of 36 articles by views in developmental cognitive neuroscience

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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.
Reference Key
he2015econometricstesting Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Ming He;Kuan-Pin Lin
Journal developmental cognitive neuroscience
Year 2015
DOI
10.3390/econometrics3040761
URL
Keywords Keywords not found

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