Bootstrap J-Test for Panel Data Models with Spatially Dependent Error Components, a Spatial Lag and Additional Endogenous Variables. Issue 1 (2nd January 2016)

• Record Type: Journal Article
• Authors: Fingleton, Bernard; Palombi, Silvia
• Is Part Of: Spatial economic analysis. Volume 11:Issue 1(2016)
• Page Start: 7
• Page End: 26
• Publication Date: 2016-01-02
• Subjects: Spatial econometrics -- panel data -- J-test -- bootstrap; C01 -- C12 -- C23 -- C52; Space in economics -- Periodicals; Economic geography -- Periodicals; Space in economics -- Econometric models -- Periodicals; Urbanization -- Periodicals; Espace (Économie politique) -- Périodiques; Économétrie -- Périodiques; Géographie économique -- Périodiques; Économie industrielle -- Périodiques; Économie du travail -- Périodiques; Économie urbaine -- Périodiques; Politique économique -- Périodiques; Relations économiques internationales -- Périodiques; 330.9
• DOI: 10.1080/17421772.2016.1102960
• Languages: English
• ISSNs: 1742-1772

Abstract

Abstract: We develop a bootstrap J -test method for testing a panel model against one non-nested alternative when the competing specifications are estimated by Feasible Generalised Spatial Two Stage Least Squares/Generalised Method of Moments (FGS2SLS/GMM). Both models incorporate spatially correlated error components, thus accounting for spatial heterogeneity via random effects, and accommodate endogenous regressors other than the spatially lagged dependent variable. The proposed scheme is applied to a testing problem involving non-nested wage equations as motivated by the Wage Curve literature and the New Economic Geography theory. Results show that our bootstrap test is a reliable and effective procedure for correcting asymptotic reference critical values and distinguishing between the two rival hypotheses.