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

Artikel

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 3 ; Year: 2015 ; Issue: 4 ; Pages: 761-796 ; Basel: MDPI

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Hypothesis Testing: General ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
• Thema: individual random effects ; spatial error correlation ; spatial lag dependence ; lagrange multiplier (LM) test ; (robust) LM test

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): He, Ming ; Lin, Kuan-Pin
• Ereignis: Veröffentlichung
• (wer): MDPI
• (wo): Basel
• (wann): 2015

Weitere Informationen

• DOI: doi:10.3390/econometrics3040761
• Handle: http://hdl.handle.net/10419/171856
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ