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Estimation and Inference in Heterogeneous Spatial Panels with a Multifactor Error Structure

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Publication details

JournalJournal of Econometrics
DateAccepted/In press - 11 May 2021
DateE-pub ahead of print (current) - 28 Apr 2022
DatePublished - 1 Jul 2022
Issue number1
Volume229
Number of pages25
Pages (from-to)55-79
Early online date28/04/22
Original languageEnglish

Abstract

We develop a unifying econometric framework for the analysis of heterogeneous panel data models that can account for both spatial dependence and common factors. To tackle the challenging issues of endogeneity due to the spatial lagged term and the correlation between the regressors and factors, we propose the CCEX-IV estimation procedure that approximates factors by the cross-section averages of regressors and deals with the spatial endogeneity using the internal instrumental variables. We develop the individual and Mean Group estimators, and establish their consistency and asymptotic normality. By contrast, the Pooled estimator is shown to be inconsistent in the presence of parameter heterogeneity. Monte Carlo simulations confirm that the finite sample performance of the proposed estimators is quite satisfactory. We demonstrate the usefulness of our approach with an application to the house price growth for Local Authority Districts in the UK over 1997Q1-2016Q4.

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© 2021 Published by Elsevier B.V. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy.

    Research areas

  • Spatial Dependence and Heterogeneity, Unobserved Common Factors, CCEX-IV Estimation, the UK House Price Growth, GCM Analysis.

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