Estimation and Inference for Spatial Models with Heterogeneous Coefficients: An Application to U.S. House Prices

69 Pages Posted: 18 Mar 2019

See all articles by Michele Aquaro

Michele Aquaro

European Commission, Joint Research Centre

Natalia Bailey

Monash University

M. Hashem Pesaran

University of Southern California - Department of Economics

Multiple version iconThere are 2 versions of this paper

Date Written: 2019

Abstract

This paper considers the problem of identification, estimation and inference in the case of spatial panel data models with heterogeneous spatial lag coefficients, with and without (weakly) exogenous regressors, and subject to heteroskedastic errors. A quasi maximum likelihood (QML) estimation procedure is developed and the conditions for identification of spatial coefficients are derived. Regularity conditions are established for the QML estimators of individual spatial coefficients, as well as their means (the mean group estimators), to be consistent and asymptotically normal. Small sample properties of the proposed estimators are investigated by Monte Carlo simulations for Gaussian and non-Gaussian errors, and with spatial weight matrices of differing degrees of sparsity. The simulation results are in line with the paper's key theoretical findings even for panels with moderate time dimensions, irrespective of the number of cross section units. An empirical application to U.S. house price changes during the 1975-2014 period shows a significant degree of heterogeneity in spill-over effects over the 338 Metropolitan Statistical Areas considered.

Keywords: spatial panel data models, heterogeneous spatial lag coefficients, identification, quasi maximum likelihood (QML) estimators, non-Gaussian errors, house price changes, Metropolitan Statistical Areas

JEL Classification: C210, C230

Suggested Citation

Aquaro, Michele and Bailey, Natalia and Pesaran, M. Hashem, Estimation and Inference for Spatial Models with Heterogeneous Coefficients: An Application to U.S. House Prices (2019). CESifo Working Paper No. 7542, Available at SSRN: https://ssrn.com/abstract=3352906 or http://dx.doi.org/10.2139/ssrn.3352906

Michele Aquaro (Contact Author)

European Commission, Joint Research Centre ( email )

Via E. Fermi 2749
Ispra (VA), 21027
Italy

Natalia Bailey

Monash University ( email )

23 Innovation Walk
Wellington Road
Clayton, Victoria 3800
Australia

M. Hashem Pesaran

University of Southern California - Department of Economics ( email )

3620 South Vermont Ave. Kaprielian (KAP) Hall 300
Los Angeles, CA 90089
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
115
Abstract Views
685
Rank
134,402
PlumX Metrics