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A Two-Stage Approach to Spatio-Temporal Analysis with Strong and Weak Cross-Sectional Dependence

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Bailey, N 
Holly, S 
Pesaran, MH 

Abstract

jats:titleSummary</jats:title>jats:pAn understanding of the spatial dimension of economic and social activity requires methods that can separate out the relationship between spatial units that is due to the effect of common factors from that which is purely spatial even in an abstract sense. The same applies to the empirical analysis of networks in general. We use cross‐unit averages to extract common factors (viewed as a source of strong cross‐sectional dependence) and compare the results with the principal components approach widely used in the literature. We then apply multiple testing procedures to the de‐factored observations in order to determine significant bilateral correlations (signifying connections) between spatial units and compare this to an approach that just uses distance to determine units that are neighbours. We apply these methods to real house price changes at the level of Metropolitan Statistical Areas in the USA, and estimate a heterogeneous spatio‐temporal model for the de‐factored real house price changes and obtain significant evidence of spatial connections, both positive and negative. Copyright © 2015 John Wiley & Sons, Ltd.</jats:p>

Description

Keywords

38 Economics, 3801 Applied Economics

Journal Title

Journal of Applied Econometrics

Conference Name

Journal ISSN

0883-7252
1099-1255

Volume Title

31

Publisher

Wiley

Rights

All rights reserved
Sponsorship
Economic and Social Research Council (ES/I031626/1)
ESRC Grant. Grant Number: ES/I031626/1