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Spatial methods

Gibbons, Stephen, Overman, Henry G. ORCID: 0000-0002-3525-7629 and Patacchini, Eleonora (2015) Spatial methods. In: Duranton, Gilles, Henderson, J. Vernon and Strange, William C., (eds.) Handbook of Regional and Urban Economics. North-Holland, Amsterdam, pp. 115-168. ISBN 9780444595171

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Identification Number: 10.1016/B978-0-444-59517-1.00003-9


This chapter is concerned with methods for analyzing spatial data. After initial discussion of the nature of spatial data, including the concept of randomness, we focus most of our attention on linear regression models that involve interactions between agents across space. The introduction of spatial variables into standard linear regression provides a flexible way of characterizing these interactions, but complicates both interpretation and estimation of parameters of interest. The estimation of these models leads to three fundamental challenges: the “reflection problem,” the presence of omitted variables, and problems caused by sorting. We consider possible solutions to these problems, with a particular focus on restrictions on the nature of interactions. We show that similar assumptions are implicit in the empirical strategies—fixed effects or spatial differencing—used to address these problems in reduced form estimation. These general lessons carry over to the policy evaluation literature.

Item Type: Book Section
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Additional Information: © 2015 Elsevier.
Divisions: Spatial Economics Research Centre
Centre for Economic Performance
What Works Centre
Geography & Environment
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HB Economic Theory
JEL classification: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling
R - Urban, Rural, and Regional Economics > R0 - General
Date Deposited: 18 Aug 2015 08:28
Last Modified: 20 Oct 2021 01:19

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