Industrial Location and Spatial Dependence: An Empirical Application

Daniel Liviano and Josep-Maria Arauzo-Carod

Regional Studies, 2020, vol. 48, issue 4, 727-743

Abstract: Liviano D. and Arauzo-Carod J.-M. Industrial location and spatial dependence: an empirical application, Regional Studies. This paper tries to resolve some of the main shortcomings in the empirical literature on location decisions for new plants, that is, spatial effects and over-dispersion. Spatial effects are omnipresent, being a source of over-dispersion in the data as well as a factor shaping the functional relationship between the variables that explain a firm's location decisions. Using count data models, empirical researchers have dealt with over-dispersion and excess zeros by developments of the Poisson regression model. This study aims to take this a step further by adopting Bayesian methods and models in order to tackle the excess of zeros, spatial and non-spatial over-dispersion, and spatial dependence simultaneously. Data for Catalonia (Spain) are used and location determinants are analysed to that end. The results show that spatial effects are determinant. Additionally, over-dispersion is decomposed into an unstructured independently and identically distributed (i.i.d.) effect and a spatially structured effect.

Date: 2020
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Journal Article: Industrial Location and Spatial Dependence: An Empirical Application (2014)
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DOI: 10.1080/00343404.2012.675054

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