Uncovering Spatial Productivity Centers using Asymmetric Bidirectional Spillovers

Abstract

The principal contribution of this paper is to present the first method to sift through a large number of firms in an industry to uncover which firms act as large spatial total factor productivity (TFP) growth centers. We define a large spatial TFP growth center as a firm that is a large net generator of spatial TFP growth spillovers, i.e., it is a source of large TFP growth spill-outs to other firms vis-à-vis the size of the TFP growth spill-ins that permeate to the firm from other firms. We use this definition because, other things being equal, firms would want to locate near a firm that is a net generator of TFP growth spillovers. In the process of presenting the above method we make three further contributions, two of which are methodological and the other relates to our application. First, rather than follow the literature on spatial frontier modeling by considering spatial interaction between firms in a single network, we introduce a more sophisticated model that is able to account for spatial interaction in multiple networks. Second, we obtain bidirectional spatial TFP growth decompositions by complementing a unidirectional decomposition in the literature, where the spillover components are spill-ins to a firm, with a decomposition that includes spill-out components. Third, from a spatial revenue frontier for U.S. banks (1998−2015), we find a number of cases where banks that represent large spatial TFP growth centers have branches that cluster together, while in several states we find no such clusters.

Publication DOI: https://doi.org/10.1016/j.ejor.2020.02.007
Divisions: College of Business and Social Sciences > Aston Business School > Economics, Finance & Entrepreneurship
College of Business and Social Sciences > Aston Business School
Additional Information: © 2020, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: Multiple spatial networks,Productivity and competitiveness,Revenue function,Spatial stochastic frontier analysis,U.S. banks,Computer Science(all),Modelling and Simulation,Management Science and Operations Research,Information Systems and Management
Publication ISSN: 1872-6860
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Related URLs: https://www.sci ... 377221720301259 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2020-09-01
Published Online Date: 2020-02-11
Accepted Date: 2020-02-04
Authors: Glass, Anthony
Kenjegalieva, Karligash
Douch, Mustapha (ORCID Profile 0000-0002-3906-1690)

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Version: Accepted Version

Access Restriction: Restricted to Repository staff only until 11 February 2022.

License: Creative Commons Attribution Non-commercial No Derivatives


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