Semester

Spring

Date of Graduation

2014

Document Type

Dissertation

Degree Type

PhD

College

College of Business and Economics

Department

Economics

Committee Chair

Brian J. Cushing

Committee Co-Chair

Randall W. Jackson

Committee Member

Donald J. Lacombe

Committee Member

Peter V. Schaeffer

Committee Member

Feng Yao

Abstract

Industrial agglomeration is an important subject in the field of regional economics. It is an economic phenomenon with two dimensions---space and industry. These two dimensions call for research that can take both spatial and industry factors into consideration regarding industrial agglomeration. Despite the advance of economic theories on agglomeration, empirical studies that satisfactorily incorporate spatial and industrial dimensions are very few. My research aims to enrich the existing methodology for empirical studies by combining spatial econometrics and the input-output model to investigate the effects of input-output linkages on industrial agglomeration.;In this research I propose two methods to integrate spatial econometrics and the input-output model. The first method is a direct application of the embedding strategy in the literature of the integrated econometrics and input-output model, extending it by introducing the spatial intermediate demand variable and estimating the model as if it were a spatial panel data model. The industry dimension replaces the time dimension in the spatial panel data model so that the model in this research is called spatial pseudo panel data model. The second method further explores the spatial pseudo panel data model with a space-industry filter. The space-industry filter enriches the embedding strategy by straightforwardly combining spatial econometrics and the input-output model within a simple model setting. Using the space-industry filter, I define four summary measures of effects estimates that disentangle the impacts of the inter-industry and inter-regional linkages on industrial agglomeration. Based on the summary measures, I explore two ways to partition the effects estimates along the spatial and industry directions. Besides these two methods, I also put forward a bootstrap method to identify the existence of industrial agglomeration using the standardized location quotient.

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