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Spatial And Supply/Demand Agglomeration Economies: An Evaluation Of State-And-Industry-Linkages In The U.S. Food System

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  • Cohen, Jeffrey P.
  • Morrison Paul, Catherine J.

Abstract

In this paper we postulate, measure, and evaluate the importance of cost-impacts from spatial and industrial spillovers for analysis of economic performance. To accomplish this, we incorporate measures of "activity levels" of related states and industries in a cost function model, and estimate their associated thick market and agglomeration effects in terms of shadow values and elasticities. We focus on the food processing sector, the proximity of own-industry activity in neighboring states, and the supply- and demand- side "drivers", associated with urbanization and localization economies (represented by the GSP and agricultural intensity in the own and neighboring states). We find significant cost-savings benefits to a states food processing sector of being close to other food manufacturing centers (high levels of food processing activity in neighboring states). We also find it beneficial to be in a state with high purchasing power (demand), and to have neighboring states that are agriculture-based (supply). However, it also seems costly to actually be located in a heavily agricultural or rural state, possibly due to diseconomies from "thin markets" associated with infrastructure support and labor markets.

Suggested Citation

  • Cohen, Jeffrey P. & Morrison Paul, Catherine J., 2001. "Spatial And Supply/Demand Agglomeration Economies: An Evaluation Of State-And-Industry-Linkages In The U.S. Food System," Working Papers 11982, University of California, Davis, Department of Agricultural and Resource Economics.
  • Handle: RePEc:ags:ucdavw:11982
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    File URL: http://purl.umn.edu/11982
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    References listed on IDEAS

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    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Donald S. Siegel & Catherine J. Morrison Paul, 1999. "Scale Economies and Industry Agglomeration Externalities: A Dynamic Cost Function Approach," American Economic Review, American Economic Association, vol. 89(1), pages 272-290, March.
    3. Jeffrey Bernstein, 1998. "Factor Intensities, Rates of Return, and International R&D Spillovers: The Case of Canadian and U.S. Industries," Annals of Economics and Statistics, GENES, issue 49-50, pages 541-564.
    4. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    5. repec:adr:anecst:y:1998:i:49-50:p:21 is not listed on IDEAS
    6. Morrison, Catherine J, 1985. "Primal and Dual Capacity Utilization: An Application to Productivity Measurement in the U.S. Automobile Industry," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(4), pages 312-324, October.
    7. Bartelsman, Eric J & Caballero, Ricardo J & Lyons, Richard K, 1994. "Customer- and Supplier-Driven Externalities," American Economic Review, American Economic Association, vol. 84(4), pages 1075-1084, September.
    8. David, Paul A. & Rosenbloom, Joshua L., 1990. "Marshallian factor market externalities and the dynamics of industrial localization," Journal of Urban Economics, Elsevier, vol. 28(3), pages 349-370, November.
    9. Cohen, Jeffrey P. & Paul, Catherine J. Morrison, 2005. "Agglomeration economies and industry location decisions: the impacts of spatial and industrial spillovers," Regional Science and Urban Economics, Elsevier, vol. 35(3), pages 215-237, May.
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    Cited by:

    1. Cohen, Jeffrey P. & Morrison Paul, Catherine J., 2001. "Hub and Spoke Airport Networks and State Airport Infrastructure Spillovers: A Spatial Econometrics Approach," Working Papers 190900, University of California, Davis, Department of Agricultural and Resource Economics.

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    Keywords

    Productivity Analysis;

    Statistics

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