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Spatial Labor Markets And Technology Spillovers - Analysis From Us Midwest

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  • Monchuk, Daniel C.
  • Miranowski, John A.

Abstract

The primary focus of this paper is the impact of knowledge creation and innovative activity on employment growth. A number of employment growth hypotheses are tested for counties in Iowa, Minnesota, Missouri, Kansas, Nebraska, South Dakota and North Dakota. We assume that new knowledge and innovative activity are embodied in patent filings for the years 1975-2000. Due to the spatial nature of the data, both spatially lagged dependant variables and spatial error models are employed. The results support the importance of knowledge creation and innovative activity as an important factor explaining employment growth in Heartland counties over the 1969-2000 period.

Suggested Citation

  • Monchuk, Daniel C. & Miranowski, John A., 2003. "Spatial Labor Markets And Technology Spillovers - Analysis From Us Midwest," 2003 Annual meeting, July 27-30, Montreal, Canada 22250, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea03:22250
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    File URL: http://purl.umn.edu/22250
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    References listed on IDEAS

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    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. 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.
    3. LeSage, James P., 1997. "Regression Analysis of Spatial Data," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 27(2).
    4. Acs, Zoltan J. & Anselin, Luc & Varga, Attila, 2002. "Patents and innovation counts as measures of regional production of new knowledge," Research Policy, Elsevier, vol. 31(7), pages 1069-1085, September.
    5. Emery N. Castle, 1998. "A Conceptual Framework for the Study of Rural Places," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(3), pages 621-631.
    6. Pace, R. Kelley & LeSage, James P., 2004. "Chebyshev approximation of log-determinants of spatial weight matrices," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 179-196, March.
    7. Brian Roe & Elena G. Irwin & Jeff S. Sharp, 2002. "Pigs in Space: Modeling the Spatial Structure of Hog Production in Traditional and Nontraditional Production Regions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 259-278.
    8. Luc Anselin, 2000. "Geographical Spillovers and University Research: A Spatial EconometricPerspective," Growth and Change, Wiley Blackwell, vol. 31(4), pages 501-515.
    9. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 19-40, Suppl. De.
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    Keywords

    Labor and Human Capital;

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