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The Geographic Diversity of U.S. Nonmetropolitan Growth Dynamics: A Geographically Weighted Regression Approach

Author

Listed:
  • Mark D. Partridge

    (Ohio State University)

  • Dan S. Rickman

    (Oklahoma State University)

  • Kamar Ali

    (University of Saskatchewan)

  • M. Rose Olfert

    (University of Saskatchewan)

Abstract
Spatial heterogeneity is introduced as an explanation for local-area growth mechanisms, especially employment growth. As these effects are difficult to detect using conventional regression approaches, we use Geographically Weighted Regressions (GWR) for non-metropolitan U.S. counties. We test for geographic heterogeneity in the growth parameters and compare them to global regression estimates. The results indicate significant heterogeneity in the regression coefficients across the country, most notably for amenities and college graduate shares. Using GWR also exposes significant local variations that are masked by global estimates suggesting limitations of a one-size fits all approach to describe growth and to inform public policy.

Suggested Citation

  • Mark D. Partridge & Dan S. Rickman & Kamar Ali & M. Rose Olfert, 2007. "The Geographic Diversity of U.S. Nonmetropolitan Growth Dynamics: A Geographically Weighted Regression Approach," Economics Working Paper Series 0704, Oklahoma State University, Department of Economics and Legal Studies in Business.
    • Handle: RePEc:okl:wpaper:0704
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Nonmetropolitan Growth; Geographically Weighted Regression; Economic Geography; Regional and Urban Economics;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General

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