Skip to main content
Log in

Spatial variation of nonmetropolitan industrial location

  • Published:
The Journal of Real Estate Finance and Economics Aims and scope Submit manuscript

Abstract

This study examines economic development and industrial location in the rural Southeast using a varying coefficient model. Empirical results generated with a Poisson regression show that the varying coefficient model is appropriate and that the posited variables help explain the number of manufacturing firms which have located to a rural county. The model distinguishes between the ability of a county to attract industry both independent of distance and as a function of the distance to the nearest strategic urban center. Differences exist between the locational preferences of traditional industry and nontraditionial (diversification-enhancing) industry.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Carlton, D.W. “The Location and Employment Choices of New Firms: An Econometric Model with Discrete and Continuous Endogenous Variables.”Review of Economics and Statistics. 65 (1983), 440–449.

    Google Scholar 

  • County and City Data Book. United States Department of Commerce, 1983.

  • Clark, C. “Urban Population Densities.”Journal of the Royal Statistical Society, Series A. 114 (1951), 490–496.

    Google Scholar 

  • Erickson, R.A. and Wasylenko, M. “Firm Relocation and Site Selection in Suburban Municipalities.”Journal of Urban Economics. 8 (1980), 69–85.

    Google Scholar 

  • Georgia Industrial Directory. Georgia Department of Commerce, 1988.

  • Georgia Statistical Abstract. University of Georgia, College of Business Administration, Division of Research, 1988.

  • Goldberg, M. A. “An Economic Model of Intrametropolitan Industrial Location.”Journal of Regional Science. 10 (1970), 75–79.

    Google Scholar 

  • Green, W.Econometric Analysis. New York: MacMillan, 1990, 707–709.

    Google Scholar 

  • Highway Rate Basis Numbers. Georgia Public Service Commission, 1988, Table 3.

  • Hoare, A.G. “Industrial Linkage Studies.” In M. Pacione, ed.,Progress in Industrial Geography. London: Croom Helm, 1985.

    Google Scholar 

  • Johnson, S.R. and Kau, J.B. “Urban Spatial Structure: An Analysis with a Varying Coefficient Model.”Journal of Urban Economics 7 (1980), 141–154.

    Google Scholar 

  • Maddala, G.S.Limited Dependent and Qualitative Variables in Econometrics, Econometric Series Monographs. New York: Cambridge University Press, 1983.

    Google Scholar 

  • Mullahy, J. “Specification and Testing of Some Modified Count Data Models.”Journal of Econometrics 33 (1986), 341–366.

    Google Scholar 

  • Newling, B.E. “The Spatial Variation of Urban Population Densities.”Geography Review 59 (1969), 242–252.

    Google Scholar 

  • Parr, J.B. “The Development of Spatial Structure and Regional Economic Growth.”Land Economics 63 (1987), 113–127.

    Google Scholar 

  • Parr, J.B. “The Form of the Regional Density Function.”Regional Studies 19 (1985), 535–546.

    Google Scholar 

  • Simon, C.J. “Industrial Diversity, Vacancy Dispersion, and Unemployment.”Annals of Regional Science 21 (1987), 60–73.

    Google Scholar 

  • South Carolina Industrial Directory. South Carolina Department of Commerce, 1988.

  • South Carolina Statistical Abstract. South Carolina Budget and Control Board, Division of Research and Statistical Services, 1988.

  • Till, T.E. “Industrialization and Poverty in Southern Nonmetropolitan Labor Markets.”Growth and Change 5 (1974), 18–24.

    Google Scholar 

  • Weisberg, S.Applied Linear Regression. New York: Wiley, 1985, Chapter 12.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ambrose, B.W., Springer, T.M. Spatial variation of nonmetropolitan industrial location. J Real Estate Finan Econ 7, 17–27 (1993). https://doi.org/10.1007/BF01096933

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01096933

Key words

Navigation