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Are High-Tech Employment and Natural Amenities Linked?: Answers from a Smoothed Bayesian Spatial Model

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  • Dorfman, Jeffrey H.
  • Patridge, Mark D.
  • Galloway, Hamilton

Abstract

We investigate the recently advanced theory that high-technology workers are drawn to high amenity locations and then the high-technology jobs follow the workers. Using a novel data set that tracks high-technology job growth by U.S. county, we estimate spatial parameters of the response of job growth to the level of local natural amenities. We achieve this estimation with a reasonably new class of models, smooth coefficient models. The model is employed in a spatial setting to allow for smooth, but nonparametric response functions to key variables in an otherwise standard regression model. With spatial data this allows for flexible modeling such as a unique place-specific effects to be estimated for each location, and also for the responses to key variables to vary by location. This flexibility is achieved through the non-parametric smoothing rather than by nearest-neighbor type estimators such as in geographically weighted regressions. The resulting model can be estimated in a straightforward application of analytical Bayesian techniques. Our results show that amenities can definitely have a significant effect on high-technology employment growth; however, the effect varies over space and by amenity level.

Suggested Citation

  • Dorfman, Jeffrey H. & Patridge, Mark D. & Galloway, Hamilton, 2008. "Are High-Tech Employment and Natural Amenities Linked?: Answers from a Smoothed Bayesian Spatial Model," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6459, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea08:6459
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    References listed on IDEAS

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    1. Koop, Gary & Tobias, Justin L., 2006. "Semiparametric Bayesian inference in smooth coefficient models," Journal of Econometrics, Elsevier, vol. 134(1), pages 283-315, September.
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    3. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    4. Mark D. Partridge & Dan S. Rickman & Kamar Ali & M. Rose Olfert, 2008. "The Geographic Diversity of U.S. Nonmetropolitan Growth Dynamics: A Geographically Weighted Regression Approach," Land Economics, University of Wisconsin Press, vol. 84(2), pages 241-266.
    5. Edward L. Glaeser, Jed Kolko, and Albert Saiz, 2001. "Consumer city," Journal of Economic Geography, Oxford University Press, vol. 1(1), pages 27-50, January.
    6. Steven C. Deller & Tsung-Hsiu (Sue) Tsai & David W. Marcouiller & Donald B.K. English, 2001. "The Role of Amenities and Quality of Life In Rural Economic Growth," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(2), pages 352-365.
    7. Mark Ferguson & Kamar Ali & M. Rose Olfert & Mark Partridge, 2007. "Voting with Their Feet: Jobs versus Amenities," Growth and Change, Wiley Blackwell, vol. 38(1), pages 77-110.
    8. Klaus Desmet & Marcel Fafchamps, 2005. "Changes in the spatial concentration of employment across US counties: a sectoral analysis 1972--2000," Journal of Economic Geography, Oxford University Press, vol. 5(3), pages 261-284, June.
    9. Partridge Mark D. & Rickman Dan S & Ali Kamar & Olfert M. Rose, 2008. "Employment Growth in the American Urban Hierarchy: Long Live Distance," The B.E. Journal of Macroeconomics, De Gruyter, vol. 8(1), pages 1-38, March.
    10. McGranahan, David A. & Wojan, Timothy R., 2007. "The Creative Class: A Key to Rural Growth," Amber Waves, United States Department of Agriculture, Economic Research Service, April.
    11. Mark Partridge & Ray D. Bollman & M. Rose Olfert & Alessandro Alasia, 2007. "Riding the Wave of Urban Growth in the Countryside: Spread, Backwash, or Stagnation?," Land Economics, University of Wisconsin Press, vol. 83(2), pages 128-152.
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    14. Dwight W. Adamson & David E. Clark & Mark D. Partridge, 2004. "Do Urban Agglomeration Effects and Household Amenities have a Skill Bias?," Journal of Regional Science, Wiley Blackwell, vol. 44(2), pages 201-224.
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    Citations

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    Cited by:

    1. Munasib, Abdul & Rickman, Dan S., 2015. "Regional economic impacts of the shale gas and tight oil boom: A synthetic control analysis," Regional Science and Urban Economics, Elsevier, vol. 50(C), pages 1-17.
    2. Stefano Magrini & Margherita Gerolimetto & Hasan Engin Duran, 2011. "Understanding the lead/lag structure among regional business cycles," Working Papers 2011_06, Department of Economics, University of Venice "Ca' Foscari".
    3. Mark D. Partridge & Dan S. Rickman & M. Rose Olfert & Ying Tan, 2015. "When Spatial Equilibrium Fails: Is Place-Based Policy Second Best?," Regional Studies, Taylor & Francis Journals, vol. 49(8), pages 1303-1325, August.
    4. Partridge, Mark & Rickman, Dan & Tan, Ying & Olfert, M. Rose, 2013. "U.S. Regional Poverty Post-2000: The Lost Decade," MPRA Paper 48528, University Library of Munich, Germany.
    5. Mark D. Partridge & Michael R. Betz & Linda Lobao, 2013. "Natural Resource Curse and Poverty in Appalachian America," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 449-456.
    6. Belal Fallah & Mark D. Partridge & Dan S. Rickman, 2014. "Geography and High-Tech Employment Growth in US Counties," Journal of Economic Geography, Oxford University Press, vol. 14(4), pages 683-720.
    7. Dan S. Rickman & Mouhcine Guettabi, 2015. "The Great Recession And Nonmetropolitan America," Journal of Regional Science, Wiley Blackwell, vol. 55(1), pages 93-112, January.
    8. Stephens, Heather & Partridge, Mark, 2012. "Lake Amenities, Environmental Degradation, and Great Lakes Regional Growth," MPRA Paper 43903, University Library of Munich, Germany.
    9. Dan Rickman & Belal Fallah & Mark Partridge, 2011. "Geographic Determinants of Hi-Tech Employment Growth in U.S. Counties," ERSA conference papers ersa11p518, European Regional Science Association.

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    Keywords

    Bayesian econometrics; employment growth; high technology; smooth coefficient models; spatial modeling.; Labor and Human Capital; Resource /Energy Economics and Policy;

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