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

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

No 6459, 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida from American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association)

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.

Keywords: Bayesian econometrics; employment growth; high technology; smooth coefficient models; spatial modeling.; Labor and Human Capital; Resource /Energy Economics and Policy (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-geo, nep-lab and nep-ure
Date: 2008
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