Extending a Smooth Parameter Model to Firm Location Analyses: The Case of Natural Gas Establishments in the United States

20 Pages Posted: 22 Nov 2016

See all articles by Jason Brown

Jason Brown

Federal Reserve Bank of Kansas City

Dayton M. Lambert

University of Tennessee, Knoxville

Date Written: November 2016

Abstract

This paper extends recent developments in regional growth modeling that use spatial regime switching functions to a count regression model of firm location events. The smooth parameter count model (SPCM) allows for a parsimonious parameterization of locally varying coefficients while simultaneously attending to excess‐zero count events. An empirical application examines natural gas establishment growth between 2005 and 2010. The smooth parameter model appears to outperform a standard zero‐inflated count model. The SPCM may be extended to the location analysis of other industries with the identification of transition variables related to the supply or demand oriented cost structure of the sector.

Suggested Citation

Brown, Jason and Lambert, Dayton M., Extending a Smooth Parameter Model to Firm Location Analyses: The Case of Natural Gas Establishments in the United States (November 2016). Journal of Regional Science, Vol. 56, Issue 5, pp. 848-867, 2016, Available at SSRN: https://ssrn.com/abstract=2873978 or http://dx.doi.org/10.1111/jors.12280

Jason Brown (Contact Author)

Federal Reserve Bank of Kansas City ( email )

1 Memorial Dr.
Kansas City, MO 64198
United States

Dayton M. Lambert

University of Tennessee, Knoxville ( email )

The Boyd Center for Business and Economic Research
Knoxville, TN 37996
United States

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