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A Multivariate Spatial Analysis for Anticipating New Firm Counts

Yiyi Wang, Kara M. Kockelman and Paul Damien

A chapter in Spatial Econometrics: Qualitative and Limited Dependent Variables, 2016, vol. 37, pp 167-193 from Emerald Group Publishing Limited

Abstract: This paper analyzes county-level firm births across the United States using a spatial count model that permits spatial dependence, cross-correlation among different industry types, and over-dispersion commonly found in empirical count data. Results confirm the presence of spatial autocorrelation (which can arise from agglomeration effects and missing variables), industry-specific over-dispersion, and positive, significant cross-correlations. After controlling for existing-firm counts in 2008 (as an exposure term), parameter estimates and inference suggest that a younger work force and/or clientele (as quantified using each county’s median-age values) is associated with more firm births (in 2009). Higher population densities is associated with more new basic-sector firms, while reducing retail-firm starts. The modeling framework demonstrated here can be adopted for a variety of settings, harnessing very local, detailed data to evaluate the effectiveness of investments and policies, in terms of generating business establishments and promoting economic gains.

Keywords: Firm birth; spatial count model; multivariate response; conditional autoregressive; M13; C11; C30; C35 (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-905320160000037014

DOI: 10.1108/S0731-905320160000037014

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