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Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States Author info | Abstract | Publisher info | Download info | Related research | Statistics Daniel C. Monchuk
Dermot J. Hayes () (Center for Agricultural and Rural Development (CARD) )
John Miranowski
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This study examines correlates with aggregate county income growth across the 48 contiguous states from 1990 to 2001. Since visual inspection of the variable to be explained shows a clear spatial relationship and to control for potentially endogenous variables, we estimate a two-stage spatial error model. Given the lack of theoretical and asymptotic results for such models, we propose and implement a number of spatial bootstrap algorithms, including one allowing for heteroskedasticity, to infer parameter significance. Among the results of a comparison of the marginal effects in rural versus non-rural counties, we find that outdoor recreation and natural amenities favor positive growth in rural counties, densely populated rural areas enjoy stronger growth, and property taxes correlate negatively with rural growth.
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Paper provided by Center for Agricultural and Rural Development (CARD) at Iowa State University in its series Center for Agricultural and Rural Development (CARD) Publications with number
08-wp471.
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Date of creation: Jun 2008Date of revision:
Handle: RePEc:ias:cpaper:08-wp471Contact details of provider: Postal: 578 Heady Hall, Ames, Iowa 50011-1070 Phone: (515) 294-1183 Fax: (515) 294-6336 Email: Web page: http://www.card.iastate.edu/ More information through EDIRC
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Keywords: county income growth rural development spatial bootstrapping. Other versions of this item:
This paper has been announced in the following NEP Reports :
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