Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States

Daniel Monchuk (), Dermot Hayes, John Miranowski and Dayton Lambert

Center for Agricultural and Rural Development (CARD) Publications from Center for Agricultural and Rural Development (CARD) at Iowa State University

Abstract: This study examines aggregate county income growth across the 48 contiguous states from 1990 to 2005. To control for endogeneity we estimate a two-stage spatial error model and infer parameter significance by implementing a number of spatial bootstrap algorithms. 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. We also compare estimates from the aggregate county income growth model with per capita income growth and find that these two growth processes can be quite different.

Keywords: county income growth; rural development; spatial bootstrapping. (search for similar items in EconPapers)
JEL-codes: O18 R11 R58 (search for similar items in EconPapers)
Date: 2010-05
New Economics Papers: this item is included in nep-fdg, nep-geo and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Related works:
Working Paper: Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States (2013)
Journal Article: INFERENCE BASED ON ALTERNATIVE BOOTSTRAPPING METHODS IN SPATIAL MODELS WITH AN APPLICATION TO COUNTY INCOME GROWTH IN THE UNITED STATES (2011)
Working Paper: Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States (2011)
Working Paper: Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States (2008)
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