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Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States
CARD Working Papers
  • Daniel C. Monchuk, University of Southern Mississippi
  • Dermot J. Hayes, Iowa State University
  • John A. Miranowski, Iowa State University
  • Dayton M. Lambert, University of Teneessee
Publication Date
5-1-2010
Series Number
10-WP 507
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.
Publication Information

This working paper was published as Monchuk, Daniel C., Dermot J. Hayes, John A. Miranowski and Dayton M. Lambert, "Inference based on alternative bootstrapping methods in spatial models with an application to county income growth in the United States," Journal of Regional Science 51 (2011): 880–896, doi:10.1111/j.1467-9787.2011.00716.x.

Citation Information
Daniel C. Monchuk, Dermot J. Hayes, John A. Miranowski and Dayton M. Lambert. "Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States" (2010)
Available at: http://works.bepress.com/dermot_hayes/70/