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

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  • Monchuk, Daniel C.
  • Hayes, Dermot J.
  • Miranowski, John
  • Lambert, Dayton

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 implement a number of spatial bootstrap routines to infer parameter significance. Among the results, we find that outdoor recreation and natural amenities favor positive growth in rural counties and property taxes correlate negatively with rural growth. Comparing bootstrap inference with other models, including the recent General Moment heteroskedastic-robust spatial error estimator, we find similar conclusions suggesting bootstrapping can be effective in spatial models where asymptotic results are not well established. ��

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Bibliographic Info

Paper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 36121.

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Date of creation: 15 Apr 2013
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Publication status: Published in Journal of Regional Science, March 2011, vol. 51 no. 5, pp. 880-896
Handle: RePEc:isu:genres:36121

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Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
Phone: +1 515.294.6741
Fax: +1 515.294.0221
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Web page: http://www.econ.iastate.edu
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  1. Monchuk, Daniel C. & Miranowski, John A. & Hayes, Dermot J. & Babcock, Bruce A., 2004. "An Analysis Of Regional Economic Growth In The Us Midwest," 2004 Annual meeting, August 1-4, Denver, CO 20369, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  2. Steven C. Deller & Tsung-Hsiu (Sue) Tsai & David W. Marcouiller & Donald B.K. English, 2001. "The Role of Amenities and Quality of Life In Rural Economic Growth," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(2), pages 352-365.
  3. Mitch Renkow, 2003. "Employment Growth, Worker Mobility, and Rural Economic Development," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 503-513.
  4. Cheshire, Paul & Sheppard, Stephen, 1995. "On the Price of Land and the Value of Amenities," Economica, London School of Economics and Political Science, vol. 62(246), pages 247-67, May.
  5. Georgeanne M. Artz & Peter F. Orazem & Daniel M. Otto, 2007. "Measuring the Impact of Meat Packing and Processing Facilities in Nonmetropolitan Counties: A Difference-in-Differences Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(3), pages 557-570.
  6. David Brownstone & Robert Valletta, 2001. "The Bootstrap and Multiple Imputations: Harnessing Increased Computing Power for Improved Statistical Tests," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 129-141, Fall.
  7. JunJie Wu & Munisamy Gopinath, 2008. "What Causes Spatial Variations in Economic Development in the United States?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(2), pages 392-408.
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Cited by:
  1. Torben Klarl, 2013. "Is Spatial Bootstrapping a Panacea for Valid Inference?," Discussion Paper Series 322, Universitaet Augsburg, Institute for Economics.
  2. Andrés Rodríguez-Pose & Tobias D. Ketterer, 2012. "Do local amenities affect the appeal of regions in Europe for migrants?," Working Papers 2012-04, Instituto Madrileño de Estudios Avanzados (IMDEA) Ciencias Sociales.
  3. Herrera Gómez, Marcos & Ruiz Marín, Manuel & Mur Lacambra, Jesús, 2013. "Detecting dependence between spatial processes," MPRA Paper 43861, University Library of Munich, Germany.

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