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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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Author Info

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

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.

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File URL: http://hdl.handle.net/10.1111/j.1467-9787.2011.00716.x
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Bibliographic Info

Article provided by Wiley Blackwell in its journal Journal of Regional Science.

Volume (Year): 51 (2011)
Issue (Month): 5 (December)
Pages: 880-896

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Handle: RePEc:bla:jregsc:v:51:y:2011:i:5:p:880-896

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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0022-4146

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References

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  1. 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.
  2. Daniel C. Monchuk & John Miranowski & Dermot J. Hayes & Bruce A. Babcock, 2005. "Analysis of Regional Economic Growth in the U.S. Midwest, An," Center for Agricultural and Rural Development (CARD) Publications 05-wp392, Center for Agricultural and Rural Development (CARD) at Iowa State University.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
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Citations

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Cited by:
  1. Ketterer, Tobias & Rodríguez-Pose, Andrés, 2012. "Do Local Amenities Affect the Appeal of Regions in Europe for Migrants?," CEPR Discussion Papers 8964, C.E.P.R. Discussion Papers.
  2. Herrera Gómez, Marcos & Ruiz Marín, Manuel & Mur Lacambra, Jesús, 2013. "Detecting dependence between spatial processes," MPRA Paper 43861, University Library of Munich, Germany.
  3. Torben Klarl, 2013. "Is Spatial Bootstrapping a Panacea for Valid Inference?," Discussion Paper Series 322, Universitaet Augsburg, Institute for Economics.

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