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Clustering of auto supplier plants in the U.S.: GMM spatial logit for large samples

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  • Thomas H. Klier
  • Dan McMillen

Abstract

A linearized version of Pinkse and Slade’s (1998) spatial probit estimator is used to account for the tendency of auto supplier plants to cluster together. By reducing estimation to two steps – standard probit or logit followed by two-stage least squares – linearization produces a model that can be estimated using large datasets. Our results imply significant clustering among older plants. Supplier plants are more likely to be in counties that are near assembly plants, that include interstate highways, and that are near other counties with supplier plants. New plants show no additional tendency toward clustering beyond that shown by older plants.

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Bibliographic Info

Paper provided by Federal Reserve Bank of Chicago in its series Working Paper Series with number WP-05-18.

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Date of creation: 2005
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Handle: RePEc:fip:fedhwp:wp-05-18

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Related research

Keywords: Automobile supplies industry;

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References

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  1. Saavedra, Luz Amparo, 2000. "A Model of Welfare Competition with Evidence from AFDC," Journal of Urban Economics, Elsevier, vol. 47(2), pages 248-279, March.
  2. Thomas Klier, 2004. "Challenges to the U.S. auto industry," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue Mar.
  3. Revelli, Federico, 2003. "Reaction or interaction? Spatial process identification in multi-tiered government structures," Journal of Urban Economics, Elsevier, vol. 53(1), pages 29-53, January.
  4. Jan K. Brueckner & Luz A. Saavedra, 2000. "Do Local Governments Engage in Strategic Property-Tax Competition?," Econometric Society World Congress 2000 Contributed Papers 0357, Econometric Society.
  5. Smith Jr. , Donald F. & Florida Richard, 1994. "Agglomeration and Industrial Location: An Econometric Analysis of Japanese-Affiliated Manufacturing Establishments in Automotive-Related Industries," Journal of Urban Economics, Elsevier, vol. 36(1), pages 23-41, July.
  6. Pinkse, Joris & Slade, Margaret E., 1998. "Contracting in space: An application of spatial statistics to discrete-choice models," Journal of Econometrics, Elsevier, vol. 85(1), pages 125-154, July.
  7. Case, Anne C. & Rosen, Harvey S. & Hines, James Jr., 1993. "Budget spillovers and fiscal policy interdependence : Evidence from the states," Journal of Public Economics, Elsevier, vol. 52(3), pages 285-307, October.
  8. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
  9. Craig Brett & Joris Pinkse, 2000. "The determinants of municipal tax rates in British Columbia," Canadian Journal of Economics, Canadian Economics Association, vol. 33(3), pages 695-714, August.
  10. Brueckner, Jan K., 1998. "Testing for Strategic Interaction Among Local Governments: The Case of Growth Controls," Journal of Urban Economics, Elsevier, vol. 44(3), pages 438-467, November.
  11. Case, Anne, 1992. "Neighborhood influence and technological change," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 491-508, September.
  12. Fredriksson, Per G. & Millimet, Daniel L., 2002. "Strategic Interaction and the Determination of Environmental Policy across U.S. States," Journal of Urban Economics, Elsevier, vol. 51(1), pages 101-122, January.
  13. Alfonso Flores‐Lagunes & Kurt Erik Schnier, 2012. "Estimation of sample selection models with spatial dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 173-204, 03.
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Cited by:
  1. Jason P. Brown & Raymond J.G.M. Florax & Kevin T. McNamara, 2008. "Evolution Of Investment Flows In U.S. Manufacturing:A Spatial Panel Approach," Working Papers 08-06, Purdue University, College of Agriculture, Department of Agricultural Economics.
  2. Jørn Rattsø & Jon Hernes Fiva, 2005. "Decentralization with Property Taxation to Improve Incentives: Evidence from Local Governments’ Discrete Choice," Working Paper Series 5305, Department of Economics, Norwegian University of Science and Technology, revised 02 Sep 2005.
  3. Chandra Bhat & Ipek Sener, 2009. "A copula-based closed-form binary logit choice model for accommodating spatial correlation across observational units," Journal of Geographical Systems, Springer, vol. 11(3), pages 243-272, September.

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