Clustering of auto supplier plants in the U.S.: GMM spatial logit for large samples
AbstractA 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 InfoPaper provided by Federal Reserve Bank of Chicago in its series Working Paper Series with number WP-05-18.
Date of creation: 2005
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-01-01 (All new papers)
- NEP-BEC-2006-01-01 (Business Economics)
- NEP-DCM-2006-01-01 (Discrete Choice Models)
- NEP-ECM-2006-01-01 (Econometrics)
- NEP-GEO-2006-01-01 (Economic Geography)
- NEP-URE-2006-01-01 (Urban & Real Estate Economics)
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