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

Thomas Klier and Daniel McMillen ()

No WP-05-18, Working Paper Series from Federal Reserve Bank of Chicago

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.

Keywords: Automobile; supplies; industry (search for similar items in EconPapers)
Date: 2005
New Economics Papers: this item is included in nep-bec, nep-dcm, nep-ecm, nep-geo and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.chicagofed.org/digital_assets/publicati ... s/2005/wp2005_18.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fip:fedhwp:wp-05-18

Ordering information: This working paper can be ordered from

Access Statistics for this paper

More papers in Working Paper Series from Federal Reserve Bank of Chicago Contact information at EDIRC.
Bibliographic data for series maintained by Lauren Wiese ().