The location quotient as an estimator of industrial concentration

Stephen Billings and Erik Johnson ()

Regional Science and Urban Economics, 2012, vol. 42, issue 4, 642-647

Abstract: We construct the location quotient (LQ) from a discrete data generating process and formally test its statistical properties. First, we show that the LQ is typically unbiased, but exhibits finite sample bias when assuming a Poisson distribution. Second, we determine the accuracy of statistical tests, which depends of both sample size as well as desired confidence levels. After constructing LQs using County Business Patterns (2000) data, we find improved accuracy in statistical tests when one increases spatial as well as industrial aggregation. Results show a clear tradeoff between precise statistical inference and power in detecting industrial concentration.

Keywords: Location quotient; Industrial concentration (search for similar items in EconPapers)
JEL-codes: R12 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0166046212000269
Full text for ScienceDirect subscribers only

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:eee:regeco:v:42:y:2012:i:4:p:642-647

DOI: 10.1016/j.regsciurbeco.2012.03.003

Access Statistics for this article

Regional Science and Urban Economics is currently edited by D.P McMillen and Y. Zenou

More articles in Regional Science and Urban Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().