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The location quotient as an estimator of industrial concentration

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  • Billings, Stephen B.
  • Johnson, Erik B.
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    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.

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    Bibliographic Info

    Article provided by Elsevier in its journal Regional Science and Urban Economics.

    Volume (Year): 42 (2012)
    Issue (Month): 4 ()
    Pages: 642-647

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

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    Web page: http://www.elsevier.com/locate/regec

    Related research

    Keywords: Location quotient; Industrial concentration;

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    1. Briant, Anthony & Combes, Pierre-Philippe & Lafourcade, Miren, 2008. "Dots to Boxes: Do the Size and Shape of Spatial Units Jeopardize Economic Geography Estimations?," CEPR Discussion Papers 6928, C.E.P.R. Discussion Papers.
    2. Gilles Duranton & Henry G. Overman, 2002. "Testing for localisation using micro-geographic data," LSE Research Online Documents on Economics 20071, London School of Economics and Political Science, LSE Library.
    3. JH Ll DEWHURST, . "Regional Size, Industrial Location And Input-Output Expenditure Coefficients," Dundee Discussion Papers in Economics 074, Economic Studies, University of Dundee.
    4. Paulo Guimaraes & Octavio Figueiredo & Douglas Woodward, 2000. "A tractable approach to the firm location decision problem," NIMA Working Papers 2, Núcleo de Investigação em Microeconomia Aplicada (NIMA), Universidade do Minho.
    5. Paulo Guimarães & Octávio Figueiredo & Douglas Woodward, 2008. "Dartboard Tests for the Location Quotient," FEP Working Papers 273, Universidade do Porto, Faculdade de Economia do Porto.
    6. Dan O'Donoghue & Bill Gleave, 2004. "A Note on Methods for Measuring Industrial Agglomeration," Regional Studies, Taylor & Francis Journals, vol. 38(4), pages 419-427.
    7. Joseph P. Romano & Michael Wolf, 2003. "Stepwise Multiple Testing as Formalized Data Snooping," Working Papers 17, Barcelona Graduate School of Economics.
    8. Gemechis D. Djira & Frank Schaarschmidt & Bichaka Fayissa, 2008. "Inferences for Selected Location Quotients with Applications to Health Outcomes," Working Papers 200809, Middle Tennessee State University, Department of Economics and Finance.
    9. George Deltas, 2003. "The Small-Sample Bias of the Gini Coefficient: Results and Implications for Empirical Research," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 226-234, February.
    10. Thomas J. Holmes & John J. Stevens, 2002. "Geographic Concentration and Establishment Scale," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 682-690, November.
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