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Simulating Confidence for the Ellison-Glaeser Index

Author

Listed:
  • Andrew J. Cassey
  • Ben O. Smith

    (School of Economic Sciences, Washington State University)

Abstract
The Ellison-Glaeser (1997) index is an unbiased statistic of industrial localization. Though the expected value of the index is known, ad hoc values are used to interpret the extent of localization. We improve on the interpretation of the index by simulating con dence intervals while varying the underlying parameters of the lognormal distribution of plant employment size and the number of plants in the industry. In the data, we nd cases whose index value is above the ad hoc threshold that are not statistically signi cant. We nd many cases below the ad hoc threshold that are statistically signi cant.

Suggested Citation

  • Andrew J. Cassey & Ben O. Smith, 2012. "Simulating Confidence for the Ellison-Glaeser Index," Working Papers 2012-8, School of Economic Sciences, Washington State University.
    • Handle: RePEc:wsu:wpaper:cassey-7
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    File URL: http://faculty.ses.wsu.edu/WorkingPapers/Cassey/WP2012-8.pdf
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    References listed on IDEAS

    as
    1. William R. Kerr & Scott Duke Kominers, 2015. "Agglomerative Forces and Cluster Shapes," The Review of Economics and Statistics, MIT Press, vol. 97(4), pages 877-899, October.
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    11. Ellison, Glenn & Glaeser, Edward L, 1997. "Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach," Journal of Political Economy, University of Chicago Press, vol. 105(5), pages 889-927, October.
    12. 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.
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    Cited by:

    1. Kristy Buzard & Gerald A. Carlino & Jake Carr & Robert M. Hunt & Tony E. Smith, 2015. "Localized Knowledge Spillovers: Evidence from the Agglomeration of American R&D Labs and Patent Data," Working Papers 15-3, Federal Reserve Bank of Philadelphia.
    2. Carlino, Gerald & Kerr, William R., 2015. "Agglomeration and Innovation," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 349-404, Elsevier.
    3. Tanaka, Kiyoyasu & Hashiguchi, Yoshihiro, 2015. "Agglomeration effects of informal sector: evidence from Cambodia," IDE Discussion Papers 495, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    4. repec:zbw:bofrdp:urn:nbn:fi:bof-201512111472 is not listed on IDEAS
    5. Craig Wesley Carpenter & Anders Van Sandt & Scott Loveridge, 2022. "Measurement error in US regional economic data," Journal of Regional Science, Wiley Blackwell, vol. 62(1), pages 57-80, January.
    6. Carlino, Gerald & Kerr, William R., 2015. "Agglomeration and Innovation," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 349-404, Elsevier.
    7. Billings, Stephen B. & Johnson, Erik B., 2016. "Agglomeration within an urban area," Journal of Urban Economics, Elsevier, vol. 91(C), pages 13-25.
    8. repec:bof:bofrdp:urn:nbn:fi:bof-201512111472 is not listed on IDEAS
    9. repec:zbw:bofrdp:2015_027 is not listed on IDEAS

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    More about this item

    Keywords

    Ellison-Glaeser; localization; herfindahl; simulation; confidence interval;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns

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