IDEAS home Printed from https://ideas.repec.org/a/sae/inrsre/v26y2003i1p68-85.html
   My bibliography  Save this article

Identifying Export Industries Using Parametric Density Functions

Author

Listed:
  • Donald Nichols

    (University of Wisconsin–Madison)

  • David Mushinski

    (Colorado State University, Fort Collins, CO)

Abstract

In this article, the authors present a new way of identifying the set of industries that may constitute a region’s economic base. The authors focus on the differences among regions in their regional employment shares (the percentage of total employment in a particular region attributable to a particular industry). They find that the distribution across regions of regional employment shares can be characterized by what they call a mixed-exponential distribution for industries that are easy to classify as being export industries—such as automotive manufacturing—while the distributions of regional employment shares for some easy-to-classify local industries tend to be normal. The authors then attempt to classify each of the remaining industries as being either export or local to determine whether the empirical distribution of employment shares in each industry is more like the mixed-exponential distribution or more like the normal distribution. The attempt is partially successful.

Suggested Citation

  • Donald Nichols & David Mushinski, 2003. "Identifying Export Industries Using Parametric Density Functions," International Regional Science Review, , vol. 26(1), pages 68-85, January.
  • Handle: RePEc:sae:inrsre:v:26:y:2003:i:1:p:68-85
    DOI: 10.1177/0160017602238986
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0160017602238986
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0160017602238986?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Quang Vuong & Weiren Wang, 1993. "Selecting Estimated Models Using Chi-Square Statistics," Annals of Economics and Statistics, GENES, issue 30, pages 143-164.
    2. repec:adr:anecst:y:1993:i:30:p:06 is not listed on IDEAS
    3. Vuong, Quang H. & Wang, Weiren, 1993. "Minimum chi-square estimation and tests for model selection," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 141-168, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. David Mushinski & Donald Nichols, 2011. "Identifying the export component of industries that produce partly for local consumption," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(2), pages 313-329, April.
    2. repec:rre:publsh:v:33:y:2003:i:2:p:164-83 is not listed on IDEAS
    3. Eli Miloslavsky & Howard J. Shatz, 2006. "Services Exports and the States: Measuring the Potential," Economic Development Quarterly, , vol. 20(1), pages 3-21, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hanieh Panahi, 2016. "Model Selection Test for the Heavy-Tailed Distributions under Censored Samples with Application in Financial Data," IJFS, MDPI, vol. 4(4), pages 1-14, December.
    2. M. Jiménez-Gamero & R. Pino-Mejías & A. Rufián-Lizana, 2014. "Minimum $$K_{\phi }$$ K ϕ -divergence estimators for multinomial models and applications," Computational Statistics, Springer, vol. 29(1), pages 363-401, February.
    3. R. Golden, 2003. "Discrepancy Risk Model Selection Test theory for comparing possibly misspecified or nonnested models," Psychometrika, Springer;The Psychometric Society, vol. 68(2), pages 229-249, June.
    4. M. Jiménez-Gamero & A. Batsidis & M. Alba-Fernández, 2016. "Fourier methods for model selection," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(1), pages 105-133, February.
    5. Jiménez-Gamero, M.D. & Pino-Mejías, R. & Alba-Fernández, V. & Moreno-Rebollo, J.L., 2011. "Minimum [phi]-divergence estimation in misspecified multinomial models," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3365-3378, December.
    6. G. Avlogiaris & A. C. Micheas & K. Zografos, 2019. "A Criterion for Local Model Selection," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 406-444, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:inrsre:v:26:y:2003:i:1:p:68-85. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.