IDEAS home Printed from https://ideas.repec.org/a/tpr/restat/v69y1987i2p232-40.html
   My bibliography  Save this article

Some Generalized Mixture Distributions with an Application to Unemployment Duration

Author

Listed:
  • McDonald, James B
  • Butler, Richard J

Abstract

Compounding or mixture distributions provide a rich class of models for applications ranging from models of heterogeniety, measurement error, distribution of stock returns and income to models of unemployment duration. Some very general mixtures are considered which include many new mixture models and also provide a unified method of organizing and comparing previously considered models as well as a test of heterogeneity. These models are used to analyze CPS unemployment duration data. A heterogeniety interpretation of the mixture models explains the discrepancy between implications of search theory and patterns observed in aggregate unemployment data. Copyright 1987 by MIT Press.

Suggested Citation

  • McDonald, James B & Butler, Richard J, 1987. "Some Generalized Mixture Distributions with an Application to Unemployment Duration," The Review of Economics and Statistics, MIT Press, vol. 69(2), pages 232-240, May.
    • Handle: RePEc:tpr:restat:v:69:y:1987:i:2:p:232-40
    as

    Download full text from publisher

    File URL: http://links.jstor.org/sici?sici=0034-6535%28198705%2969%3A2%3C232%3ASGMDWA%3E2.0.CO%3B2-Y&origin=repec
    File Function: full text
    Download Restriction: Access to full text is restricted to JSTOR subscribers. See http://www.jstor.org for details.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Arslan, Olcay, 2004. "Family of multivariate generalized t distributions," Journal of Multivariate Analysis, Elsevier, vol. 89(2), pages 329-337, May.
    2. Andrew M. Jones & James Lomas & Nigel Rice, 2014. "Applying Beta‐Type Size Distributions To Healthcare Cost Regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(4), pages 649-670, June.
    3. Cummins, J. David & McDonald, James B. & Merrill, Craig, 2007. "Risky Loss Distributions and Modeling the Loss Reserve Pay-out Tail," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 3(1-2), pages 1-23.
    4. Brian W. Gould, 1996. "Consumer Promotion and Purchase Timing: The Case of Cheese," Wisconsin-Madison Agricultural and Applied Economics Staff Papers 396, Wisconsin-Madison Agricultural and Applied Economics Department.
    5. Gould, Brian W., 1996. "Consumer Promotion And Purchase Timing: The Case Of Cheese," Staff Papers 12664, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    6. Pope, Rulon, 1990. "Aggregation, Heterogeneity and Risk: Adding Apples and Oranges, or Apples and Apples," 1990 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, January 28-31, 1990, Sanibel Island, Florida 271538, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    7. Brian GOULD, 1996. "Consumer Promotion And Purchase Timing: The Case Of Cheese," Staff Papers 396, University of Wisconsin Madison, AAE.
    8. Peng Shi & Wei Zhang, 2011. "A copula regression model for estimating firm efficiency in the insurance industry," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(10), pages 2271-2287.
    9. Dong, A.X.D. & Chan, J.S.K., 2013. "Bayesian analysis of loss reserving using dynamic models with generalized beta distribution," Insurance: Mathematics and Economics, Elsevier, vol. 53(2), pages 355-365.
    10. Singh, Vijay P., 2018. "Systems of frequency distributions for water and environmental engineering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 50-74.
    11. Sarabia, José María & Jordá, Vanesa, 2014. "Explicit expressions of the Pietra index for the generalized function for the size distribution of income," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 582-595.
    12. Higbee, Joshua D. & Jensen, Jonathan E. & McDonald, James B., 2019. "The asymmetric log-Laplace distribution as a limiting case of the generalized beta distribution," Statistics & Probability Letters, Elsevier, vol. 151(C), pages 73-78.
    13. Monique Graf & J. Miguel Marín & Isabel Molina, 2019. "A generalized mixed model for skewed distributions applied to small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 565-597, June.
    14. Corrado Di Guilmi & Edoardo Gaffeo & Mauro Gallegati & Antonio Palestrini, 2004. "International evidence on business cycle magnitude dependence," Papers cond-mat/0401495, arXiv.org.
    15. Safari-Katesari Hadi & Zaroudi Samira, 2020. "Count copula regression model using generalized beta distribution of the second kind," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 1-12, June.
    16. Szwed, P. & Dorp, J. Rene van & Merrick, J.R.W. & Mazzuchi, T.A. & Singh, A., 2006. "A Bayesian paired comparison approach for relative accident probability assessment with covariate information," European Journal of Operational Research, Elsevier, vol. 169(1), pages 157-177, February.
    17. Shi, Peng & Valdez, Emiliano A., 2011. "A copula approach to test asymmetric information with applications to predictive modeling," Insurance: Mathematics and Economics, Elsevier, vol. 49(2), pages 226-239, September.
    18. Callealta Barroso, Francisco Javier & García-Pérez, Carmelo & Prieto-Alaiz, Mercedes, 2020. "Modelling income distribution using the log Student’s t distribution: New evidence for European Union countries," Economic Modelling, Elsevier, vol. 89(C), pages 512-522.
    19. Broda, Simon A. & Krause, Jochen & Paolella, Marc S., 2018. "Approximating expected shortfall for heavy-tailed distributions," Econometrics and Statistics, Elsevier, vol. 8(C), pages 184-203.
    20. José María Sarabia & Vanesa Jordá & Faustino Prieto & Montserrat Guillén, 2020. "Multivariate Classes of GB2 Distributions with Applications," Mathematics, MDPI, vol. 9(1), pages 1-21, December.
    21. Ivana Malá, 2013. "The Use of Finite Mixtures of Probability Distributions for Modelling the Distribution of the Duration of Unemployment in the Czech Republic [Použití konečných směsí pravděpodobnostních rozdělení p," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2013(5), pages 47-63.
    22. Punzo, Antonio & Bagnato, Luca & Maruotti, Antonello, 2018. "Compound unimodal distributions for insurance losses," Insurance: Mathematics and Economics, Elsevier, vol. 81(C), pages 95-107.
    23. Fischer, Matthias J., 2000. "The folded EGB2 distribution and its application to financial return data," Discussion Papers 32/2000, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    24. Christofides, Louis N & McKenna, C J, 1996. "Unemployment Insurance and Job Duration in Canada," Journal of Labor Economics, University of Chicago Press, vol. 14(2), pages 286-312, April.
    25. Hadi Safari-Katesari & Samira Zaroudi, 2020. "Count copula regression model using generalized beta distribution of the second kind," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 1-12, June.

    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:tpr:restat:v:69:y:1987:i:2:p:232-40. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Kelly McDougall (email available below). General contact details of provider: https://direct.mit.edu/journals .

    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.