Advanced Search
MyIDEAS: Login to save this article or follow this journal

Using quantile regression for duration analysis

Contents:

Author Info

  • Bernd Fitzenberger

    ()

  • Ralf Wilke

    ()

Abstract

Quantile regression methods are emerging as a popular technique in econometrics and biometrics for exploring the distribution of duration data. This paper discusses quantile regression for duration analysis allowing for a flexible specification of the functional relationship and of the error distribution. Censored quantile regression address the issue of right censoring of the response variable which is common in duration analysis. We compare quantile regression to standard duration models. Quantile regression do not impose a proportional effect of the covariates on the hazard over the duration time. However, the method can not take account of time{varying covariates and it has not been extended so far to allow for unobserved heterogeneity and competing risks. We also discuss how hazard rates can be estimated using quantile regression methods. A small application with German register data on unemployment duration for younger workers demonstrates the applicability and the usefulness of quantile regression for empirical duration analysis. --

(This abstract was borrowed from another version of this item.)

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://hdl.handle.net/10.1007/s10182-006-0224-2
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by Springer in its journal Allgemeines Statistisches Archiv.

Volume (Year): 90 (2006)
Issue (Month): 1 (March)
Pages: 105-120

as in new window
Handle: RePEc:spr:alstar:v:90:y:2006:i:1:p:105-120

Contact details of provider:
Web page: http://www.springerlink.com/link.asp?id=112915

Order Information:
Web: http://link.springer.de/orders.htm

Related research

Keywords: Censored quantile regression; hazard rate; unobserved heterogeneity. JEL C13; C14;

Other versions of this item:

Find related papers by JEL classification:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Hong H. & Chernozhukov V., 2002. "Three-Step Censored Quantile Regression and Extramarital Affairs," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 872-882, September.
  2. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, April.
  3. Wilke, Ralf A. & Fitzenberger, Bernd & Zhang, Xuan, 2004. "A Note on Implementing Box-Cox Quantile Regression," ZEW Discussion Papers 04-61, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  4. Moshe Buchinsky & Jinyong Hahn, 1998. "An Alternative Estimator for the Censored Quantile Regression Model," Econometrica, Econometric Society, vol. 66(3), pages 653-672, May.
  5. José A. F. Machado & Pedro Portugal, 2002. "Quantile Regression Methods: na Application to U.S. Unemployment Duration," Working Papers w200201, Banco de Portugal, Economics and Research Department.
  6. Bilias, Yannis & Chen, Songnian & Ying, Zhiliang, 2000. "Simple resampling methods for censored regression quantiles," Journal of Econometrics, Elsevier, vol. 99(2), pages 373-386, December.
  7. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
  8. Biewen, Martin & Wilke, Ralf A., 2005. "Unemployment Duration and the Length of Entitlement Periods for Unemployment Benefits: Do the IAB Employment Subsample and the German Socio-Economic Panel Yield the Same Results?," ZEW Discussion Papers 05-05, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  9. Yannis Bilias & Roger Koenker, 2001. "Quantile regression for duration data: A reappraisal of the Pennsylvania Reemployment Bonus Experiments," Empirical Economics, Springer, vol. 26(1), pages 199-220.
  10. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
  11. Fitzenberger, Bernd, 1998. "The moving blocks bootstrap and robust inference for linear least squares and quantile regressions," Journal of Econometrics, Elsevier, vol. 82(2), pages 235-287, February.
  12. Arntz, Melanie, 2005. "The Geographical Mobility of Unemployed Workers: Evidence from West Germany," ZEW Discussion Papers 05-34, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  13. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
  14. Juliana Guimarães & (Universidade NOVA de Lisboa, 2004. "Has long become longer or short become shorter? Evidence from a censored quantile regression analysis of the changes in the distribution of U.S. unemployment duration," Econometric Society 2004 Latin American Meetings 128, Econometric Society.
  15. Fitzenberger, Bernd & Winker, Peter, 2007. "Improving the computation of censored quantile regressions," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 88-108, September.
  16. Portnoy S., 2003. "Censored Regression Quantiles," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 1001-1012, January.
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 in new window

Cited by:
  1. Eva Mueller & Ralf A. Wilke & Philipp Zahn, 2007. "Beschäftigung und Arbeitslosigkeit aelterer Arbeitnehmer, Eine mikrooekonometrische Evaluation der Arbeitslosengeldreform von 1997," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 227(1), pages 65-86, February.
  2. Wilke, Ralf A. & Wichert, Laura, 2005. "Application of a simple nonparametric conditional quantile function estimator in unemployment duration analysis," ZEW Discussion Papers 05-67 [rev.], ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  3. Laura Wichert & Ralf A. Wilke, 2008. "Simple non-parametric estimators for unemployment duration analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(1), pages 117-126.
  4. De Silva, Dakshina G. & Kosmopoulou, Georgia & Lamarche, Carlos, 2009. "The effect of information on the bidding and survival of entrants in procurement auctions," Journal of Public Economics, Elsevier, vol. 93(1-2), pages 56-72, February.
  5. Melanie Arntz & Ralf Wilke, 2009. "Unemployment Duration in Germany: Individual and Regional Determinants of Local Job Finding, Migration and Subsidized Employment," Regional Studies, Taylor & Francis Journals, vol. 43(1), pages 43-61.
  6. Boockmann, Bernhard & Steffes, Susanne, 2007. "Seniority and Job Stability: A Quantile Regression Approach Using Matched Employer-Employee Data," ZEW Discussion Papers 07-014, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  7. Fitzenberger, Bernd & Winker, Peter, 2007. "Improving the computation of censored quantile regressions," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 88-108, September.
  8. Chen, Songnian, 2010. "An integrated maximum score estimator for a generalized censored quantile regression model," Journal of Econometrics, Elsevier, vol. 155(1), pages 90-98, March.
  9. Coad, Alex & Segarra Blasco, Agustí, 1958- & Teruel, Mercedes, 2013. "Innovation and firm growth: Does firm age play a role?," Working Papers 2072/211886, Universitat Rovira i Virgili, Department of Economics.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:spr:alstar:v:90:y:2006:i:1:p:105-120. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Guenther Eichhorn) or (Christopher F Baum).

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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