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Using quantile regression for duration analysis

Author Info

Listed author(s):
  • 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.)

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File URL: http://hdl.handle.net/10.1007/s10182-006-0224-2
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Article provided by Springer & German Statistical Society in its journal Allgemeines Statistisches Archiv.

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

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Handle: RePEc:spr:alstar:v:90:y:2006:i:1:p:105-120
DOI: 10.1007/s10182-006-0224-2
Contact details of provider: Web page: http://www.springer.com

Web page: http://www.dstatg.de/de/startseite/

Order Information: Web: http://www.springer.com/statistics/journal/10182/PS2

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

Other versions of this item:

Find related papers by JEL classification:
  • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
  • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
  • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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  1. 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.
  2. Martin Biewen & Ralf Wilke, 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?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 89(2), pages 209-236, June.
  3. 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.
  4. 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.
  5. 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.
  6. Moshe Buchinsky & Jinyong Hahn, 1998. "An Alternative Estimator for the Censored Quantile Regression Model," Econometrica, Econometric Society, vol. 66(3), pages 653-672, May.
  7. 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.
  8. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, November.
  9. 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.
  10. Portnoy S., 2003. "Censored Regression Quantiles," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 1001-1012, January.
  11. 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.
  12. Fitzenberger, Bernd & Winker, Peter, 2007. "Improving the computation of censored quantile regressions," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 88-108, September.
  13. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
  14. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
  15. 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.
  16. 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.
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Cited by:

  1. Müller Eva & Zahn Philipp & Wilke Ralf A., 2007. "Beschäftigung und Arbeitslosigkeit älterer Arbeitnehmer / Employment and Unemployment of the Elderly: Eine mikroökonometrische Evaluation der Arbeitslosengeldreform von 1997 / A Microeconometric Evalu," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 227(1), pages 65-86, February.
  2. 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.
  3. Xavier D’Haultfoeuille & Pauline Givord, 2014. "La régression quantile en pratique," Économie et Statistique, Programme National Persée, vol. 471(1), pages 85-111.
  4. repec:jns:jbstat:v:227:y:2007:i:1:p:65-86 is not listed on IDEAS
  5. repec:eee:jeborg:v:137:y:2017:i:c:p:113-131 is not listed on IDEAS
  6. Fitzenberger, Bernd & Winker, Peter, 2007. "Improving the computation of censored quantile regressions," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 88-108, September.
  7. 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.
  8. Alona Zharova & Andrija Mihoci & Wolfgang Karl Härdle, 2016. "Academic Ranking Scales in Economics: Prediction and Imputation," SFB 649 Discussion Papers SFB649DP2016-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  9. Coad, Alex & Segarra, Agustí & Teruel, Mercedes, 2016. "Innovation and firm growth: Does firm age play a role?," Research Policy, Elsevier, vol. 45(2), pages 387-400.
  10. 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.
  11. 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.
  12. 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.
  13. 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.

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