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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

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  • Juliana Guimarães
  • (Universidade NOVA de Lisboa

Abstract

There is conflicting evidence regarding the recent evolution of unemployment duration in the U.S. In this study we rely on censored quantile regression methods to analyze the changes in the US unemployment duration distribution. We employed the decomposition method proposed by Machado and Mata (2003) to disentangle the contribution of the changes generated by the covariate distribution and by the conditional distribution and adapted it to a duration analysis framework.The data used in this inquiry are taken from the nationally representative Displaced Worker Survey of 1988 and 1998. We provide evidence that the unemployment duration distribution shifted leftward. The main driving force behind that shift was the sharp leftward move in the unemployment rate distribution. This force was partially counteracted by the ageing of the displaced population, the striking absence of impact from being displaced via a plant shutdown, and the higher sensitivity of unemployment duration to unemployment rates

Suggested Citation

  • 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.
    • Handle: RePEc:ecm:latm04:128
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    References listed on IDEAS

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    1. Addison, John T & Portugal, Pedro, 1987. "On the Distributional Shape of Unemployment Duration," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 521-526, August.
    2. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
    3. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
    4. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    5. 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.
    6. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    7. Bassett, Gilbert W. & Koenker, Roger W., 1986. "Strong Consistency of Regression Quantiles and Related Empirical Processes," Econometric Theory, Cambridge University Press, vol. 2(2), pages 191-201, August.
    8. Katharine G. Abraham & Robert Shimer, 2001. "Changes in Unemployment Duration and Labor Force Attachment," NBER Working Papers 8513, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Bernd Fitzenberger & Ralf Wilke, 2006. "Using quantile regression for duration analysis," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 105-120, March.

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    Keywords

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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