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A note on the Weibull distribution and time aggregation bias

Author

Listed:
  • Knut Røed
  • Tao Zhang

Abstract

The application of continuous time Weibull models on discrete unemployment duration data may result in severely biased baseline estimates. The bias can be substantial even for weekly duration data, and it is seriously aggravated if the Weibull model is erroneously mixed with a Gamma distribution for unobserved heterogeneity.

Suggested Citation

  • Knut Røed & Tao Zhang, 2002. "A note on the Weibull distribution and time aggregation bias," Applied Economics Letters, Taylor & Francis Journals, vol. 9(7), pages 469-472.
    • Handle: RePEc:taf:apeclt:v:9:y:2002:i:7:p:469-472
    DOI: 10.1080/13504850110096340
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    Cited by:

    1. Alicja Jokiel-Rokita & Sylwester Pia̧tek, 2024. "Estimation of parameters and quantiles of the Weibull distribution," Statistical Papers, Springer, vol. 65(1), pages 1-18, February.
    2. Manudeep Bhuller & Christian N. Brinch & Sebastian Königs, 2017. "Time Aggregation and State Dependence in Welfare Receipt," Economic Journal, Royal Economic Society, vol. 127(604), pages 1833-1873, September.
    3. Mansi Sharma & Steven Stern, 2024. "Generalized Weibull Distributions," Department of Economics Working Papers 24-05, Stony Brook University, Department of Economics.
    4. Yolanda M. Gómez & Diego I. Gallardo & Carolina Marchant & Luis Sánchez & Marcelo Bourguignon, 2023. "An In-Depth Review of the Weibull Model with a Focus on Various Parameterizations," Mathematics, MDPI, vol. 12(1), pages 1-19, December.
    5. Christian N. Brinch, 2011. "Non‐parametric identification of the mixed proportional hazards model with interval‐censored durations," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 343-350, July.
    6. Wulfrano Gómez & Leovardo Mata & Montserrat Reyna, 2013. "Hodrick-Prescott Filter: An Extreme-Sport Testing," Revista de Administración, Finanzas y Economía (Journal of Management, Finance and Economics), Tecnológico de Monterrey, Campus Ciudad de México, vol. 7(1), pages 1-13.
    7. Christian N. Brinch, 2008. "Non-parametric Identification of the Mixed Hazards Model with Interval-Censored Durations," Discussion Papers 539, Statistics Norway, Research Department.

    More about this item

    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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