IDEAS home Printed from https://ideas.repec.org/p/fip/fedhwp/wp-09-16.html
   My bibliography  Save this paper

Estimation of a transformation model with truncation, interval observation and time-varying covariates

Author

Listed:
  • Bo E. Honore
  • Luojia Hu

Abstract

Abrevaya (1999b) considered estimation of a transformation model in the presence of left-truncation. This paper observes that a cross-sectional version of the statistical model considered in Frederiksen, Honor, and Hu (2007) is a generalization of the model considered by Abrevaya (1999b) and the generalized model can be estimated by a pairwise comparison version of one of the estimators in Frederiksen, Honor, and Hu (2007). Specifically, our generalization will allow for discretized observations of the dependent variable and for piecewise constant time- varying explanatory variables.

Suggested Citation

  • Bo E. Honore & Luojia Hu, 2009. "Estimation of a transformation model with truncation, interval observation and time-varying covariates," Working Paper Series WP-09-16, Federal Reserve Bank of Chicago.
    • Handle: RePEc:fip:fedhwp:wp-09-16
    as

    Download full text from publisher

    File URL: http://www.chicagofed.org/digital_assets/publications/working_papers/2009/wp2009_16.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. Hausman, Jerry A. & Woutersen, Tiemen, 2014. "Estimating a semi-parametric duration model without specifying heterogeneity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 114-131.
    2. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    3. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    4. Chen, Songnian, 2019. "Quantile regression for duration models with time-varying regressors," Journal of Econometrics, Elsevier, vol. 209(1), pages 1-17.
    5. Jerry Hausman & Tiemen Woutersen, 2014. "Estimating the Derivative Function and Counterfactuals in Duration Models with Heterogeneity," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 472-496, August.
    6. Shinya Sugawara, 2013. "An Interval Regression Analysis for Tenures of Japanese Elder Care Workers Using Matched Employer-Employee Data," CIRJE F-Series CIRJE-F-887, CIRJE, Faculty of Economics, University of Tokyo.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:fip:fedhwp:wp-09-16. 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: Lauren Wiese (email available below). General contact details of provider: https://edirc.repec.org/data/frbchus.html .

    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.