IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v221y2021i1p43-67.html
   My bibliography  Save this article

A general semiparametric approach to inference with marker-dependent hazard rate models

Author

Listed:
  • van den Berg, Gerard. J.
  • Janys, Lena
  • Mammen, Enno
  • Nielsen, Jens Perch

Abstract

We examine a new general class of hazard rate models for duration data, containing a parametric and a nonparametric component. Both can be a mix of a time effect and possibly time-dependent covariate effects. A number of well-known models are special cases. In a counting process framework, a general profile likelihood estimator is developed and the parametric component of the model is shown to be asymptotically normal and efficient. Finite sample properties are investigated in simulations. The estimator is applied to investigate the long-run relationship between birth weight and later-life mortality.

Suggested Citation

  • van den Berg, Gerard. J. & Janys, Lena & Mammen, Enno & Nielsen, Jens Perch, 2021. "A general semiparametric approach to inference with marker-dependent hazard rate models," Journal of Econometrics, Elsevier, vol. 221(1), pages 43-67.
    • Handle: RePEc:eee:econom:v:221:y:2021:i:1:p:43-67
    DOI: 10.1016/j.jeconom.2019.05.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304407620300439
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jeconom.2019.05.025?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bijwaard Govert E. & Ridder Geert & Woutersen Tiemen, 2013. "A Simple GMM Estimator for the Semiparametric Mixed Proportional Hazard Model," Journal of Econometric Methods, De Gruyter, vol. 2(1), pages 1-23, July.
    2. Olivier Jean Blanchard & Peter Diamond, 1994. "Ranking, Unemployment Duration, and Wages," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(3), pages 417-434.
    3. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 767-779, April.
    4. Van den Berg, Gerard & Modin, Bitte, 2013. "Economic Conditions at Birth, Birth Weight, Ability, and the Causal Path to Cardiovascular Mortality," CEPR Discussion Papers 9650, C.E.P.R. Discussion Papers.
    5. 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.
    6. 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.
    7. Nielsen, Jens P. & Linton, Oliver & Bickel, Peter J., 1998. "On a semiparametric survival model with flexible covariate effect," LSE Research Online Documents on Economics 301, London School of Economics and Political Science, LSE Library.
    8. Geert Ridder & Tiemen M. Woutersen, 2003. "The Singularity of the Information Matrix of the Mixed Proportional Hazard Model," Econometrica, Econometric Society, vol. 71(5), pages 1579-1589, September.
    9. Enno Mammen & Jens Perch Nielsen, 2007. "A General Approach to the Predictability Issue in Survival Analysis with Applications," Biometrika, Biometrika Trust, vol. 94(4), pages 873-892.
    10. Jens Perch Nielsen & Carsten Tanggaard, 2001. "Boundary and Bias Correction in Kernel Hazard Estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 28(4), pages 675-698, December.
    11. Douglas Almond & Janet Currie, 2011. "Killing Me Softly: The Fetal Origins Hypothesis," Journal of Economic Perspectives, American Economic Association, vol. 25(3), pages 153-172, Summer.
    12. Spierdijk, Laura, 2008. "Nonparametric conditional hazard rate estimation: A local linear approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2419-2434, January.
    13. Bearse, Peter & Canals-Cerdá, José & Rilstone, Paul, 2007. "Efficient Semiparametric Estimation Of Duration Models With Unobserved Heterogeneity," Econometric Theory, Cambridge University Press, vol. 23(2), pages 281-308, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Janys, Lena, 2017. "A General Semiparametric Approach to Inference with Marker-Dependent Hazard Rate Models," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168077, Verein für Socialpolitik / German Economic Association.
    2. van den Berg, Gerard J. & Janys, Lena & Mammen, Enno & Nielsen, Jens P., 2014. "A General Semiparametric Approach to Inference with Marker-Dependent Hazard Rate Models," IZA Discussion Papers 8339, Institute of Labor Economics (IZA).
    3. 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.
    4. María Luz Gámiz & Enno Mammen & María Dolores Martínez Miranda & Jens Perch Nielsen, 2016. "Double one-sided cross-validation of local linear hazards," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(4), pages 755-779, September.
    5. 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.
    6. 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.
    7. Bhalotra, Sonia & Karlsson, Martin & Nilsson, Therese, 2014. "Life Expectancy and Mother-Baby Interventions. Evidence from A Historical Trial," Ruhr Economic Papers 504, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    8. Sonia Bhalotra & Martin Karlsson & Therese Nilsson, 2014. "Life Expectancy and Mother-Baby Interventions. Evidence from A Historical Trial," Ruhr Economic Papers 0504, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    9. van den Berg, Gerard J. & Paul, Alexander & Reinhold, Steffen, 2020. "Economic conditions and the health of newborns: Evidence from comprehensive register data," Labour Economics, Elsevier, vol. 63(C).
    10. Spierdijk, Laura, 2008. "Nonparametric conditional hazard rate estimation: A local linear approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2419-2434, January.
    11. Angelini, Viola & Mierau, Jochen O. & Viluma, Laura, 2021. "Socioeconomic Conditions in Childhood and Mental Health Later in Life," GLO Discussion Paper Series 844, Global Labor Organization (GLO).
    12. Alessie, Rob & Angelini, Viola & van den Berg, Gerard J. & Mierau, Jochen O. & Viluma, Laura, 2017. "Economic Conditions at Birth and Cardiovascular Disease Risk in Adulthood: Evidence from New Cohorts," IZA Discussion Papers 10810, Institute of Labor Economics (IZA).
    13. Di Giacomo, Marina & Piacenza, Massimiliano & Siciliani, Luigi & Turati, Gilberto, 2022. "The effect of co-payments on the take-up of prenatal tests," Journal of Health Economics, Elsevier, vol. 81(C).
    14. Burda, Martin & Harding, Matthew, 2014. "Environmental Justice: Evidence from Superfund cleanup durations," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 380-401.
    15. repec:zbw:rwirep:0504 is not listed on IDEAS
    16. Alessie, Rob J.M. & Angelini, Viola & van den Berg, Gerard J. & Mierau, Jochen O. & Viluma, Laura, 2019. "Economic conditions at birth and cardiovascular disease risk in adulthood: Evidence from post-1950 cohorts," Social Science & Medicine, Elsevier, vol. 224(C), pages 77-84.
    17. Arulampalam, Wiji & Corradi, Valentina & Gutknecht, Daniel, 2017. "Modeling heaped duration data: An application to neonatal mortality," Journal of Econometrics, Elsevier, vol. 200(2), pages 363-377.
    18. Tine Buch-Kromann & Jens Nielsen, 2012. "Multivariate density estimation using dimension reducing information and tail flattening transformations for truncated or censored data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(1), pages 167-192, February.
    19. Aiyar, Anaka & Cummins, Joseph R., 2021. "An age profile perspective on two puzzles in global child health: The Indian Enigma & economic growth," Journal of Development Economics, Elsevier, vol. 148(C).
    20. Alex Hollingsworth & Krzysztof Karbownik & Melissa A. Thomasson & Anthony Wray, 2024. "The Gift of a Lifetime: The Hospital, Modern Medicine, and Mortality," American Economic Review, American Economic Association, vol. 114(7), pages 2201-2238, July.
    21. Nandi, Arindam & Sahoo, Soham & Haberland, Nicole & Ngô, Thoại D., 2023. "A glass ceiling at the playhouse? Gender gaps in public and private preschool enrollment in India," International Journal of Educational Development, Elsevier, vol. 103(C).

    More about this item

    Keywords

    Covariate effects; Duration analysis; Kernel estimation; Mortality; Semiparametric estimation;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

    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:eee:econom:v:221:y:2021:i:1:p:43-67. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc 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 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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.