A general semiparametric approach to inference with marker-dependent hazard rate models
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...
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| Main Authors: | , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
2021
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| In: |
Journal of econometrics
Year: 2020, Volume: 221, Issue: 1, Pages: 43-67 |
| DOI: | 10.1016/j.jeconom.2019.05.025 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.jeconom.2019.05.025 Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S0304407620300439 
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| Author Notes: | Gerard. J. van den Berg, Lena Janys, Enno Mammen, Jens Perch Nielsen |
| Summary: | 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. |
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| Item Description: | Available online 5 March 2020 Gesehen am 07.04.2021 |
| Physical Description: | Online Resource |
| DOI: | 10.1016/j.jeconom.2019.05.025 |