Bayesian Analysis of Hazard Regression Models under Order Restrictions on Covariate Effects and Ageing
We propose Bayesian inference in hazard regression models where the baseline hazard is unknown, covariate effects are possibly agevarying (non-proportional), and there is multiplicative frailty with arbitrary distribution. Our framework incorporates a wide variety of order restrictions on covariate dependence and duration dependence (ageing). We propose estimation and evaluation of age-varying covariate e¤ects when covariate dependence is monotone rather than proportional. In particular, we consider situations where the lifetime conditional on a higher value of the covariate ages faster or slower than that conditional on a lower value; this kind of situation is common in applications. In addition, there may be restrictions on the nature of ageing. For example, relevant theory may suggest that the baseline hazard function decreases with age. The proposed framework enables evaluation of order restrictions in the nature of both covariate and duration dependence as well as estimation of hazard regression models under such restrictions. The usefulness of the proposed Bayesian model and inference methods are illustrated with an application to corporate bankruptcies in the UK.
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- Bhattacharjee, A., 2003.
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Cambridge Working Papers in Economics
0337, Faculty of Economics, University of Cambridge.
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"A Simple Test for the Absence of Covariate Dependence in Hazard Regression Models,"
3937, University Library of Munich, Germany.
- Arnab Bhattacharjee, 2007. "A Simple Test for the Absence of Covariate Dependence in Hazard Regression Models," Discussion Paper Series, Department of Economics 200708, Department of Economics, University of St. Andrews.
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"Macro Economic Instability and Business Exit: Determinants of Failures and Acquisitions of Large UK Firms,"
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27, Royal Economic Society.
- A. Bhattacharjee & Higson, C. & Holly, S. & Kattuman, P., 2002. "Macro Economic Instability and Business Exit: Determinants of Failures and Acquisitions of Large UK Firms," Cambridge Working Papers in Economics 0206, Faculty of Economics, University of Cambridge.
- Alan Gelfand & Athanasios Kottas, 2001. "Nonparametric Bayesian Modeling for Stochastic Order," Annals of the Institute of Statistical Mathematics, Springer, vol. 53(4), pages 865-876, December.
- Bhattacharjee, A. & Samarjit Das, 2002. "Testing Proportionality in Duration Models with Respect to Continuous Covariates," Cambridge Working Papers in Economics 0220, Faculty of Economics, University of Cambridge.
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