Additive time-dependent hazard model with doubly truncated data |
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Authors: | Gordon Frank Minwoo Chae Yongdai Kim |
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Affiliation: | 1. Faculty for Economic and Social Sciences, University of Rostock, Germany;2. Department of Mathematics, Applied Mathematics and Statistics, Case Western Reserve University, United States;3. Department of Statistics, Seoul National University, Republic of Korea |
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Abstract: | For doubly truncated data, i.e. the variables of interest are only observable if they lie in a certain random interval, an additive hazard model with time-dependent regression coefficients is investigated. Consistency and asymptotic normality are proven under mild assumptions. A simulation study investigates the finite sample properties and the influence of the truncation distribution on the estimation error. Finally, the method is applied to a doubly truncated data set of German companies, where the age at insolvency is of interest. |
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Keywords: | Corresponding author. primary 62N01 secondary 62N02 Additive hazard model Insolvency risk Non-parametric Random double-truncation Time-dependent regression coefficients |
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