EASY ESTIMATION METHODS FOR DISCRETE-TIME DURATION MODELS

Recent literature has emphasized that estimation of duration models sh ould take account of the sampling scheme generating the data, but this cannot be done using the duration modules in currently-available pack ages. This paper shows that discrete-time duration models can be estim ated easily using widely-available, non-specialist, software packages. It focuses on the case where the data are for respondents randomly se lected from a stock at one date and then interviewed after some time i nterval has elapsed, and also shows that these results generalize to o ther sampling schemes where the likelihood function requires condition ing on survival to a data between sample selection and interview. The findings extend earlier results concerning the easy estimation of dura tion models which use data from random population samples.