Using Discrete-Time Event History Fertility Models to Simulate Total Fertility Rates and Other Fertility Measures

Jennifer Van Hook, Pennsylvania State University
Claire Altman, Pennsylvania State University

Event history models are commonly used in analyses of fertility. Such models offer advantages over more simplistic OLS or Poisson models of children ever borne. One drawback of event history models is that the conditional probabilities estimated by event history models do not readily translate into summary measures, particularly for models of repeatable events, like childbirth. In this paper, we describe how to translate the results of discrete-time event history models of all births into well-known summary fertility measures: simulated age- and parity-specific fertility rates, parity progression ratios, and the total fertility rate. Our method incorporates all birth intervals, but permits the hazard functions to vary across parities. It also can simulate values for groups defined by both fixed and time-varying covariates, such as marital or employment life histories. We demonstrate the method using an example from the National Survey of Family Growth.