A Monte Carlo study of time aggregation in continuous-time and discrete-time parametric hazard models

This study investigates the effects of time aggregation in discrete and continuous-time hazard models. A Monte Carlo study is conducted in which data are generated according to various continuous and discrete-time processes, and aggregated into daily, weekly and monthly intervals. These data are analyzed with flexible continuous-time and discrete-time parametric hazard models. The estimates of the structural parameter and baseline hazard seem robust to the form of the distribution of the data generation process when the time-aggregation window is small. Both estimates of continuous-time models and of discrete-time models suffer from time aggregation, but the estimates of the discrete-time model are more sensitive to aggregation.