Dentifications of the Distribution of Treatment Effect with Duration Outcomes

The most critical factor in econometric estimations is parameter identification. Identification in econometric models formalizes prior assumptions and the data to information about a parameter of interest. However, there are two important features characterize duration data. The first one is that the data may be censored, and the second feature of duration data is that exogenous determinants of the event times characterizing the data may change during the event spell. The two characteristics lead some famous identification problems for the duration models. Following the recent literature in partial identification, we show the conditions when the duration models could be identified and provide several suggestions for the confidence bounds of partial identifications.