Achieving Semiparametric Efficiency Bounds in Left-Censored Duration Models
Consider the estimation of unemployment duration when the statistician samples individuals from the pool of unemployed persons and later interviews them and asks how long they had been unmployed. This incurs the problem of left-censoring; ignoring left-censoring overestimates the mean duration since longer spells tend to be observed more frequently than shorter ones. Lancaster (1979) gives a simple and convenient solution to the problem by introducing a conditional maximum likelihood estimator (MLE), i.e. analysis conditional on duration at the time of sampling. Here we give answers to the question whether or not such an approach is optimal in the sense that a semiparametric efficiency bound is achieved.