Time and Causality: A Monte Carlo Assessment of the Timing-of-Events Approach
We present new Monte Carlo evidence regarding the feasibility of separating causal-ity from selection within non-experimental interval-censored duration data, by means of the nonparametric maximum likelihood estimator (NPMLE). Key findings are: i) the NPMLE is extremely reliable, and it accurately separates the causal effects of treatment and duration dependence from sorting effects, almost regardless of the true unobserved heterogeneity distribution; ii) the NPMLE is normally distributed, and standard errors can be computed directly from the optimally selected model; and iii) unjustified restrictions on the heterogeneity distribution, e.g., in terms of a pre-specified number of support points, may cause substantial bias.
Gaure, Simen, Knut Røed and Tao Zhang
Nummer i serie: 19
C14, C15, C41
NPMLE, treatment effect
Prosjekt:1151 - Mobilisering av arbeidstilbudet