摘要：We present new Monte Carlo evidence regarding the feasibility of separating causality
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 prespecified
number of support points, may cause substantial bias.
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