Empirical Likelihood for Nonsmooth Functionals
Empirical likelihood is an attractive inferential framework that respects natural parameter boundaries, but existing approaches typically require smoothness of the functional and miscalibrate substantially when these assumptions are violated. For the optimal-value functional central to policy evaluation, smoothness holds only when the optimum is unique -- a condition that fails exactly when rigorous inference is most needed where more complex policies have modest gains. In this work, we develop a bootstrap empirical likelihood method for partially nonsmooth functionals. Our analytic workhorse is a geometric reduction of the profile likelihood to the distance between the score mean and a l...
| Authors | Hongseok Namkoong |
|---|---|
| Primary category | stat.ME |
| Published | 29 March 2026 |
| Last updated at source | 29 March 2026 |
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