Sieve inference on irregular parameters

This paper presents sieve inferences on possibly irregular (i.e., slower than root- n estimable) functionals of semi-nonparametric models with i.i.d. data. We provide a simple consistent variance estimator of the plug-in sieve M estimator of a possibly irregular functional, and the asymptotic standard normality of the sieve t  statistic. We show that, for hypothesis testing of irregular functionals, the sieve likelihood ratio statistic is asymptotically Chi-square distributed. These results are useful in inference on structural parameters that may have singular semiparametric efficiency bounds. A simulation study and an empirical application of Heckman and Singer (1984) duration model are presented.