On the Convergence Rate of the SCAD-Penalized Empirical Likelihood Estimator
Tomohiro Ando, Naoya Sueishi
Econometrics | MDPI AG | Published : 2019
This paper investigates the asymptotic properties of a penalized empirical likelihood estimator for moment restriction models when the number of parameters ( pn ) and/or the number of moment restrictions increases with the sample size. Our main result is that the SCAD-penalized empirical likelihood estimator is n/pn−−−−√ -consistent under a reasonable condition on the regularization parameter. Our consistency rate is better than the existing ones. This paper also provides sufficient conditions under which n/pn−−−−√ -consistency and an oracle property are satisfied simultaneously. As far as we know, this paper is the first to specify sufficient conditions for both n/pn−−−−√ -consistency and t..View full abstract
Awarded by JSPS KAKENHI
This research was supported by JSPS KAKENHI Grant Number 15K03396.