Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
13459420 | Economics Letters | 2020 | 6 Pages |
Abstract
This paper proposes a new semiparametric estimator of models where the response random variable is a fraction. The estimator is constructed by optimizing a semiparametric quasi-maximum likelihood that utilizes kernel smoothing. Under suitable conditions, the consistency and asymptotic normality of the proposed estimator is established allowing for data-driven bandwidth choices as well as random trimming, and its flexibility and robustness are showcased in a Monte Carlo experiment and an empirical application.
Related Topics
Social Sciences and Humanities
Economics, Econometrics and Finance
Economics and Econometrics
Authors
Santiago Montoya-Blandón, David T. Jacho-Chávez,