Binary response model with many weak instruments

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autore principale: Seong, Dakyung
Natura: Preprint
Pubblicazione: 2022
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866916305895948288
author Seong, Dakyung
author_facet Seong, Dakyung
contents This paper considers an endogenous binary response model with many weak instruments. We employ a control function approach and a regularization scheme to obtain better estimation results for the endogenous binary response model in the presence of many weak instruments. Two consistent and asymptotically normally distributed estimators are provided, each of which is called a regularized conditional maximum likelihood estimator (RCMLE) and a regularized nonlinear least squares estimator (RNLSE). Monte Carlo simulations show that the proposed estimators outperform the existing ones when there are many weak instruments. We use the proposed estimation method to examine the effect of family income on college completion.
format Preprint
id arxiv_https___arxiv_org_abs_2201_04811
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Binary response model with many weak instruments
Seong, Dakyung
Econometrics
Applications
This paper considers an endogenous binary response model with many weak instruments. We employ a control function approach and a regularization scheme to obtain better estimation results for the endogenous binary response model in the presence of many weak instruments. Two consistent and asymptotically normally distributed estimators are provided, each of which is called a regularized conditional maximum likelihood estimator (RCMLE) and a regularized nonlinear least squares estimator (RNLSE). Monte Carlo simulations show that the proposed estimators outperform the existing ones when there are many weak instruments. We use the proposed estimation method to examine the effect of family income on college completion.
title Binary response model with many weak instruments
topic Econometrics
Applications
url https://arxiv.org/abs/2201.04811