logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

Nonparametric estimation of sample selection models

delete2003-01-01
delete246
PRE
AI
M
Mitali Das
W
Whitney K. Newey
F
Francis Vella
DOI：10.1111/1467-937X.00236delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Sample selection models provide an important way of accounting for economic decisions that combine discrete and continuous choices and of correcting for nonrandom sampling. Nonparametric estimators for these models are developed in this paper. These can be used for estimating shapes and important economic quantities, as in standard nonparametric regression. Endogeneity of regressors of interest is allowed for. Series estimators for these models are developed, which are useful for imposing additivity restrictions that arise from selection corrections. Convergence rates and asymptotic normality results are derived. An application to returns to schooling among Australian young females is given.
Keywords:
SEMIPARAMETRIC ESTIMATION
CONVERGENCE
PRICES
RATES
BIAS
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Review of Economic Studies cover
Review of Economic Studies
IF:
6.4
Papers:
2.5K
Citations:
2.1W

Organization

No organization information available