Nonparametric identification under discrete variation
成果类型：
Article
署名作者：
Chesher, A
署名单位：
University of London; University College London; London School Economics & Political Science; University of London; University College London
刊物名称：
ECONOMETRICA
ISSN/ISSBN：
0012-9682
DOI：
10.1111/j.1468-0262.2005.00628.x
发表日期：
2005
页码：
1525-1550
关键词：
摘要：
This paper provides weak conditions under which there is nonparametric interval identification of local features of a structural function that depends on a discrete endogenous variable and is nonseparable in latent variates. The function delivers values of a discrete or continuous outcome and instruments may be discrete valued. Application of the analog principle leads to quantile regression based interval estimators of values and partial differences of structural functions. The results are used to investigate the nonparametric identifying power of the quarter-of-birth instruments used in Angrist and Krueger's 1991 study of the returns to schooling.
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