ivcrc: An instrumental-variables estimator for the correlated random-coefficients model

被引:0
|
作者
Benson, David [1 ]
Masten, Matthew A. [2 ]
Torgovitsky, Alexander [3 ]
机构
[1] Fed Reserve Board Governors, Div Res & Stat, Washington, DC 20551 USA
[2] Duke Univ, Dept Econ, Econ, Durham, NC 27706 USA
[3] Univ Chicago, Kenneth C Griffin Dept Econ, Econ, Chicago, IL 60637 USA
来源
STATA JOURNAL | 2022年 / 22卷 / 03期
基金
美国国家科学基金会;
关键词
st0680; ivcrc; ivregress; instrumental variables; correlated random coefficients; heterogeneous treatment effects; varying-coefficient models; returns to schooling; SIMULTANEOUS-EQUATIONS MODELS; LEAST-SQUARES ESTIMATION; SELECTION BIAS; AVERAGE; IDENTIFICATION; RETURNS; EDUCATION; QUANTILE;
D O I
10.1177/1536867X221124449
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
We discuss the ivcrc command, which implements an instrumental-variables (IV) estimator for the linear correlated random-coefficients model. The correlated random-coefficients model is a natural generalization of the standard linear IV model that allows for endogenous, multivalued treatments and unobserved heterogeneity in treatment effects. The estimator implemented by ivcrc uses recent semiparametric identification results that allow for flexible functional forms and permit instruments that may be binary, discrete, or continuous. The ivcrc command also allows for the estimation of varying-coefficient regressions, which are closely related in structure to the proposed IV estimator. We illustrate the use of ivcrc by estimating the returns to education in the National Longitudinal Survey of Young Men.
引用
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页码:469 / 495
页数:27
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