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Journal article
Local Linear GMM Estimation of Functional Coefficient IV Models With an Application to Estimating the Rate of Return to Schooling
Journal of business & economic statistics, v 31(2)
01 Apr 2013
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We consider the local linear generalized method of moment (GMM) estimation of functional coefficient models with a mix of discrete and continuous data and in the presence of endogenous regressors. We establish the asymptotic normality of the estimator and derive the optimal instrumental variable that minimizes the asymptotic variance-covariance matrix among the class of all local linear GMM estimators. Data-dependent bandwidth sequences are also allowed for. We propose a nonparametric test for the constancy of the functional coefficients, study its asymptotic properties under the null hypothesis as well as a sequence of local alternatives and global alternatives, and propose a bootstrap version for it. Simulations are conducted to evaluate both the estimator and test. Applications to the 1985 Australian Longitudinal Survey data indicate a clear rejection of the null hypothesis of the constant rate of return to education, and that the returns to education obtained in earlier studies tend to be overestimated for all the work experience.
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Details
- Title
- Local Linear GMM Estimation of Functional Coefficient IV Models With an Application to Estimating the Rate of Return to Schooling
- Creators
- Liangjun Su - Singapore Management UniversityIrina Murtazashvili - Drexel UniversityAman Ullah - University of California, Riverside
- Publication Details
- Journal of business & economic statistics, v 31(2)
- Publisher
- Amer Statistical Assoc
- Number of pages
- 24
- Grant note
- Academic Senate, UCR
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Economics (School of Economics)
- Web of Science ID
- WOS:000318269800005
- Scopus ID
- 2-s2.0-84885016788
- Other Identifier
- 991019168972704721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Economics
- Social Sciences, Mathematical Methods
- Statistics & Probability