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Author: Hellerstein, Judith K.

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1.	Hellerstein, Judith K. Imbens, Guido W.
1.	Imposing Moment Restrictions from Auxiliary Data by Weighting The Review of Economics and Statistics 81,1 (February 1999): 1-14. Also: http://www.jstor.org/stable/2646780 Cohort(s): Young Men Publisher: Harvard University Press Keyword(s): Data Quality/Consistency; Education; Educational Returns; Modeling; Wage Models; Wages; Work Experience Permission to reprint the abstract has not been received from the publisher. In this paper we analyze the estimation of coefficients in regression models under moment restrictions in which the moment restrictions are derived from auxiliary data. The moment restrictions yield weights for each observation that can subsequently be used in weighted regression analysis. We discuss the interpretation of these weights under two assumptions: that the target population (from which the moments are constructed) and the sampled population (from which the sample is drawn) are the same, and that these populations differ. We present an application based on omitted ability bias in estimation of wage regressions. The National Longitudinal Survey Young Men's Cohort (NLS) -- in addition to containing information for each observation on wages, education, and experience--records data on two test scores that may be considered proxies for ability. The NLS is a small dataset, however, with a high attrition rate. We investigate how to mitigate these problems in the NLS by forming moments from the joint distribution of education, experience, and log wages in the 1% sample of the 1980 U.S. Census and using these moments to construct weights for weighted regression analysis of the NLS. We analyze the impacts of our weighed regression techniques on the estimated coefficients and standard errors of returns to education and experience in the NLS controlling for ability, with and without the assumption that the NLS and the Census samples are random samples from the same population. Copyright 1999 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
	Bibliography Citation Hellerstein, Judith K. and Guido W. Imbens. "Imposing Moment Restrictions from Auxiliary Data by Weighting." The Review of Economics and Statistics 81,1 (February 1999): 1-14.

2.	Imbens, Guido W. Hellerstein, Judith K.
2.	Imposing Moment Restrictions from Auxiliary Data by Weighting NBER Technical Working Paper No. 202, National Bureau of Economic Research, August 1996. Also: http://www.nber.org/papers/t0202 Cohort(s): Young Men Publisher: National Bureau of Economic Research (NBER) Keyword(s): Attrition; Census of Population; Data Analysis; Data Quality/Consistency; Earnings; Education; Educational Returns; Modeling, Mixed Effects; Sample Selection; Statistical Analysis; Test Scores/Test theory/IRT In this paper we analyze estimation of coefficients in regression models under moment restrictions where the moment restrictions are derived from auxiliary data. Our approach is similar to those that have been used in statistics for analyzing contingency tables with known marginals. These methods are useful in cases where data from a small, potentially non-representative data set can be supplemented with auxiliary information from another data set which may be larger and/or more representative of the target population. The moment restrictions yield weights for each observation that can subsequently be used in weighted regression analysis. We discuss the interpretation of these weights both under the assumption that the target population and the sampled population are the same, as well as under the assumption that these populations differ. We present an application based on omitted ability bias in estimation of wage regressions. The National Longitudinal Survey Young Men's Cohort (NLS), as well as containing information for each observation on earnings, education and experience, records data on two test scores that may be considered proxies for ability. The NLS is a small data set, however, with a high attrition rate. We investigate how to mitigate these problems in the NLS by forming moments from the joint distribution of education, experience and earnings in the 1% sample of the 1980 U.S. Census and using these moments to construct weights for weighted regression analysis of the NLS. We analyze the impacts of our weighted regression techniques on the estimated coefficients and standard errors on returns to education and experience in the NLS controlling for ability, with and without assuming that the NLS and the Census samples are random samples from the same population.
	Bibliography Citation Imbens, Guido W. and Judith K. Hellerstein. "Imposing Moment Restrictions from Auxiliary Data by Weighting." NBER Technical Working Paper No. 202, National Bureau of Economic Research, August 1996.

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