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Author: Imbens, Guido W.
Resulting in 4 citations.
1. Hellerstein, Judith K.
Imbens, Guido W.
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.
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.
3. Imbens, Guido W.
Lynch, Lisa M.
Re-employment Probabilities over the Business Cycle
NBER Working Paper No. 4585, National Bureau of Economic Research, December, 1993.
Also: http://nber.nber.org/papers/W4585
Cohort(s): NLSY79
Publisher: National Bureau of Economic Research (NBER)
Keyword(s): Business Cycles; Local Labor Market; Modeling, Hazard/Event History/Survival/Duration; Seasonality; Unemployment Duration; Unemployment Rate

Using a Cox proportional hazard model that allows for a flexible time dependence that can incorporate both seasonal and business cycle effects this paper analyzes the determinants of reemployment probabilities of young workers from 1978-1989. It finds considerable changes in the chances of young workers finding jobs over the business cycle, however, the characteristics of those starting jobless spells do not vary much over time. Therefore, government programs that target specific demographic groups may change individuals' positions within the queue of job seekers but will probably have a more limited impact on the overall re-employment probability. Living in an area with high local unemployment reduces re-employment chances as does being in a long spell of non-employment. However, when we allow for an interaction between the length of time of a jobless spell and the local unemployment rate we find the interaction term is positive. In other words, while workers appear to be scarred by a long spell of unemployment, the median age seems to be reduced if they are unemployed in an area with high overall unemployment.
Bibliography Citation
Imbens, Guido W. and Lisa M. Lynch. "Re-employment Probabilities over the Business Cycle." NBER Working Paper No. 4585, National Bureau of Economic Research, December, 1993.
4. Imbens, Guido W.
Lynch, Lisa M.
Re-Employment Probabilities over the Business Cycle
IZA Discussion Paper No. 2167, Institute for the Study of Labor (IZA), June 2006
Cohort(s): NLSY79
Publisher: Institute for the Study of Labor (IZA)
Keyword(s): Business Cycles; Modeling, Hazard/Event History/Survival/Duration; Re-employment; Unemployment; Unemployment Duration; Unemployment, Youth

Permission to reprint the abstract has not been received from the publisher.

Using a Cox proportional hazard model that allows for a flexible time dependence in order to incorporate business cycle effects, we analyze the determinants of reemployment probabilities of young workers in the U.S. from 1978-1989. We find considerable changes in the chances of young workers finding jobs over the business cycle despite the fact that personal characteristics of those starting jobless spells do not vary much over time. Therefore, government programs that target specific demographic groups may change individuals' positions within the queue of job seekers, but may only have a more limited impact on average re-employment probabilities. Living in an area with high local unemployment reduces re-employment chances as does being in a long spell of nonemployment. However, the damage associated with being in a long spell seems to be reduced somewhat if a worker is unemployed in an area with high overall unemployment.
Bibliography Citation
Imbens, Guido W. and Lisa M. Lynch. "Re-Employment Probabilities over the Business Cycle." IZA Discussion Paper No. 2167, Institute for the Study of Labor (IZA), June 2006.