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Source: Wiley and Sons
Resulting in 2 citations.
1. Griliches, Zvi
Earnings of Very Young Men
In: Income Distribution and Economic Inequality. Z. Griliches, et al., eds. New York, NY: Wiley and Sons, 1978
Cohort(s): Young Men
Publisher: Wiley Online
Keyword(s): Earnings; Family Influences; I.Q.; Schooling

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

This study replicates the author's earlier (1976) results on newer data from the NLS of Young Men, discusses the distribution of earnings as opposed to wage rates, and outlines a model for the analysis of time series on individuals. The effect of schooling on wage rates is far stronger than is the effect of IQ, and this difference is even stronger when the effects of these two variables on earnings are considered. Only half of the observed variance in completed schooling is explained by family background and IQ, so other forces affecting schooling remain to be identified. In the late 1960s, young black men were completing more schooling than white of similar background and ability.
Bibliography Citation
Griliches, Zvi. "Earnings of Very Young Men" In: Income Distribution and Economic Inequality. Z. Griliches, et al., eds. New York, NY: Wiley and Sons, 1978
2. Hill, Jennifer L.
Reiter, Jerome P.
Zanutto, Elaine L.
A Comparison of Experimental and Observational Data Analyses
In: Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives. A. Gelman and X. Meng, eds., New York: Wiley, 2007: 49-60
Cohort(s): Children of the NLSY79
Publisher: Wiley Online
Keyword(s): Birthweight; Child Care; I.Q.; Missing Data/Imputation; Peabody Picture Vocabulary Test (PPVT); Propensity Scores; Test Scores/Test theory/IRT

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

In this paper, we illustrate the potential efficacy of these types of analyses. The causal question we address concerns the effects on intelligence test scores of a particular intervention that provided very high quality childcare for children with low birth weights.We have data from the randomized experiment performed to evaluate the causal effect of this intervention, as well as observational data from the National Longitudinal Survey of Youth on children not exposed to the intervention. Using these two datasets, we compare several estimates of the treatment effect from the observational data to the estimate of the treatment effect from the experiment, which we treat as the gold standard. ...We also demonstrate the use of propensity scores with data that has been multiply imputed to handle pretreatment and post-treatment missingness. To our knowledge, these other constructed observational studies performed analyses using only units with fully observed data.
Bibliography Citation
Hill, Jennifer L., Jerome P. Reiter and Elaine L. Zanutto. "A Comparison of Experimental and Observational Data Analyses" In: Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives. A. Gelman and X. Meng, eds., New York: Wiley, 2007: 49-60