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Author: Chamberlain, Gary

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1.	Chamberlain, Gary
1.	Multivariate Regression Models for Panel Data Journal of Econometrics 18,1 (January 1982): 5-46. Also: http://www.sciencedirect.com/science/article/pii/030440768290094X Cohort(s): Young Men Publisher: Elsevier Keyword(s): Heterogeneity; Regions; Research Methodology; Standard Metropolitan Statistical Area (SMSA); Unions The relationship between heterogeneity bias and strict exogeneity is examined in a distributed lag regression of y on x. The relationship is very strong when x is continuous, weaker when x is discrete, and non-existent as the order of the distributed lag becomes infinite. The individual specific random variables introduce nonlinearity and heteroskedasticity, so a framework suitable for the estimation of multivariate linear predictors is provided. A minimum distance estimator is used to impose restrictions, being generally more efficient than the conventional estimators, such as quasi-maximum likelihood. Computationally simple generalizations of 2- and 3-stage least squares exist to accomplish this efficiency gain. The sample of Young Men in the NLS is used to illustrate some of these ideas. Regressions on leads and lags of variables measuring union coverage, Standard Metropolitan Statistical Areas (SMSAs), and regions are reported. The results suggest that the leads and lags could have been brought about just by a random intercept, which gives some support for analysis of covariance type estimates. These estimates point to a substantial heterogeneity bias in the union, SMSA, and region coefficients. (ABI/Inform)
	Bibliography Citation Chamberlain, Gary. "Multivariate Regression Models for Panel Data." Journal of Econometrics 18,1 (January 1982): 5-46.

2.	Chamberlain, Gary
2.	Omitted Variable Bias in Panel Data: Estimating the Returns to Schooling Annales de l'INSEE 30-31 (April-September 1978): 49-82. Also: http://www.jstor.org/stable/20075285 Cohort(s): Young Men Publisher: INSEE (Institut National de la Statistique et des Etudes Economiques) Keyword(s): Earnings; Educational Returns; Heterogeneity; Job Training; Schooling; Work Experience Permission to reprint the abstract has not been received from the publisher. This paper uses panel data to control for heterogeneity in estimating the effect of variables that are not changing over time. Identification is achieved by structuring the cross-equation residual covariances via a set of common omitted variables, which are in turn related to a set of measured exogenous variables. The principal finding is a substantial downward bias in regression estimates of the effect of schooling upon wages for a sample of young men. This finding is interpreted by relating schooling to the variance in experience-earnings profiles associated with investment in on-the-job training.
	Bibliography Citation Chamberlain, Gary. "Omitted Variable Bias in Panel Data: Estimating the Returns to Schooling." Annales de l'INSEE 30-31 (April-September 1978): 49-82.

3.	Chamberlain, Gary
3.	Panel Data NBER Working Paper No. 0913, National Bureau of Economic Research, June 1982 Cohort(s): Young Men Publisher: National Bureau of Economic Research (NBER) Keyword(s): Fertility; Gender Differences; Labor Force Participation; Modeling, Mixed Effects; Modeling, Multilevel; Modeling, Probit; Unions; Wage Effects We consider linear predictor definitions of noncausality or strict exogeneity and show that it is restrictive to assert that there exists a time-invariant latent variable c such that x is strictly exogenous conditional on c. A restriction of this sort is necessary to justify standard techniques for controlling for unobserved individual effects. There is a parallel analysis for multivariate probit models, but now the distributional assumption for the individual effects is restrictive. This restriction can be avoided by using a conditional likelihood analysis in a logit model. Some of these ideas are illustrated by estimating union wage effects for a sample of Young Men in the National Longitudinal Survey. The results indicate that the lags and leads could have been generated just by an unobserved individual effect, which gives some support for analysis of covariance-type estimates. These estimates indicate a substantial omitted variable bias. We also present estimates of a model of female labor force participation, focusing on the relationship between participation and fertility. Unlike the wage example, there is evidence against conditional strict exogeneity; if we ignore this evidence, the probit and logit approaches give conflicting results.
	Bibliography Citation Chamberlain, Gary. "Panel Data." NBER Working Paper No. 0913, National Bureau of Economic Research, June 1982.

4.	Chamberlain, Gary Griliches, Zvi
4.	More on Brothers In: Kinometrics: Determinants of Socio-Economic Success Within/Between Families. P. Taubman, ed. Amsterdam, The Netherlands: North Holland Publishing, 1977. Cohort(s): Young Men Publisher: Elsevier Keyword(s): Brothers; Educational Aspirations/Expectations; Family Income; I.Q.; Occupational Aspirations; Pairs (also see Siblings); Schooling; Siblings The major focus of this study is on estimating the income-schooling relationship in the presence of an unobserved ability variable. The main results are the negligible ability coefficient and the substantial schooling coefficient in the earnings equation. The authors expect the ability coefficient to increase as the sample ages. On the whole, they feel that the results from the expectation data are better indicators of the eventual peak schooling and ability effects.
	Bibliography Citation Chamberlain, Gary and Zvi Griliches. "More on Brothers" In: Kinometrics: Determinants of Socio-Economic Success Within/Between Families. P. Taubman, ed. Amsterdam, The Netherlands: North Holland Publishing, 1977.

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