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Title: Multivariate Regression Models for Panel Data
Resulting in 1 citation.
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Chamberlain, Gary |
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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) |
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Bibliography Citation
Chamberlain, Gary. "Multivariate Regression Models for Panel Data." Journal of Econometrics 18,1 (January 1982): 5-46.
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