An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias Export

@article{zellner-62, abstract = {In this paper a method of estimating the parameters of a set of regression equations is reported which involves application of Aitken's generalized least-squares [1] to the whole system of equations. Under conditions generally encountered in practice, it is found that the regression coefficient estimators so obtained are at least asymptotically more efficient than those obtained by an equation-by-equation application of least squares. This gain in efficiency can be quite large if \"{i}ndependent" variables in different equations are not highly correlated and if disturbance terms in different equations are highly correlated. Further, tests of the hypothesis that all regression equation coefficient vectors are equal, based on "micro" and "macro" data, are described. If this hypothesis is accepted, there will be no aggregation bias. Finally, the estimation procedure and the "micro-test" for aggregation bias are applied in the analysis of annual investment data, 1935-1954, for two firms.}, author = {Zellner, Arnold}, citeulike-article-id = {1211699}, citeulike-linkout-0 = {http://dx.doi.org/10.2307/2281644}, citeulike-linkout-1 = {http://www.jstor.org/stable/2281644}, doi = {10.2307/2281644}, journal = {Journal of the American Statistical Association}, keywords = {480-3, econometrics, sur}, number = {298}, pages = {348--368}, posted-at = {2007-04-06 06:07:30}, priority = {2}, title = {An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias}, url = {http://dx.doi.org/10.2307/2281644}, volume = {57}, year = {1962} }

TY - JOUR ID - zellner-62 L3 - citeulike-article-id:1211699 N2 - In this paper a method of estimating the parameters of a set of regression equations is reported which involves application of Aitken's generalized least-squares [1] to the whole system of equations. Under conditions generally encountered in practice, it is found that the regression coefficient estimators so obtained are at least asymptotically more efficient than those obtained by an equation-by-equation application of least squares. This gain in efficiency can be quite large if ïndependent" variables in different equations are not highly correlated and if disturbance terms in different equations are highly correlated. Further, tests of the hypothesis that all regression equation coefficient vectors are equal, based on "micro" and "macro" data, are described. If this hypothesis is accepted, there will be no aggregation bias. Finally, the estimation procedure and the "micro-test" for aggregation bias are applied in the analysis of annual investment data, 1935-1954, for two firms. IS - 298 JF - Journal of the American Statistical Association EP - 368 TI - An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias VL - 57 SP - 348 KW - 480-3 KW - econometrics KW - sur AU - Zellner, Arnold PY - 1962/// UR - http://dx.doi.org/10.2307/2281644 ER -