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An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias
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 “independent” 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.
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Citations
Cited by
(2001) · RePEc: Research Papers in Economics · Cited by 27,577
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Pesaran, M. H. (2004) · doi:10.2139/ssrn.572504 · Cited by 8,738
Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data
Driscoll, J. C., & Kraay, A. C. (1998) · Review of Economics and Statistics · doi:10.1162/003465398557825 · Cited by 6,865
Pooled Mean Group Estimation of Dynamic Heterogeneous Panels
Pesaran, M. H., Shin, Y., & Smith, R. P. (1999) · Journal of the American Statistical Association · doi:10.1080/01621459.1999.10474156 · Cited by 6,683
Exploring the Black Box: An Analysis of Work Group Diversity, Conflict and Performance
Pelled, L. H., Eisenhardt, K. M., & Xin, K. R. (1999) · Administrative Science Quarterly · doi:10.2307/2667029 · Cited by 2,971
Metadata
- Authors
- Zellner, A.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1962-06
- Volume
- 57
- Issue
- 298
- Pages
- 348-368
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2094514178
- Cited by
- 8,401
- References
- 0
- FWCI
- 8.86
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1962.10480664
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