Anova-type consistent estimators of variance components in unbalanced multi-way error components models
AbstractThis paper introduces three new Anova-type consistent estimators of variance components for use in multi-way unbalanced error components models, with possibly non-normal errors and endogenous regressors. They are easy to compute and are proved to be consistent under mild regularity conditions. For the first time proofs of consistency for Anova estimators are offered under such a general class of models, providing novel insights into the impact of unbalancedness on the large-sample properties of the estimators. A battery of Monte Carlo experiments and an empirical application to US production data show that the estimators perform reasonably well, in comparison to unbiased methods incorporating finite-sample corrections.
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Bibliographic InfoPaper provided by KITeS, Centre for Knowledge, Internationalization and Technology Studies, Universita' Bocconi, Milano, Italy in its series KITeS Working Papers with number 034.
Length: 86 pages
Date of creation: Oct 2010
Date of revision: Oct 2010
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Find related papers by JEL classification:
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
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