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http://dx.doi.org/10.5351/CKSS.2009.16.4.659

Application of Generalized Maximum Entropy Estimator to the Two-way Nested Error Component Model with III-Posed Data  

Cheon, Soo-Young (KU Industry-Academy Cooperation Group Team of Economics and Statistics, Korea University)
Publication Information
Communications for Statistical Applications and Methods / v.16, no.4, 2009 , pp. 659-667 More about this Journal
Abstract
Recently Song and Cheon (2006) and Cheon and Lim (2009) developed the generalized maximum entropy(GME) estimator to solve ill-posed problems for the regression coefficients in the simple panel model. The models discussed consider the individual and a spatial autoregressive disturbance effects. However, in many application in economics the data may contain nested groupings. This paper considers a two-way error component model with nested groupings for the ill-posed data and proposes the GME estimator of the unknown parameters. The performance of this estimator is compared with the existing methods on the simulated dataset. The results indicate that the GME method performs the best in estimating the unknown parameters in terms of its quality when the data are ill-posed.
Keywords
Two way nested error component; III-posed; GME estimation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Jaynes, E. T. (1957a). Information theory and statistical mechanics, Physics Review, 106, 620-630   DOI
2 Jaynes, E. T. (1957b). Information theory and statistical mechanics II, Physics Review, 108, 171-190   DOI
3 Amemyia, T. (1971). The estimation of the variances in a variance components model, International Econometric Review, 12, 1-13   DOI   ScienceOn
4 Beisley, D. (1991). Conditioning Diagnostics: Collinearity and Weak Data in Regression, John Wiley & Sons, New York
5 Cheon, S. and Lim, S. S. (2009). Generalized maximum entropy estimator for the linear regression model with a spatial autoregressive disturbance, Communications of the Korean Statistical Soci-ety, 16, 265-274   과학기술학회마을   DOI   ScienceOn
6 Golan, A. (1994). A multi-variable stochastic theory of size distribution of firms with empirical evidence, Advances in Econometrics, 10, 1-46
7 Golan, A. and Judge, G. (1996). Recovering Information in the Case of Partial Underdetermined Problems and Incomplete Data, John Wiley & Sons, New York
8 Swamy, P. A. V. B. and Arora, A. A. (1972). The exact finite sample properties of the estimators of coefficients in the error components regression models, Econometrica, 40, 261-275   DOI   ScienceOn
9 Judge, G. G. and Golan, A. (1992). Recovering information in the case of ill-posed inverse problems with noise, Unpublished paper, University of California at Berkeley
10 Song, S. H. and Cheon, S. (2006). A study of generalized maximum entropy estimator for the panel regression model, The Korean Journal of Applied Statistics, 19, 521-534   과학기술학회마을   DOI   ScienceOn
11 Wallace, T. D. and Hussain, A. (1969). The use of error components models in combining cross-section and time-series data, Econometrica, 37, 55-72   DOI   ScienceOn