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Titlebook: Contributions to Econometric Theory and Application; Essays in Honour of R. A. L. Carter,J. Dutta,A. Ullah Book 1990 Springer-Verlag New Y

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https://doi.org/10.1007/978-3-642-51169-1eral inequality measures that are used to test whether observed differences in sample estimates are statistically significant. The results presented in the paper are used to analyze income inequality in Côte d’Ivoire from the data of the Living Standards Survey, 1985.
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https://doi.org/10.1007/978-3-642-51169-1cients of dynamic simultaneous linear equations models. Various versions of the instrumental variables estimator were obtained by using differing amounts of prior information to choose the instrument set. The results suggest that the asymptotically correct standard normal distribution is a poor approximation when samples are very small.
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T. Hellman,S. Schumacher,K. W. Zimmermanncterized by two scalars. This article reviews briefly the results dealing with the properties of estimators. Specifically, the issues in finite sample properties are highlighted and an appraisal is presented.
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Finite Sample Econometrics: A Unified Approach,xact moments and the distributions of econometric estimators and test statistics. The results are derived for the normal case and extended for non-normal cases as well. A general result on the approximations is also given.
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,Regional Inequality by Components of Income: United States, 1969–1986,rovide insight into asymmetries of intertemporal change, differences in inequality at a point in time compared with changes in that inequality over time, and identification of regional contribution to inequality.
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A Monte Carlo Study of Structural Estimator Distributions After Performance of Likelihood Ratio Prely) restricted structural coefficient estimators such as 2SLS and 3SLS are “approximately” statistically independent over a broad range of Type I error levels of for the test statistic. The results of the Monte Carlo experiments based on the Klein model I are not conclusive, though they tend to support approximate independence in most cases.
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Estimation and Testing of Regression Coefficients in Cobb-Douglas and Other Models, are in the spirit of full information maximum likehood (FIML) and to develop test statistics that are of the Student sort, provided that the reduced form errors have normal properties often used for analysis of this sort.
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