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＜紀要論文＞
Parametric Approximations of a New Functional Form for Estimating the Lorenz Curve
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| 概要 | The Lorenz curve is a most powerful tool in the analysis of the size distribution of income and wealth. In the past, many authors have been proposed different functional forms for estimating the Loren...z curve. The problem of indirect approach for estimating the Lorenz curve is that it is difficult to find any one hypothetical statistical distribution to serve as a good approximation over the entire range of an actual batch of income data. That is why, the principle objective of this paper is to present direct parametric approximations of a new functional form for estimating the Lorenz curve. We can compare these alternative forms by goodness of fit, F-tests of nested forms, and measurement of the Gini coefficients, Kakwani and Chakravarty inequality indices.続きを見る |
| 目次 | 1. Introduction 2. Meaning of Heteroscedasticity 3. Plausible Sources of Heteroscedasticity 4. Consequences of Heteroscedasticity 5. Deriving Some Important Properties of the OLSE of Parameters for the Specific Form of Heteroscedasticity that is，σ_i^2=σ^2 X_i^2 with the Additional Condition that，∑_(i=1)^nX_i^2 =n 6. Theoretically Proof of the Efficiency of the GLSE with Compare to the OLSE of the Parameters for the Specific Form of Heteroscedasticity that is，σ_i^2=σ^2 X_i^2 with the Additional Condition that，∑_(i=1)^nX_i^2 =n 7. Data Collection 8. Discussion on Empirical Results on the Basis of the Given Data Set 9. Discussion and Conclusion |
詳細
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| 登録日 | 2020.05.28 |
| 更新日 | 2020.10.14 |