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Robust estimation of personal income distribution models

Victoria-Feser, Maria-Pia (1993) Robust estimation of personal income distribution models. DARP (4). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.

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Statistical problems in modelling personal income distributions include estimation procedures, testing and model choice. Typically, the parameters of a given model are estimated by classical procedures such as maximum likelihood and least squares estimators. Unfortunately, the classical methods are very sensitive to model derivations such as gross errors in the data, grouping effects or model misspecifications. These deviations can ruin the values of the estimators and inequality measures and can produce false information about the distribution of the personal income in a given country. In this paper we discuss the use of robust techniques for the estimation of income distributions. These methods behave as the classical procedures at the model but are less influenced by model deviations and can be applied to general estimation problems.

Item Type: Monograph (Discussion Paper)
Official URL:
Additional Information: © 1993 Maria-Pia Victoria-Feser
Divisions: STICERD
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HD Industries. Land use. Labor
JEL classification: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C13 - Estimation
D - Microeconomics > D6 - Welfare Economics > D63 - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
Date Deposited: 07 Jul 2008 15:59
Last Modified: 15 Sep 2023 22:41

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