Poverty, income distribution and CGE micro-simulation modeling: Does the functional form of distribution matter? |
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Authors: | Dorothée Boccanfuso Bernard Decaluwé Luc Savard |
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Institution: | (1) GRéDI, Faculté d’administration, Université de Sherbrooke, 2500, boul. de l’Université, Sherbrooke (Québec), Canada, J1K 2R1;(2) CIRPEE, Université Laval, J-A De Sève, Québec, Canada |
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Abstract: | This paper explores income distribution modeling approaches for poverty analysis in a CGE micro-simulation context. Income
distribution functional forms such as the lognormal, Pareto, beta distribution and empirical methods are currently used in
CGE models in parallel with the estimation of FGT poverty indices. The particular methods or functional forms used in this
context are not always clearly defined and justified. In this paper, we investigate and provide better criteria for selecting
a functional distribution for poverty analysis. To achieve this, we apply parametric estimation to seven functional forms
and compare the results to a purely “empirical” method. The results showed that no single form is more appropriate in all
instances or for all household subgroups. The choice of a modeling approach should be motivated by a search for best fit and
should be based on appropriate statistical tests. Selecting inappropriate distributional forms can lead to biased results
in terms of poverty analysis. Introducing functional forms in the empirical approach can also provide greater confidence in
the results obtained.
An erratum to this article can be found at |
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Keywords: | Computable general equilibrium models Estimation Measurement and poverty analysis Personal income and wealth distribution |
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