Affiliations: Instituto Nacional de Estadística y Geografía (INEGI), H. de Nacozari 2301, Aguascalientes 20276, México . Tel.: +52 449 910 5431; E-mail: [email protected]
Abstract: In this paper, we present an approach for the estimation of income
distributions, which deals with survey data shortcomings through
simultaneous consideration of other statistical sources and through
adjustment for compatibility with all of them. We show how our proposal
deals both with survey income under-reporting, and with under representation
of households with very large incomes, which are known to affect the results
of the survey. Our proposal has the purpose of selecting the distributional
model that best fits the data from the survey, using a Constrained Pseudo
Log-likelihood criterion, and is based on well-established statistical
criteria and methods and thus reduces the need for subjective or arbitrary
choices. The proposed procedure is applied to Mexican data from the National
Survey on Household Income and Expenditure for the year 2012 and from
Mexico's System of National Accounts, two sources that produce widely
differing results regarding total national household current income. We show
that, among all fitted models, a satisfactory explanation is given by a
4-parameter Generalized Beta Type 2 distribution. The chosen distribution
has little impact on the official poverty measurement. The Gini coefficient,
however, reaches a value as high as 0.803.