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Towards a More Realistic Estimate of the Income Distribution in Mexico
Author(s) -
Bustos Alfredo,
Leyva Gerardo
Publication year - 2017
Publication title -
latin american policy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.195
H-Index - 4
eISSN - 2041-7373
pISSN - 2041-7365
DOI - 10.1111/lamp.12114
Subject(s) - income distribution , distribution (mathematics) , gini coefficient , econometrics , survey data collection , stability (learning theory) , lorenz curve , maximum likelihood , economics , estimation , statistics , economic inequality , mathematics , inequality , computer science , mathematical analysis , management , machine learning
Accurate estimations of income distributions from survey data and other sources have proven elusive. This article presents an approximation to an income distribution in Mexico for 2012, using three data sources, household‐survey data, SNA figures, and tax records. It also considers derived measures such as Gini coefficients. Constrained Maximum Pseudo‐likelihood (CMPL) estimation is used to obtain an income distribution that reconciles all three data sources under different conditions, and results show remarkable stability.