Eckernkemper, Tobias and Gribisch, Bastian . Classical and Bayesian Inference for Income Distributions using Grouped Data. Oxf. Bull. Econ. Stat.. HOBOKEN: WILEY. ISSN 1468-0084

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Abstract

We propose a general framework for Maximum Likelihood (ML) and Bayesian estimation of income distributions based on grouped data information. The asymptotic properties of the ML estimators are derived and Bayesian parameter estimates are obtained by Monte Carlo Markov Chain (MCMC) techniques. A comprehensive simulation experiment shows that obtained estimates of the income distribution are very precise and that the proposed estimation framework improves the statistical precision of parameter estimates relative to the classical multinomial likelihood. The estimation approach is finally applied to a set of countries included in the World Bank databasePovcalNet.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Eckernkemper, TobiasUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Gribisch, BastianUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-319856
DOI: 10.1111/obes.12396
Journal or Publication Title: Oxf. Bull. Econ. Stat.
Publisher: WILEY
Place of Publication: HOBOKEN
ISSN: 1468-0084
Language: English
Faculty: Unspecified
Divisions: Unspecified
Subjects: no entry
Uncontrolled Keywords:
KeywordsLanguage
GENERALIZED BETAMultiple languages
Economics; Social Sciences, Mathematical Methods; Statistics & ProbabilityMultiple languages
URI: http://kups.ub.uni-koeln.de/id/eprint/31985

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