A statistical approach to address the problem of heaping in self-reported income data

DOI10.1080/02664763.2015.1077372OpenAlexW2292520441MaRDI QIDQ5138029

A. Würbach, S. Zinn

Publication date: 3 December 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2015.1077372

zbMATH Keywords

heapingGerman national educational panel studyself-reported income datazero-inflated log-normal distribution

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Applications of statistics to social sciences (62P25) Point estimation (62F10) Parametric inference under constraints (62F30) Statistical sampling theory and related topics (62D99)

Related Items (1)

A shared parameter mixture model for longitudinal income data with missing responses and zero rounding

Uses Software

• Maxlik
• MICE
• maxLik

Cites Work

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• Ignorability and coarse data
• Truth and memory: linking instantaneous and retrospective self-reported cigarette consumption
• maxLik: a package for maximum likelihood estimation in R
• Fully conditional specification in multivariate imputation
• Statistical Size Distributions in Economics and Actuarial Sciences
• Measures and tests of heaping in discrete quantitative distributions
• A Simplex Method for Function Minimization

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