Full Citation

Title: A generative model for age and income distribution

Citation Type: Journal Article

Publication Year: 2022

ISBN:

ISSN:

DOI: 10.1140/epjds/s13688-022-00317-x

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Abstract: Each individual in society experiences an evolution of their income during their lifetime. Macroscopically, this dynamic creates a statistical relationship between age and income for each society. In this study, we investigate income distribution and its relationship with age and identify a stable joint distribution function for age and income within the United Kingdom and the United States. We demonstrate a flexible calibration methodology using panel and population surveys and capture the characteristic differences between the UK and the US populations. The model here presented can be utilised for forecasting income and planning pensions.

Url: https://doi.org/10.1140/epjds/s13688-022-00317-x

User Submitted?: Yes

Authors: Ozhamaratli, Fatih; Kitov, Oleg; Barucca, Paolo

Periodical (Full): EPJ Data Science

Issue: 4

Volume: 11

Pages: 1-27

Data Collections: IPUMS CPS

Topics: Aging and Retirement, Labor Force and Occupational Structure, Population Data Science

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