EconPapers    
Economics at your fingertips  
 

Forecasting Income Inequality with Demographic Projections

Terence Tai Leung Chong and Yiu Tung Ka

MPRA Paper from University Library of Munich, Germany

Abstract: This paper provides a first attempt in the literature to forecast the future evolution of income inequality with the demographic projections. The contribution of this paper is twofold. First, we establish a framework to quantify and analyze the effects of population ageing and the secular upward trend in educational attainment on income inequality. Second, we modify the human capital model and perform microsimulations to forecast a list of standard measures of income inequality of Hong Kong for the coming years of 2021, 2026 and 2031 based on the projected changes in the demographic structure of Hong Kong’s working population. The pseudo out-of-sample forecasts are reasonably close to the corresponding realized values. Our true out-of-sample forecasts suggest that income disparity will be alleviated in the next 15 years, as a result of the increasingly equal spread of level of schooling across the workforce.

Keywords: Income Inequality; Demographic Projections; Population Ageing. (search for similar items in EconPapers)
JEL-codes: D63 J11 (search for similar items in EconPapers)
Date: 2019-12-01
New Economics Papers: this item is included in nep-age and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/99160/1/MPRA_paper_99160.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:99160

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().

 
Page updated 2025-03-22
Handle: RePEc:pra:mprapa:99160