Do demographic structure conditions sector contribution to economic growth? A machine learning approach
Ngueuleweu Tiwang Gildas (),
Ningaye Paul and
Fon Dorothy Engwali
Additional contact information
Ngueuleweu Tiwang Gildas: University of Dschang
Ningaye Paul: University of Dschang
Fon Dorothy Engwali: University of Dschang
Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2025, vol. 27, issue 2, No 7, 2941 pages
Abstract:
Abstract This paper examines the impact of demographic structure on sector contribution to economic growth. It adopts a double robust instrumental variable of the heterogeneous treatment effect coupled with policy learning methodologies applied in machine learning. The paper uses data from 210 countries from 1990 to 2020 from the World Development Indicators databases. The paper introduces a new descriptive statistic tool termed the demography evolution plot by the authors. Results from the study are threefold. First, for the impact of demographic structure on economic growth within the fast-growing population, (a) the impact is globally negative on agriculture’s GDP but if the working-age ratio of the population is more than 87%, then the effect is reversed and (b) the impact on service GDP is globally negative but the effect is inversed if the elderly share within the population is less than 27%. Second, for the impact of demographic structure on economic growth within the population with high mortality, (a) the impact is globally negative on agriculture GDP and (b) the impact on services GDP is negative. Third, for the impact of demographic structure on economic growth within the aging populations, (a) the impact is strongly positive on agriculture GDP. In addition, world economy is mostly driven by an increasing service sector, the industry sector is constant, and the agriculture sector is decreasing worldwide. The paper suggests that countries should consider their demographic structure as an instrument for policy analysis to better profit from the potentials of each sector of their economy.
Keywords: Demographic structure; Sector economic growth; Machine learning; GDP; Demography evolution plot (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10668-023-04147-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:spr:endesu:v:27:y:2025:i:2:d:10.1007_s10668-023-04147-3
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/10668
DOI: 10.1007/s10668-023-04147-3
Access Statistics for this article
Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development is currently edited by Luc Hens
More articles in Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().