Working Age Population Projection across Indian Subcontinent’s countries

population-projection-working-age-group-indian-subcontinents-countries-2023

KEY POINTS

● The working-age population represents one of the key demographic segments typically defined as individuals between 15 and 64 years old who can participate in economic activities. This group is the primary workforce driving economic productivity, innovation, and national development.

● India and Pakistan demonstrate remarkably similar workforce distributions, with their 25-54 age group comprising 61.75% and 62.00% of the population.

● The youth demographic (15-24 years old) presents an intriguing aspect of the regional landscape. Bangladesh leads this segment with 44.70% of its population in this age group.

● Conversely, the older workforce segment (55-64 years) remains consistently small across all countries, ranging from 1.19% in Afghanistan to 4.22% in Sri Lanka.

The working-age population represents one of the key demographic segments typically defined as individuals between 15 and 64 years old who can participate in economic activities. This group is the primary workforce driving economic productivity, innovation, and national development. In most of the countries, the working-age population generates the majority of economic output, pays taxes, supports social systems, and contributes to societal progress. The proportion and characteristics of this population segment have profound implications for a nation’s economic potential, with a large, skilled working-age population often indicating opportunities for robust economic growth. In contrast, a diminishing or poorly skilled workforce can signal potential economic challenges. Understanding the working-age population’s composition, skills, and distribution provides crucial insights into a country’s economic health and future development trajectory, making it a key focus for policymakers, economists, and social planners.

The working-age population, typically defined as individuals between 25 and 54 years old, emerges as the dominant demographic segment across all countries in the dataset. This core workforce represents the primary economic engine, driving productivity, innovation, and economic growth. This group stands out most prominently in Sri Lanka, with an impressive 69.42% of the population falling within this critical age range, which suggests a particularly robust and mature workforce with significant potential for economic development and sustained productivity.

India and Pakistan demonstrate remarkably similar workforce distributions, with their 25-54 age group comprising 61.75% and 62.00% of the population, respectively. This consistency suggests comparable demographic structures and potential labour market dynamics. Both countries represent large, young populations with substantial economic potential, capable of driving significant economic transformation in the coming decades.

The youth demographic (15-24 years old) presents an intriguing aspect of the regional landscape. Bangladesh leads this segment with 44.70% of its population in this age group, followed closely by Afghanistan at 39.79%. This substantial youth population represents a critical reservoir of potential workforce, education, and future economic innovation. The high proportion of young people suggests these countries have significant opportunities for skill development, education, and workforce expansion.

Conversely, the older workforce segment (55-64 years) remains consistently small across all countries, ranging from 1.19% in Afghanistan to 4.22% in Sri Lanka. This narrow band of older workers highlights the region’s youthful demographic structure and potential challenges in pension systems and elder care. Bhutan and Nepal present interesting intermediate cases, with balanced workforce distributions that closely mirror the regional trends. Their workforce compositions suggest gradual economic transitions, with robust middle-aged populations supported by significant youth segments.

These demographic insights tell us a story beyond mere numbers. It reflects complex historical, economic, and social dynamics unique to each country. Historical development patterns, education systems, healthcare improvements, and economic opportunities have shaped these population distributions. From an economic perspective, these distributions offer both opportunities and challenges. The large working-age populations in countries like India, Pakistan, and Bangladesh represent a potential “demographic dividend” – a window of economic opportunity where a large working-age population can drive significant economic growth if accompanied by appropriate education, skills, and economic infrastructure investments.

However, this potential is not automatic. Successfully leveraging this demographic structure requires strategic investments in education, skill development, job creation, and economic diversification. Countries must create environments that can absorb and productively employ their large youth and working-age populations. This overview of workforce distribution underscores the importance of understanding demographic structures as more than static statistics. As these countries continue to develop, their ability to effectively utilize and develop their human capital will be crucial in determining their economic and social progress.

References

  1. OECD. (n.d.). Working age population. Retrieved December 6, 2024, from https://www.oecd-ilibrary.org/social-issues-migration-health/working-age-population/indicator/english_d339918b-en#:~:text=The%20working%20age%20population%20is,age%20population%20in%20total%20population.
  2. United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024: Data Sources. (UN DESA/POP/2024).
  3. EY India. (2023, April 11). Reaping the demographic dividend. https://www.ey.com/en_in/insights/india-at-100/reaping-the-demographic-dividend

 



About Author



 

Pankaj Chowdhury is a former Research Assistant at the International Economic Association. He holds a Master’s degree in Demography & Biostatistics from the International Institute for Population Sciences and a Bachelor’s degree in Statistics from Visva-Bharati University. His primary research interests focus on exploring new dimensions of in computational social science and digital demography.

Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of 360 Analytika.

Acknowledgement: The author extends his gratitude to the UN World Population Prospects for providing data support.

This article is posted by Sahil Shekh, Editor-in-Chief at 360 Analytika.

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