Understanding the Concept of Optimum Population

How many people is “the right number” for a country? It is a deceptively simple question that has occupied economists for nearly a century. The concept of optimum population tries to answer it by linking the size of a population to the resources, technology, and welfare available to its people. Rather than asking how many people the land can feed, it asks how many people the economy can support while still ensuring the highest possible standard of living. For a country like India, which crossed 1.46 billion people in 2024 to become the world’s most populous nation, this question has moved from textbook theory to live policy debate.

What is optimum population? 🔗

Optimum population is the size of population that, given a country’s natural resources, capital stock, and technology, yields the maximum per capita income and economic welfare. It is neither the largest population a country can physically sustain nor the smallest one that can survive comfortably. It sits at a balance point where every additional worker still adds more to output than they consume, and every unutilised resource is being put to productive use.

The idea was first systematically developed by the English economist Edwin Cannan in his 1924 book Wealth. Cannan rejected the gloom of Malthusian thinking, which had argued that population growth would inevitably outstrip food supply. Instead, he proposed that there exists an ideal population for every country, determined not just by food but by the broader relationship between people and wealth-producing resources. The theory was later refined by Lionel Robbins, Hugh Dalton, and Alexander Carr-Saunders, who gave it the structure we study today.

How economists have defined the optimum 🔗

While the broad idea is shared, different economists have emphasised different dimensions of the optimum.

Edwin Cannan and Carr-Saunders: maximum economic welfare 🔗

Cannan framed the optimum as the population that best matches a country’s productive capacity. Carr-Saunders, in his influential book World Population, defined it as “that population which produces maximum economic welfare.” Welfare here is broader than income alone; it includes the general well-being that flows from balanced economic activity.

Lionel Robbins: maximum returns 🔗

Robbins took a sharper, productivity-based view. He described the optimum as the population that just makes the maximum returns possible, the best possible population given existing resources. His framing draws attention to the marginal contribution of an additional worker.

Hugh Dalton: maximum income per head 🔗

Dalton offered the most quantitative formulation. For him, optimum population is “that which gives the maximum income per head.” He went further and gave a formula to measure deviation from the optimum, calling it maladjustment (M). If A is the actual population and O is the optimum, then M = (A − O) / O. A positive M signals over-population, a negative M signals under-population, and M = 0 indicates the country is exactly at its optimum. The formula is, as most demographers acknowledge, of mainly academic interest because O cannot be measured precisely in practice.

Joan Robinson and Kenneth Boulding: refinements 🔗

Joan Robinson, the Cambridge economist, focused on the relationship between population size and average output per person, arguing that the optimum is the level at which average product per worker is maximised. Kenneth Boulding tied the idea directly to living standards, stating that “the population at which the standard of living is at maximum is called the optimum population.” He also drew attention to the role of diminishing returns: once each additional person begins to lower average welfare, the country has passed its optimum.

A dynamic, not static, concept 🔗

One crucial insight running through all these definitions is that the optimum is not a fixed number. As economists have long noted, the optimum shifts whenever technology improves, capital stock grows, or new resources become available. A discovery of new energy sources, a leap in agricultural productivity, or a wave of automation can all push the optimum upward, allowing more people to live well on the same land base.

Criteria for measuring optimum population 🔗

If economists cannot pin down a single number, how do they judge whether a country is close to its optimum? In practice, several indicators are read together.

Per capita income 🔗

This remains the central yardstick. A rising per capita income, especially when it outpaces population growth, suggests the country is moving closer to (or staying within) its optimum range. India’s real per capita income rose from around ₹83,003 in FY 2016-17 to ₹1,08,786 in FY 2023-24 at constant prices, indicating that economic output has, on average, grown faster than population in recent years.

Full employment 🔗

An economy at its optimum population should be able to productively employ those who want to work. Widespread open unemployment or large-scale disguised unemployment, particularly in agriculture, is a classic sign of over-population. Conversely, chronic labour shortages and unfilled jobs suggest under-population.

Life expectancy and health outcomes 🔗

Healthy populations live longer, work longer, and place less strain on care systems relative to what they produce. Rising life expectancy, falling infant mortality, and improved nutrition all suggest the population-resource balance is working. Sharp deteriorations in these indicators often accompany over-population stress.

Balanced resource use 🔗

An optimum population uses natural resources at a pace they can be regenerated or substituted. Water tables that are not falling, soils that are not degrading, air quality that is not collapsing, and forests that are not shrinking faster than they regrow are all markers of a sustainable balance. Persistent ecological deficit is a red flag for over-population, even if income statistics look healthy.

Quality of life and welfare indicators 🔗

Modern formulations of optimum population go beyond income to include access to housing, education, clean water, sanitation, and basic services. Composite indices like the Human Development Index, although not designed for this purpose, give a fuller picture of whether welfare is genuinely improving as the population changes.

Dependency ratio 🔗

A low dependency ratio (a smaller share of children and elderly relative to working-age adults) creates the demographic conditions under which per capita income can rise quickly. India currently has about 68 percent of its population in the 15-64 working-age group, which is exactly the kind of structure that places a country closer to its productive optimum, provided jobs and skills match the workforce.

Challenges in achieving optimum population 🔗

For all its conceptual appeal, the optimum population idea is notoriously difficult to put to work in policy.

Measurement problems 🔗

Dalton’s formula assumes we can know O, the optimum level. We cannot. There is no agreed method to calculate the exact population size that would maximise per capita income for a given country at a given time. Economists can say a country is roughly over- or under-populated, but rarely by how much.

The optimum keeps moving 🔗

Because technology, capital, and resource availability change constantly, today’s optimum is not tomorrow’s. A breakthrough in renewable energy or in agricultural yields can suddenly raise the optimum by tens of millions. This makes the target a moving one, and policy designed for last decade’s optimum may already be obsolete.

Welfare is more than income 🔗

Different societies value different things: leisure, equality, environmental quality, cultural continuity, and so on. A purely income-maximising optimum may not be the one most people would actually choose. Economists like Partha Dasgupta and James Meade have long debated whether welfare should be measured per person or in total, and the answers give very different “optima”.

Regional and demographic imbalances 🔗

A national average can hide enormous internal variation. Within India, southern states like Kerala and Tamil Nadu have fertility rates well below replacement and ageing populations, while Bihar’s total fertility rate remains around 3.0. As an ORF analysis points out, this means India’s demographic shift will be deeply uneven, with some states facing labour shortages while others struggle with youth unemployment. A single national “optimum” oversimplifies this reality.

Policy lag and ethical limits 🔗

Even if we knew the optimum, populations change slowly. Fertility decisions are personal, and coercive policies have historically produced poor outcomes and ethical violations. Achieving the optimum is more about creating conditions, such as education for girls, employment opportunities, healthcare, and old-age security, than about hitting a target number.

Global interconnections 🔗

In an open economy, optimum population at the country level is complicated by trade, migration, and shared environmental commons. A country can sustain more people than its domestic resources alone allow by importing food, energy, and capital, but this links its optimum to global conditions it does not fully control.

Why this matters for India today 🔗

India’s situation makes the optimum population debate especially relevant. The country’s total fertility rate has fallen to about 1.9 births per woman, below the replacement level of 2.1, even as the total population is still growing because of demographic momentum. UN projections suggest India’s population will peak around 1.7 billion in the early 2060s before slowly declining.

Whether that peak coincides with India’s optimum depends on what happens next: whether enough productive jobs are created for the working-age bulge, whether skill levels rise to match industrial demand, whether public investment in health and education keeps up, and whether infrastructure can absorb the largest urbanisation wave in history. A recent Carnegie analysis warns that without these investments, the demographic window could close before the country gets rich, the very risk that the optimum population framework was designed to flag.

In other words, the question is no longer simply “are we too many?” It is “are we organising our resources, institutions, and policies so that the population we have can flourish?” That, ultimately, is what optimum population theory has always been about.

What do you think? Given how rapidly technology and resources change, do you think any country can ever truly identify its optimum population, or is the concept more useful as a guiding principle than as a measurable target? And in a federal country like India, where states differ dramatically in their fertility and development levels, should the “optimum” be calculated nationally or state by state?

References

1. https://www.economicsdiscussion.net/population/the-optimum-theory-of-population-with-diagram/4473
2. https://www.yourarticlelibrary.com/population/the-optimum-theory-of-population-economics/10891
3. https://www.sociologydiscussion.com/demography/population-demography/optimum-theory-of-population/3078
4. https://www.encyclopedia.com/social-sciences/encyclopedias-almanacs-transcripts-and-maps/optimum-population
5. https://www.india-briefing.com/news/india-per-capita-income-consumption-trends-40653.html/
6. https://www.capitalgroup.com/institutional/insights/articles/india-leveraging-population-boom-for-growth.html
7. https://www.orfonline.org/research/india-could-age-before-it-becomes-rich-from-demographic-dividend-to-productivity-dividend
8. https://worldpopulationclock.net/india-population-key-facts-future-outlook/
9. https://niua.in/blogs/understanding-india%E2%80%99s-population-trajectory-insights-world-population-prospects-2024
10. https://carnegieendowment.org/research/2026/04/indias-demographic-dividend-is-a-test-of-governance