How demographics drive economic performance

Between the mid-1960s and the mid-1980s, the population of developing economies increased by more than 1.3 billion people. This was larger than the total population of advanced economies at the time. For decades, such growth was seen as a threat. Rapid population increase was expected to slow income growth, reduce productivity, and lock countries into poverty. Yet global empirical data tell a more complex story. Economic outcomes depend not on how fast population grows, but on how it grows and when that growth happens.

Cross-country evidence shows a clear pattern: average population growth rates have little direct link to income growth per capita, while the structure of births and deaths, and changes in population growth over time, strongly shape labor markets, productivity, and economic performance.

From 1965 to 1985, developing economies experienced population growth on an unprecedented scale. In low-income countries, average annual population growth was about 2.2 percent. In middle-income economies, it reached roughly 2.5 percent. In advanced economies, population growth was much lower, close to 0.8 percent per year. At these rates, population in developing countries doubled in about 30 years. In industrial economies, the same process took close to a century.

At first glance, such numbers seem incompatible with rising living standards. But the data do not support this assumption. Many countries achieved economic growth despite rapid population increase. Others did not. This divergence helps explain why population growth alone cannot predict economic outcomes.

The key mistake in early debates was treating population growth as a single, uniform process. In reality, the same growth rate can reflect very different demographic dynamics. In some countries, growth comes from high birth rates combined with high death rates. In others, births are lower, but deaths fall even faster. In still others, growth reflects a demographic transition, where mortality declines first and fertility follows later.

These differences matter. They shape the age structure of the population, determine the share of people who can work, and influence labor supply for decades.

When population growth is driven by high fertility, the immediate result is a larger number of children and dependents. These groups do not contribute directly to production. Their economic contribution appears only after 15 to 25 years, when they enter working age. Until then, pressure on public budgets, education systems, and health care rises.

When population growth results from falling mortality, especially among working-age adults, the economic effect is much faster. Labor supply increases almost immediately. This can support output growth and income expansion.

Global data show that even with similar population growth rates, the share of people aged 15 to 64 can differ significantly across countries. Even in stable demographic models, the difference can reach several percentage points. At the national level, this translates into millions of workers and very different economic paths.

Between 1965 and 1985, the share of working-age population increased in almost all developing regions. In some cases, the change was dramatic. In one of the largest Asian economies, the working-age share rose by about 10 percentage points and approached levels seen in advanced economies. This shift created a strong boost to labor supply and income growth.

At the same time, another trend was at work. Labor force participation among working-age people declined. This reflected longer schooling and wider access to education. Young people stayed in school longer and entered the labor market later. As a result, two forces worked in opposite directions. The growing share of working-age population increased potential labor supply. Lower participation rates reduced it. These effects largely offset each other. The overall labor-to-population ratio remained relatively stable.

This balance is important. It shows that population growth does not automatically overwhelm labor markets. Economies can adjust through education, changes in participation, and productivity gains.

Structural transformation played a central role in this adjustment. Despite rapid population growth, developing economies moved labor out of agriculture and into more productive sectors. In low-income countries, the share of workers in agriculture fell from about 78 percent to 72 percent over 15 years. In middle-income countries, it declined from 66 percent to 55 percent. In higher-income developing economies, the drop was even larger, from roughly 45 percent to 29 percent.

In absolute terms, agricultural employment still increased. Across developing countries as a whole, the number of agricultural workers rose by nearly one-quarter, from about 670 million to more than 820 million. This highlights the scale of demographic pressure. But employment in industry and services expanded much faster.

The service sector absorbed most of the new labor force. In many countries, it became the main destination for new workers. Industry also grew, but more slowly on average, except in a few economies with strong industrial expansion.

From a productivity perspective, these shifts were decisive. Global data show that output per worker in agriculture was well below the economy-wide average. In low-income countries, it was roughly half the average level. In industry, output per worker exceeded the average by two to five times. Services also showed higher-than-average productivity.

Moving labor from agriculture into more productive sectors raised output per worker across the economy. In many countries, structural change accounted for 15 to 20 percent of productivity growth. In some cases, the contribution reached one-third or more.

Crucially, population growth did not reduce productivity in any sector. On the contrary, between 1965 and 1980, output grew faster than employment in all sectors, including agriculture. This directly contradicts the idea that surplus labor would depress efficiency.

Over the same period, real GDP in developing economies more than doubled. In industry, output increased by around 200 percent. Employment grew much more slowly. The result was a steady rise in output per worker.

Regression analysis across countries reinforces these conclusions. Over the long run, average population growth shows little or no relationship with income growth per capita. The estimated effects are small and statistically weak. This confirms that population growth alone does not determine economic success.

The picture changes over shorter periods. In the early 1980s, when global economic conditions weakened, countries with faster population growth experienced poorer outcomes. During this time, population growth was negatively associated with income growth and productivity. Demographic pressure made economies more vulnerable to external shocks.

The strongest results emerge when timing is taken into account. Countries where population growth slowed achieved faster economic growth. This happened through two channels. First, labor force per capita increased as large cohorts entered working age. Second, productivity rose as the share of workers increased and capital accumulation accelerated.

In other words, declining population growth opened a “demographic window of opportunity.” During this phase, economies benefit from a large workforce and relatively fewer dependents. Global data show that this timing effect, rather than population growth itself, has a stable link to income growth.

Breaking population growth into fertility and mortality confirms this logic. High fertility in the past can support growth if those cohorts are already working. High fertility today tends to slow growth by increasing dependency. Mortality effects are more complex, because falling death rates among children and adults have different economic implications.

The most subtle result relates to stages of demographic transition. In countries with low fertility and low mortality, population growth can coincide with faster income growth. In countries with high fertility and high mortality, the effect is neutral or negative. Demography does not act in a linear way. Context matters.

Although these findings are based on global experience in developing economies, the underlying patterns are highly relevant for countries with transition economies, including Kazakhstan.

The central lesson is clear: population growth itself is not a threat. Risk arises when growth is driven mainly by high fertility and rising dependency, without enough productive jobs. Growth can become a source of acceleration when it reflects falling mortality, a rising share of working-age people, and active structural change.

For Kazakhstan, timing is critical. The economic impact of today’s demographic trends will appear 15 to 25 years from now. This means policies on education, labor markets, and industrial development must be designed with future workforce structure in mind, not just current indicators.

Global experience shows that the biggest gains go to countries that use their demographic window to move labor into more productive sectors and raise output per worker. Without this shift, demographic potential turns into economic strain.

Workforce quality is equally important. A larger working-age population does not automatically raise incomes. Education, skills, and the availability of productive jobs are decisive.

The key message for Kazakhstan is simple. Demography is not destiny. It is an economic resource. But it works only with the right structure, the right timing, and active economic policy.

Economic development is not driven by the number of people. It is shaped by who those people are, how old they are, where they work, and when the economy absorbs their contribution. Population growth is no longer an automatic economic burden. Managed well, it can support growth. Managed poorly, it can slow it down.