What Stage of the Demographic Transition Is India In?

India sits broadly in late Stage 3 of the demographic transition, with national indicators increasingly pointing toward entry into Stage 4. The country’s total fertility rate has fallen to 1.9 children per woman, below the replacement level of 2.1 for the fifth consecutive year, while death rates have dropped substantially over the past three decades. But calling India a single-stage country obscures a reality that researchers keep returning to: different states, different income groups, and different communities are passing through different stages simultaneously, sometimes separated by decades of progress.

What the National Numbers Actually Show

The clearest marker of where a country falls in the demographic transition is its fertility rate, and India’s has changed dramatically. The national total fertility rate fell from 3.6 in 1992 to 1.9 in 2024, a gradual, sustained decline rather than a sudden drop.¹ A fertility rate below 2.1 means that, on average, Indian women are no longer having enough children to replace the current population over time. That is a hallmark of late Stage 3 or early Stage 4.

On the mortality side, the picture is equally clear. Female infant mortality fell from 81 deaths per 1,000 live births in 1990 to 33 by the time of the 2018 Sample Registration System report, while male infant mortality fell from 78 to 32 over roughly the same period.² Life expectancy has risen, though it remains stratified by wealth. People classified as multidimensionally poor have a life expectancy at birth about four years lower than those who are not, roughly 65 versus 69 years.³

Taken together, these trends are why some researchers describe India as moving from Stage 3 into Stage 4.⁴ Others describe it as still transitioning from Stage 2 to Stage 3, particularly when emphasizing that population growth remains substantial because of momentum built up during decades of high fertility.⁵ The disagreement is real, and it largely comes down to whether you foreground the national averages or the enormous gap between the country’s most and least advanced regions.

Why the Answer Depends on Where in India You Look

India’s demographic transition is not a single story. States like Kerala, Tamil Nadu, and Goa crossed below replacement fertility years ago and look, demographically, more like parts of Europe. Meanwhile, states with enormous populations tell a different story. Uttar Pradesh, India’s most populous state, had a fertility rate of 2.7 as recently as 2015–16, well above the national average of 2.18 at the time. Within Uttar Pradesh alone, district-level fertility ranged from 1.6 to 4.4, with the highest rates concentrated in districts where female schooling was lowest.⁶

This means that parts of India are functionally in Stage 2, with high fertility and declining but still elevated mortality, while others are firmly in Stage 4, with low birth rates, low death rates, and aging populations. Researchers frequently emphasize that applying a single stage label to all of India misrepresents the country’s diverse sociocultural and economic contexts.⁵ The north-south divide is the starkest version of this. Southern states transitioned earlier and are now grappling with aging workforces, while many northern and central states still have large, young populations and higher fertility.

For someone trying to understand India’s demographic position, the honest answer is that the country is not in one stage. It spans at least two, and in some pockets, three. The national average is late Stage 3, but that average papers over a 24-year variation in how quickly different parts of the country have moved through the transition.

The Role of Female Education and Contraception

If there is a single factor that best predicts where a given part of India falls in the demographic transition, it is female literacy. Across Indian states, every one percentage point increase in the female literacy rate was associated with a drop of about 0.3 in the crude birth rate per 1,000 people. Male literacy, by contrast, showed no significant independent relationship with birth rates once female literacy was accounted for.⁷

The relationship between education and fertility is not static, though. Research on India’s transition suggests that in the early stages, educating women is the main driver of fertility decline. But as the transition matures, the direction of influence partly reverses: lower fertility itself frees up household resources to educate daughters, creating a reinforcing cycle. Interestingly, much of the recent fertility reduction in India has come not from more women becoming literate over time, but from changes in the reproductive decisions of illiterate women themselves, likely driven by wider access to contraception, exposure to media, and shifting cultural norms around family size.⁸

On contraception, India’s method mix has long been dominated by female sterilization, a pattern quite different from most other large countries. From 1992 to 2016, sterilization remained the most common method, though use of pills and condoms increased over that period.⁹ The heavy reliance on a permanent method means that many Indian women essentially make a one-time contraceptive decision after reaching their desired family size, rather than managing fertility through reversible methods over many years. This has implications for how quickly fertility can respond to changing preferences and how much autonomy women exercise in timing their births.

The Epidemiological Transition Running in Parallel

Alongside the demographic transition, India has been undergoing a related shift in what people get sick and die from. In classical demographic transition theory, falling death rates come first from controlling infectious diseases, and then chronic conditions like heart disease, diabetes, and cancer become the leading causes of death as people live longer. India crossed this threshold around 2003 nationally, the year when non-communicable diseases and injuries first accounted for more of the disease burden than infectious and maternal causes.¹⁰

But just as with fertility, the timing varied enormously. The most developed states crossed this threshold as early as 1986, while the least developed states did not cross it until 2010, a 24-year gap within a single country.¹⁰ What makes India’s epidemiological transition particularly challenging is that the burden of chronic diseases has been rising in older age groups without fully replacing the burden of infectious diseases, so the country faces both simultaneously.¹¹ The health system must deal with tuberculosis and malaria in some populations while managing diabetes and cardiovascular disease in others, sometimes in the same household.

India’s Demographic Dividend Window

One of the most discussed consequences of the demographic transition is the so-called demographic dividend, the period when a country’s working-age population is unusually large relative to the number of children and elderly it must support. India’s working-age population, those aged 15 to 64, is projected to keep growing as a share of the total population until around 2036, after which it will begin to shrink. The child population has been falling steadily, while the elderly population will keep rising and is projected to overtake the child population in size after 2056. Modeling suggests India’s effective window of demographic opportunity runs from roughly 2011 to 2041, giving the country about 30 years to capitalize on this favorable age structure.¹²

Whether India actually reaps an economic benefit from that window is a separate and much less certain question. The demographic dividend is not automatic. It requires that the large working-age population actually has jobs, and here the evidence is sobering. Female labor force participation remains strikingly low, which means a large share of the working-age population is not contributing to measured economic output. Under constant participation rates, the ratio of non-workers to workers may never reach the favorable levels needed for a strong dividend.¹³

Even among those who do seek work, the picture is mixed. Before the pandemic, about 4.5 million people per year were leaving agriculture, but non-farm sectors were not creating enough jobs to absorb them along with newly educated job seekers. Educated youth unemployment ran around 18%, affecting roughly 24 million people, creating a large population of discouraged workers.¹⁴ The implication is stark: a favorable age structure alone does not produce a dividend. Without investment in education, health, and job creation, the bulge of working-age adults becomes a source of frustration rather than growth.¹⁵

On the positive side of the ledger, the growing working-age share has been measurably boosting per capita private savings across India. Demographic factors account for about one-quarter of the variation in private savings rates across Indian states, which supports the idea that the dividend mechanism is at least partly functioning on the savings side.¹⁶

Son Preference and the Sex Ratio

One demographic feature that the standard transition model does not account for is sex-selective behavior, and India is one of the countries where it has been most pronounced. Between 1987 and 2016, an estimated 13.5 million female births went “missing” in India, meaning they would have occurred under a natural sex ratio but did not, primarily due to sex-selective abortion. The annual number of missing female births actually increased over time, from about 350,000 per year in the late 1980s and 1990s to roughly 550,000 per year in the most recent decade studied.¹⁷

The pattern is especially stark for second and third births after a family has already had a daughter. The sex ratio for second-born children after an earlier daughter dropped from 930 girls per 1,000 boys in 1981 to 885 by 2016. For third-born children after two daughters, the ratio fell even further, to 788 girls per 1,000 boys.¹⁷ In other words, the more daughters a family already has, the more strongly son preference skews the sex ratio of subsequent births.

Geographically, the effect is concentrated in the northwestern and northern states. Punjab, Delhi, and Haryana show the strongest statistical effects of son preference on the sex ratio at birth, followed by Gujarat, Jammu and Kashmir, Uttarakhand, Rajasthan, Uttar Pradesh, and Bihar.¹⁸ Several southern states show little or no significant son-preference effect. This is yet another dimension of India’s internally varied demographic picture: the transition has brought fertility down everywhere, but it has not eliminated cultural preferences that distort the sex ratio, particularly in higher-parity births in specific regions.

Urbanization and Changing Family Structures

India’s demographic shift has not happened in a vacuum. It has been accompanied by rapid urbanization, and the two processes reinforce each other. As more people move to cities, family structures change. Analysis of macro-level panel data from 1991 to 2021 found that each unit increase in urbanization was associated with a 0.29 to 1.32 percent increase in nuclear family households, with rising literacy, economic changes, and women’s autonomy accelerating the trend.¹⁹ Nuclear families, in turn, tend to have fewer children than joint or extended families, partly because the economic calculus of childbearing changes when you do not have grandparents and relatives sharing the household burden.

Some researchers argue that the combination of sub-replacement fertility, rising individualism, and the shift toward nuclear families signals that parts of India may be entering what is sometimes called a “second demographic transition,” a concept originally developed to describe changes in family formation in Western Europe. In this framework, the shift goes beyond simply having fewer children to include later marriage, more cohabitation, higher divorce rates, and a greater emphasis on individual self-fulfillment over traditional family obligations. Whether this framework usefully describes India’s trajectory or imposes a Western template on a very different cultural context is a matter of ongoing debate, but the structural indicators of family nuclearization are moving clearly in that direction.

The Aging Challenge Ahead

Every country that passes through the demographic transition eventually faces a rising share of elderly people, and India is no exception. The timing is what makes India’s situation distinct. Because the transition is happening at a lower level of economic development than it did in most wealthy countries, India will be dealing with a large elderly population before it has built out the institutional infrastructure, pension systems, healthcare capacity, and social safety nets that wealthier nations developed alongside their aging.

The financial strain is already visible in the data. Households with high old-age dependency face roughly 50% higher odds of catastrophic health expenditure compared to households with no elderly dependents.²⁰ And the social protection programs that do exist face significant uptake problems. A study of elderly people below the poverty line in Delhi found that while about 80% were aware of the main old-age pension scheme, only about half were actually receiving it, with corruption and bureaucratic barriers cited as the main obstacles.²¹

After 2036, India’s working-age share will begin to shrink, and the old-age population will keep climbing. Projections suggest the elderly will outnumber children after 2056.¹² In a global context, India is following a path already walked by Japan, South Korea, China, and Thailand, though it is further behind on the timeline. Those countries have seen birthrate declines and population aging accelerate beyond initial projections, a pattern that could hold lessons for India as its own transition deepens.²² The difference is that India will face these pressures with a far larger population and a lower per capita income than any of those countries had at the equivalent stage, making the policy challenge substantially harder to manage.