How India can align its policies basis varied demographics across states to optimize growth

India’s demographic dividend can unleash powerful growth-promoting forces in the coming years. 

In brief

• Varied trends in the shares of working age and ageing populations across states necessitate understanding of state-specific demographics.
• These state-specific demographic dividend impact policy initiatives such as investment in infrastructure, skill development, education, and health.
• Customizing policies at the state level can not only help address the needs of different age groups but also optimize long-term growth for the country. 

As per the UN World Population Dashboard, India’s population for 2023 at 1428.6 million has exceeded that of China’s at 1425.7 million. From here on, India would remain the largest country by population in the world for the remaining decades of the 21st century and beyond. As years pass by, India’s working age population (WAP) would exceed that of China by progressively larger amounts. This dividend is expected to usher in a virtuous circuit of growth promoting developments. As the share of WAP increases, and correspondingly the dependency ratios fall, the saving and investment rates are expected to increase along with an increase in the available labor force.

Why is there a need to recognize state-differentiated demographic dividend?

One important dimension of India’s demographic dividend is the differential evolution of the age profile across states. Many of the large population and relatively less developed states such as Bihar, Uttar Pradesh, Madhya Pradesh, Rajasthan and Odisha will have relatively younger population during the later decades of the century. On the other hand, some of the present day developed states are already characterized by ageing populations. This differentiated demographic profile across states will have significant policy implications. Priorities for training, educating and skilling of the population may take into account the time differentiated demographic profiles of Indian states with a view to generating an optimal growth impact.  

How median ages evolve at differentiated pace across states

The latest available Census figures in India still pertain to 2011 as the 2021 census has not been conducted yet due to delays caused by COVID-19. The Ministry of Health and Family Welfare (MoHFW) however, has projected forward, state-wise population up to 2036. Based on these projections, Table 1 shows that there are considerable differences in the way the size and age profiles of state wise population are going to evolve. One common trend, however, is that population growth rates are expected to fall across all states. For some high per capita income states, such as Andhra Pradesh, Tamil Nadu, Kerala, and Telangana, population growth rates would fall to near-zero by 2036. In some of the present-day less developed states such as Odisha, Punjab, Karnataka and UP, population growth rates are expected to be in the range of 0.3% to 0.5%. Bihar, being the lowest per capita income state presently, would still show a population growth rate of 1% by 2036. As a result of these differential population growth rates, the age structure of the population of different states also shows different profiles. This is summarily captured in the inter-state profile of the median age of the population. By 2036, Tamil Nadu would have the highest median age of 40.5 years, while median age in Bihar, Jharkhand, and Madhya Pradesh by this time would still be 28.1, 31.4, and 31.7 years respectively.

The MoHFW study highlights the way population pyramids for male and female population change at five-year intervals. States which have a bulge in the middle age groups by 2036 would contribute relatively more to India’s WAP. States which have a noticeably narrow base are characterized by lower young dependency. States which have a relatively narrow top show a comparatively lower old dependency. The overall age profile can be divided into four broad groups reflecting the share of (a) population below 15 years of age (D1), (b) working age persons aged 15 to 39 years (W1), (c) working age persons aged 40 to 64 years (W2) and (d) population aged 65 years and above (D2). The economic features of differential shares of these broad age groups have distinct policy messages. For example, a state with a low D1 and D2 would be in a position to contribute to India’s saving rate relatively more than other states, since its total dependency ratio is less and the share of WAP is more. Such states include Telangana, Andhra Pradesh, Haryana, Punjab and West Bengal.

Chart 1 shows the population pyramids for Bihar and Kerala. In Bihar, a typical age pyramid of a wider base which progressively narrows down is indicated. This implies that the share of young dependents is relatively high, followed by the share of working age persons. The lowest shares are for old age dependents. In contrast, in Kerala, almost equal shares are indicated for different age groups, resulting in the age pyramid of a cylindrical shape. Kerala is also an interesting case as the share of its female population also shows higher width for higher age groups as compared to those of its male population.

Differentiated urbanization patterns

A related trend where large inter-state differences are becoming noticeable pertains to the rate of urbanization across states. Table 2 shows the current and projected urbanization profiles for states in India. 

There is one group of states where the extent of urbanization by 2036 would be comparable to developed countries. This group includes Kerala, with a projected urbanization rate of 96.4%, followed by Goa, Sikkim, and Nagaland. At the same time, some of the currently less developed states are also projected to remain low on the urbanization scale. These states include Bihar, Himachal Pradesh and Assam, where the urbanization rate would be less than 20%¹.