Is education the best contraceptive? Using the multistate human capital projection model, our analysis shows that the projected changes in India population vary depending on investments in education and helping women reduce unwanted fertility rates, that investments in both education and helping women in each education category—but particularly less educated women—meet their wanted fertility will have the largest impacts on India’s population projections, and that the impact from investment in reducing unwanted fertility will be much more immediate and significant than only investments in education. Our analysis also reveals that an increasing education transition rate in India will not only help to achieve a population age structure that is favorable for economic growth, but also result in a larger share of skilled labor force that help to achieve higher economic growth rate. More importantly, investment in girls’ education and achieving gender equality in education will be the most effective measure to increase India’s population education level and improve its overall values of human capital.
Education confers a range of benefits to individuals and societies. Hannum and Buchman [
Female education, particularly completion of primary school and into secondary school, has emerged as strongly related to lowered fertility [
And yet, even educated women need to use a means of fertility control to avoid unintended pregnancies. Using data from 26 DHS, Martin [
Drèze and Murthi [
Axinn and Barber [
Using data from India, this paper seeks to answer the questions: what could female education contribute to future changes in the population? What will achieving wanted fertility contribute? What will combined efforts to promote female education and achieve wanted fertility contribute?
Analysis for this paper is conducted using a multistate demographic method with a focus on education, which is developed at International Institute for Applied Systems Analysis (IIASA), in collaboration with the Vienna Institute of Demographic Research [
To prepare the input data for the model simulation, we derive baseline population by single year of age, sex, and education attainment using the data from the India 2001 census. The age-specific fertility rates for population by education categories are also based on the same data source. Figure
Age-specific fertility rate of Indian women by education.
As the data from the 2001 Census on mortality is not distinguished by education levels, we derive age-specific survival ratio by education based on the findings from research in other countries that the life expectancy at age 15 of those with no education is one year smaller than those with primary education; the differences between primary education and secondary and between secondary and tertiary are all two years each, resulting in a five-year difference between the highest and lowest categories [
To derive the age-specific education transition rates, we use the proportion of population by education attainment by sex and age in the 2001 Census, assuming that the increase in the proportion of each education level represents the upward transition across ages, and calculate the increase of education attainment and the conditional transition probability to achieve this increase. Based on the derived age-specific educational transition rate, the overall conditional education transition rates of the male population are 0.85 for transferring from no education to primary education, 0.63 for primary education to secondary education, and 0.26 for secondary education to tertiary education. The corresponding figures for the female population are 0.79, 0.54, and 0.24, respectively.
We construct six scenarios of future changes of the Indian population in order to analyze: (1) the impacts of investment in education on overall population growth; and (2) the potential impacts of investment in reducing unwanted fertility relative to the impact of investment in education, on population growth. The scenarios described below include (1) Constant, (2) Global Education Trend, (3) Fast Track Educational Attainment, (4) Reduce Unwanted Fertility, (5) Reduce Unwanted Fertility/Global Education Trend, and (6) Reduce Unwanted Fertility/Fast Track Educational Attainment.
First, as the baseline
Second, using the same values for fertility and mortality by educational category as in the Constant Scenario, we assume a moderate increase of the educational transition rate which is embedded in the
Third, we assume a
In the fourth
In our analysis, the assumptions about the changes in fertility are based on the proportion of the wanted fertility rate relative to the observed total fertility rate derived from India’s 1992-93 and 2005-06 National Family Health Surveys (
Wanted fertility rate of Indian women of childbearing ages, from national family health surveys.
2005-2006 NFHS | 1992-1993 NFHS | |||||
---|---|---|---|---|---|---|
Wanted TFR | TFR | Ratio | Wanted TFR | TFR | Ratio | |
(1) | (2) | (1)/(2) | (1) | (2) | (1)/(2) | |
No education | 2.4 | 3.6 | 0.667 | 3.2 | 4 | 0.800 |
Primary | 1.9 | 2.6 | 0.731 | 2.3 | 3 | 0.767 |
Secondary or higher | 1.7 | 2.1 | 0.810 | 1.9 | 2.4 | 0.792 |
Missing | 1.1 | 1.1 | 1.000 | 3.1 | 4.1 | 0.756 |
|
||||||
Total | 1.9 | 2.7 | 0.704 | 2.6 | 3.4 | 0.765 |
In the previous scenarios, mortality of the population by education is assumed to remain the same over the whole projection period in order to test the net impacts of education and fertility change (family planning services) on population growth and labor force (human capital) changes. In the fifth scenario, the
Finally, the sixth scenario, the
While India’s population will continue to grow under all scenarios, the population growth rate will be the highest under the Constant Scenario in which total population size will reach about 1.8 billion by the middle of the century (Figure
Indian Population Change. Key: Constant = Constant Scenario; GET = Global Education Trend Scenario; FT = Fast Track Educational Attainment Scenario; RTFR = Reduce Unwanted Fertility Scenario; RTFR-GET = Reduce Unwanted Fertility/Global Education Trend Scenario; RTFR-FT = Reduce Unwanted Fertility/Fast Track Educational Attainment Scenario.
Projection results show that when the education transition rate increases—under the Global Education Trend (GET) and Fast Track Educational Attainment (FT) Scenarios, India’s population growth rate declines. This is mainly due to the fact that having more educated women in the population drives down the national total fertility rate: under GET and FT Scenarios, the TFR would decline to 2.2 and 1.97 by year 2051, which is 0.5 and 0.7 lower than that under the Constant Scenario. Although increases in education will also reduce mortality as people with higher levels of education have higher life expectancy, the multiplicative effect of declining fertility over generations will result in a much more significant reduction in total population growth. Total population size will be about 100 million and 160 million smaller, respectively, than that under the Constant Scenario. Therefore, investment in education, particularly girls’ education, does contribute to slower population growth, even though slower population growth is not the goal of investing in girls’ education.
We also test how reducing unwanted fertility will affect population growth in India through the RTFR Scenario. Other factors being equal, if Indian women in each education category gradually reduce fertility to reach the level of their wanted fertility of today by 2021, the result will be overall declines in the total fertility rate from 3.05 to under replacement level by 2021, and further to 1.97 by 2031, due to the aging out of less educated women from the reproductive ages. Under this scenario, India’s population would be 50 million less by year 2021 and 260 million less by year 2051, relative to that under the Constant Scenario. Comparing the effects on population growth under the GET, FT, and RTFR scenarios, the impact from investment in helping women reach their desired fertility, including through increasing access to family planning program and reproductive health services, will be much more immediate and significant than only investments in education. This is mainly because investment in education takes a number of years to have an effect on fertility reduction when more educated girls gradually reach childbearing age. Given the nature of reproductivity of fertility over generations, the impacts of postponing reduction in fertility by investment in education will be amplified overtime. Therefore strengthening family planning and reproductive health services, particularly for less educated women who are less likely than more educated women to be using contraceptive at rates to achieve their desired fertility, and promoting contraceptive use among this group are important compliments to expanding education for girls.
Another reason that population growth under GET and FT scenarios is higher than under the RTFR scenario is because increasing the education transition rate reduces the mortality rate and, as described above, life expectancy is higher among more educated people. Although no changes in life expectancy of the population by education are assumed for future years in all three scenarios, increasing the education transition rate increases the proportion of the population with higher education levels and drives the life expectancy of the overall population by 0.3 and 0.5 years longer by 2051 under the GET and FT Scenarios than under RTFR Scenarios.
Moreover, the impact of an increasing education transition rate on life expectancy of the overall population is slightly underestimated. The GET and FT Scenarios only consider the disparities in life expectancy among people of various education levels, due to improving socioeconomic status, better knowledge about medicine and health, adaption of healthier life styles and sanitation habits, safer working environment, and so forth. However, indirect impacts of higher levels of education on life expectancy, such as better knowledge to raise healthier children and higher motivation to improve community sanitation and health facilities, are not considered. However, there is limited research that could provide evidence on how much improving education reduces mortality rates, making it difficult to build into scenarios of changes in life expectancies.
The impact of the changes in education and fertility on population growth through deaths is complicated. While an increase in education increases life expectancy of the overall population and reduces mortality as descried above, declining fertility through reducing the unwanted fertility or changing the composition of the population by education category will change the population age structure and result in population aging. A more mature or aged population will increase population death rates due to a larger proportion of elderly population, even though mortality rates remain the same or even increase. For instance, the population death rate by year 2051 is 14.4 per thousand under the RTFR Scenario, significantly higher than under the Constant Scenario (12.5‰), although the life expectancy is the same. The population death rates by year 2051 under GET and FT Scenarios are 12.7 per thousand and 12.9 per thousand, respectively, also higher than under the Constant Scenario, even though the life expectancies under FT and GET Scenarios are 0.3 and 0.5 year longer.
As the population of India increases, the total number and the proportion of the population in the labor force will also increase in the coming decades under all scenarios (Figure
Changes in proportion of labor force population.
However, the proportion of the population of labor force age is quite different under the various scenarios. In general, the lower the total fertility rate, the higher the proportion of the population of labor force age. Under the Constant Scenario, the proportion of the population of labor force age will increase from 50 percent of the total population of India in 2001 to about 57 percent by 2021, where it will stay until it slightly declines after 2041. Under the increasing education transition rate in the GET and FT Scenarios, the proportion of the population of labor force age will be virtually the same as under the Constant Scenario until 2021 and will increase to reach 59 percent and 61 percent, respectively, by the year 2051.
The increase in the proportion of the population of labor force age is much more substantial under the scenarios of reducing unwanted fertility. Through reducing fertility to the level of today’s wanted fertility by the year 2021, the proportion of population in the labor force under the RTFR Scenario will quickly increase to above 59 percent by the year 2021 and will hit a peak of about 63 percent by the year 2041. This proportion will be nearly the same under the Reduce Unwanted Fertility/Global Education Transition Scenario, although it has higher life expectancy and education transition rate. This again shows the importance of fertility levels on not only total population size but also the population age composition. The Reduce Unwanted Fertility/Fast Track Educational Attainment Scenario will also significantly drive the proportion of population in the labor force up in future years.
While an increasing proportion of the population of labor force age offers the potential of the demographic dividend, according to experience in other regions of the world, such as countries in East Asia, it will be important for the labor force to be educated. According to the 2001 Census, more than 41 percent of the Indian labor force population was illiterate (not shown in a table). Under the Constant Scenario, this proportion will gradually decline to about 26 percent by 2021, and 18 percent by 2051, as older, illiterate generations leave the labor force. The proportion of the labor force with tertiary education will increase only slightly from 13.5 percent in 2001 to 14 percent by 2021, but will decrease to 12 by 2051. In particular, the education level of the female labor force is extremely low: in 2001, about 54 percent of the female population of labor force age was illiterate and only 9 percent had tertiary education. Under the Constant Scenario, the situation will not improve very much. If India follows the Global Education Trend, the proportion of the population of labor force age with secondary or tertiary education, who account for the majority of the skilled labor force will increase from 34 percent in year 2001 to 69 percent by 2051 (Figure
Changes in proportion of labor force population with secondary or higher education.
The projection results also show that, although the proportion of the population of labor force age increases very fast by achieving replacement fertility rate under RTFR Scenario by 2021, without increasing investment in education, the percentage of labor force population with secondary or tertiary education levels remains lower than 50 percent in the future decades, which will affect India’s ability to benefit from the demographic dividend.
The projection result under the RTFR-GET Scenario offers a possible future. Under this scenario, the proportion of the population of labor force age with secondary and tertiary education will increase from 34 percent in 2001 to 45 percent in 2021 and 67 percent in 2051. These projections are slightly lower than those under the GET Scenario because of higher life expectancy in that scenario that retains more less educated people in the population of labor force age from the older generation. The RTFR-GET and the RTFR-FT Scenarios again produce significantly higher proportions of the population of labor force age with secondary and tertiary education.
Population pyramids provide a convenient tool to display and summarize the changes in population size and composition. Here we present a set of population pyramids in which the changes in total population size, age, sex, and educational attainment under two of the scenarios (Figures
Changes in Indian population composition under Constant Scenario.
Changes in Indian population composition under RTFR-GET scenario.
Changes in Indian population composition under RTFR-FT Scenario.
Using the multistate demographic projection model and based on the data from India’s 2001 Population Census, our analysis shows that India’s future population change will vary depending on investments in education and helping women reduce unwanted fertility rates.
Investments in both education and helping women in each education category—but particularly less educated women—meet their wanted fertility will have the largest impacts on India’s population projections. Comparing results from the various scenarios, the impact from investment in meeting wanted fertility, including through renewed focus on improving access to family planning program and reproductive health services and removing other barriers to contraceptive use, will be much more immediate and significant than only investments in education. Holding other factors constant, expanding programs to help Indian women in each education category gradually achieve their wanted fertility rate of today by the year 2021 will result in the overall total fertility rate declining from 3.05 to under replacement level (defined as 2.1 children per couple) by year 2021, and further to 1.97 by year 2031. Under this scenario, India’s population will be 260 million less by year 2051 than it would be if current levels of educational attainment and fertility rates remain constant in India. Reducing unwanted fertility and improving education will also affect population composition. Fertility reduction due to family planning services and education investment will change population age structure, increasing the proportion of population of labor force age and resulting in a demographic windows opportunity in the next decades, which provides India with the potential for rapid economic growth and even economic takeoff. While both expanding family planning services and education investment will contribute to a larger share of the population of labor force age, the more rapid and immediate fertility reduction due to family planning expansion will generate more significant impacts on the changes in population age structure and the effects of demographic dividend.
Moreover, a larger share of the population of labor force age alone does not necessarily guarantee an economic miracle. According to the findings of existing researches, it is the larger and more skilled labor force providing increasing human capital that entails rapid economic growth. Our analysis reveals that an increasing education transition rate in India will not only help to achieve a population age structure that is favorable for economic growth, but will also result in a larger share of skilled labor force that help to achieve higher economic growth rate. More importantly, investment in girls’ education and achieving gender equality in education will be the most effective measure to increase India’s population education level and improve its overall values of human capital.
Is education the best contraceptive? This analysis shows that increasing levels of education among girls is critical and so is increasing access to the means to achieve desired family size, so that women can both gain education and meet their fertility desires. Freedman [
The authors declare that there is no conflict of interests regarding the publication of this paper.