Abstract
A window of opportunity for fast economic growth is created by sustained fertility decline. However, its realization depends upon the quality (education and skills) of the labor force and economic policies. Fertility decline from about 6 to 2.4 births between the 1960s and 2011 in India has raised the prospects of a demographic dividend, although the timing and the pace of fertility decline have not been uniform among the major states. Consequently, the potential for reaping the benefits of a demographic dividend also differs among states. This chapter traces the common link between policies that contribute to fertility transition and create the right kind of environment for reaping the benefit of a demographic dividend. The data used for major states in India suggest this link to be the early investment in social development (education and health). For example, southern states made earlier investments in social development and experienced fertility transition early. They now have a better-educated labor force and hence are reaping the benefit of a demographic dividend by transforming the window of opportunity into faster economic growth. By contrast, northern states did not invest adequately in social development early and are now lagging behind in both fertility transition and the quality of the labor force. They are not ready to reap the benefits of a demographic dividend. These state-level differences have implications for national-level trends.
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Notes
- 1.
Fertility data are available from Sample Registration System (SRS) and three rounds of National Family Health Surveys (NFHS). SRS, a dual record system, was initiated in 1964–1965 on a pilot basis and became fully operational in 1969–1970. It provides annual estimates of vital rates at the national and state levels (RGI2009,2013). The fertility estimates from NFHS are based on the retrospective data on birth dates of children born during 3 years prior to the survey (IIIPS1995,2000,2007). We have used TFR estimates from SRS for the period 1990 onwards because the accuracy of the estimates has improved overtime to the extent that estimates for 1990 onward can be used without further adjustment (Bhat1998a). Moreover, NFHS estimates are affected by recall lapse whereas SRS estimates are not. SRS estimates of TFRs are slightly higher than those based on NFHS (0.3 for 1991, 0.5 for 1997, and 0.2 for 2004).
- 2.
The SRS data indicate that the percent of adult population may have increased to about 63 % in 2012 (RGI2013). Similar data from 2011 census are not yet available.
- 3.
Similar regional differences between northern and southern states also exist in contraceptive use (Jain and Jain2012).
- 4.
Bihar includes Jharkhand, Madhya Pradesh includes Chhattisgarh, and Uttar Pradesh includes Uttaranchal.
- 5.
TFR in 1971 represent the fertility level just after the reorganization of the family planning program in 1966; 1991 represent the period before the elimination of the targets, 1997 just after the abolition of the targets, 2004 represent the levels corresponding to the NFHS III, and 2011 represents the current level.
- 6.
Female education is measured by percent of females 15–19 years old with at least primary level education.
- 7.
Availability is measured by the percent of rural population living in villages with a government health facility (sub-centre, primary health centre, community health centre or referral hospital, government hospital, and government dispensary within the village).
- 8.
Poverty is measured by the percent of rural households with low standard of living, which is based on source of drinking water, type of housing material, type of toilet facility, source of lighting, source of cooking material, and ownership of consumer durables (IIPS2005).
- 9.
We recognize the limitation on the analysis placed by the small number of units included.
- 10.
The SRS data show that the proportion of the adult population in 2012 has increased to 56 % in Bihar and 60 % in Uttar Pradesh (RGI2013) because fertility has also started to decline in these northern states. The data from 2011 census need to confirm these changes in the age distributions.
- 11.
In addition to the potential saving in government resources, fertility decline may also stimulate higher savings at the household level because everything being equal smaller families will require fewer resources for raising children including expenditure on food, clothing, education, and health. Parents could use this saving to improve the education of their children and also save some resources for the future. In this fashion, fertility decline could also add to capital accumulation at the national level. Prior demographic analyses focused on this potential benefit of fertility decline. However, such savings are possible only in places with almost universal education and low infant and child mortality, i.e. without any backlog in these two sectors. This is not the case in the northern states.
- 12.
Satia and Jejeebhoy (1991) also noted that northern states were lagging behind the rest of India in similar indicators. Bose (1985) identified northern states as most backward in the country and deserving special attention. He also coined a term – BIMARU – literally meaning sick to collectively refer to these states. Chhattisgarh, Jharkhand, and Uttaranchal were also part of these four states.
- 13.
MDG 2: Achieve universal primary education; MDG 4: Reduce child mortality.
- 14.
Another alternative is that the fertility decline in the absence of such investment could stall in these states, which would imply a higher rate of population growth and larger population. Even if fertility declines in the absence of such investment, these states will not be able to realize the demographic dividend because the people entering the labor force will lack the education and skills to be fully productive.
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Jain, A.K. (2016). The Common Link Between Policies Conducive to Both the Demographic Dividend and Fertility Transition. In: Pace, R., Ham-Chande, R. (eds) Demographic Dividends: Emerging Challenges and Policy Implications. Demographic Transformation and Socio-Economic Development, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-32709-9_1
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