Regional Fertility Differences in India

Part of the The Springer Series on Demographic Methods and Population Analysis book series (PSDE, volume 51)


While theoretical literature distinguishes between factors that affect individual preferences regarding fertility and their ability to achieve these preferences, empirical literature often tends to conflate the two by focusing on completed family size. This chapter uses unique longitudinal data for India to distinguish between factors that affect fertility preferences, and those that affect ability to implement these preferences. India, with its tremendous regional heterogeneity in socioeconomic conditions as well as service delivery systems, offers a unique laboratory for this analysis. The results show that while socioeconomic characteristics of individuals account for substantial proportion of regional differences in fertility preferences, they only account for a small proportion of regional differences in unintended births. This suggests that unobserved factors, potentially those associated with regional health systems, have a far greater role in explaining underlying differences in unintended births than in explaining fertility preferences.


  1. Agadjanian, V. (2005). Fraught with ambivalence: Reproductive intentions and contraceptive choices in a sub-Saharan fertility transition. Population Research and Policy Review, 24(6), 617–645.Google Scholar
  2. Austin, P. C., & Merlo, J. (2017). Intermediate and advanced topics in multilevel logistic regression analysis. Statistics in Medicine, 36(20), 3257–3277.Google Scholar
  3. Balk, D. (1994). Individual and community aspects of women’s status and fertility in rural Bangladesh. Population Studies, 48(1), 21–45.Google Scholar
  4. Bankole, A. (1995). Desired fertility and fertility behaviour among the Yoruba of Nigeria: A study of couple preferences and subsequent fertility. Population Studies, 49(2), 317–328.Google Scholar
  5. Barber, J. S., & Axinn, W. G. (2004). New ideas and fertility limitation: The role of mass media. Journal of Marriage and Family, 66(5), 1180–1200.Google Scholar
  6. Basu, A., & Sundar, R. (1988). The domestic servant as family planning innovator: An Indian case study. Studies in Family Planning, 19(5), 292–298.Google Scholar
  7. Bennett, W. L. (1975). The political mind and the political environment: An investigation of public opinion and political consciousness (pp. 4–25). Lexington: Lexington Books.Google Scholar
  8. Bernardi, L. (2003). Channels of social influence on reproduction. Population Research and Policy Review, 22(5–6), 427–555.Google Scholar
  9. Bernardi, L., von der Lippe, H., & Keim, S. (2005). Mapping social influence on fertility: a mix-method approach to data collection. Max Planck Institute for Demographic Research (Working Paper 2005–015).Google Scholar
  10. Bhushan, I., & Hill, K. (1996). The measurement and interpretation of desired fertility. WP 95–1. Papers on Population. Baltimore, MD: Hopkins Population Center.Google Scholar
  11. Bocquet-Appel, J. P., Rajan, I. S., Bacro, J. N., & Lajaunie, C. (2002). The onset of India’s fertility transition. European Journal of Population/Revue européenne de Démographie, 18(3), 211–232.Google Scholar
  12. Bongaarts, J. (1978). A framework for analyzing the proximate determinants of fertility. Population and Development Review, 4(1), 105–132.Google Scholar
  13. Bongaarts, J. (1990). The measurement of wanted fertility. Population and Development Review, 16(3), 487–506.Google Scholar
  14. Bongaarts, J. (1994). Population policy options in the developing world. Science, 263(5148), 771–776.Google Scholar
  15. Bongaarts, J. (2001). Fertility and reproductive preferences in post-transitional societies. Population and Development Review, 27, 260–281.Google Scholar
  16. Bongaarts, J. (2011). Can family planning programs reduce high desired family size in sub-Saharan Africa? International Perspectives on Sexual and Reproductive Health, 37(4), 209–216.Google Scholar
  17. Bongaarts, J., & Watkins, S. C. (1996). Social interactions and contemporary fertility transitions. Population and Development Review, 22(4), 639–682.Google Scholar
  18. Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical models: Applications and data analysis methods.Google Scholar
  19. Bühler, C., & Kohler, H. P. (2004). The influence of strong ties on the use of modern contraceptives in Kenya. Journal of Sociology, 33(1), 5–25.Google Scholar
  20. Bulatao, R. A. (1981). Values and disvalues of children in successive childbearing decisions. Demography, 18(1), 1–25.Google Scholar
  21. Bulatao, R. A., & Lee. R. D. (Eds.). (1983). Determinants of fertility in developing countries (2 vols). New York: National Academy Press.Google Scholar
  22. Chatterjee, S., & Kastor, A. (2018). To what extent do couples’pre-marital communications affect their post-marital fertility behaviour in india? Journal of Biosocial Science, 50(4), 435–450.Google Scholar
  23. Cleland, J., & Wilson, C. (1987). Demand theories of the fertility transition: An iconoclastic view. Population Studies, 41(1), 5–30.Google Scholar
  24. Committee on Population, & National Research Council. (1999). The role of diffusion processes in fertility change in developing countries. National Academies Press.Google Scholar
  25. Desai, S., & Dubey, A. (2011). Caste in 21st century India: Competing narratives. Economic and Political Weekly, 46, 40–49.Google Scholar
  26. Desai, S., & Wu, L. (2010). Structured inequalities—Factors associated with spatial disparities in maternity care in India. Margin: The Journal of Applied Economic Research, 4(3), 293–319.Google Scholar
  27. Desai, S., Dubey, A., Joshi, B. L., Sen, M., Shariff, A., & Vanneman, R. (2009). India human development survey: Design and data quality (IHDS Technical Paper, 1).Google Scholar
  28. Desai, S. B., Dubey, A., Joshi, B. L., Sen, M., Shariff, A., & Vanneman, R. (2010). Human development in India. New York: Oxford University.Google Scholar
  29. Dharmalingam, A., & Morgan, S. P. (2004). Pervasive Muslim-Hindu fertility differences in India. Demography, 41(3), 529–545.Google Scholar
  30. Dharmalingam, A., Rajan, S., & Morgan, S. P. (2014). The determinants of low fertility in India. Demography, 51(4), 1451–1475.Google Scholar
  31. Dommaraju, P., & Agadjanian, V. (2009). India’s North–South divide and theories of fertility change. Journal of Population Research, 26(3), 249.Google Scholar
  32. Drèze, J., & Sen, A. (2013). An uncertain glory: India and its contradictions. Princeton: Princeton University Press.Google Scholar
  33. Dyson, T., & Moore, M. (1983). On kinship structure, female autonomy, and demographic behavior in India. Population and Development Review, 9(1), 35–60.Google Scholar
  34. Easterlin, R. A. (1978). The economics and sociology of fertility: A synthesis. Center for Advanced Study in the Behavioral Sciences.Google Scholar
  35. Easterlin, R. A. (1983). Modernization and fertility: A critical essay. Determinants of fertility in developing countries, 2, 562–586.Google Scholar
  36. Easterlin, R. A., & Crimmins, E. M. (1985). The fertility revolution: A supply-demand analysis. Chicago: University of Chicago Press.Google Scholar
  37. Edin, K., & Kefalas, M. (2011). Promises I can keep: Why poor women put motherhood before marriage. Berkeley: Univ of California Press.Google Scholar
  38. England, P., Caudillo, M. L., Littlejohn, K., Bass, B. C., & Reed, J. (2016). Why do young, unmarried women who do not want to get pregnant contracept inconsistently? Mixed-method evidence for the role of efficacy. Socius, 2, 2378023116629464.Google Scholar
  39. Faria, V. E., & Potter, J. E. (1999). Television, telenovelas and fertility change in north-east Brazil. In R. Leete (Ed.), Dynamics of values in fertility change (pp. 252–274). New York: Oxford University Press.Google Scholar
  40. Freedman, R. (1997). Do family planning programs affect fertility preferences? A literature review. Studies in Family Planning, 28(1), 1–13.Google Scholar
  41. Gamson, W. A., & Modigliani, A. (1989). Media discourse and public opinion on nuclear power: A constructionist approach. American Journal of Sociology, 95(1), 1–37.Google Scholar
  42. Gamson, W. A., Croteau, D., Hoynes, W., & Sasson, T. (1992). Media images and the social construction of reality. Annual Review of Sociology, 18(1), 373–393.Google Scholar
  43. Goldstein, H. (1995). Hierarchical data modeling in the social sciences. Journal of Educational and Behavioral Statistics, 20(2), 201–204.Google Scholar
  44. Guilmoto, C. Z., & Rajan, S. I. (2001). Spatial patterns of fertility transition in Indian districts. Population and Development Review, 27(4), 713–738.Google Scholar
  45. Guilmoto, C. Z., & Rajan, S. I. (2013). Fertility at the district level in India: Lessons from the 2011 census. Economic and Political Weekly, 48, 59–70.Google Scholar
  46. Hayford, S. R., & Agadjanian, V. (2012). From desires to behavior: Moderating factors in a fertility transition. Demographic Research, 26, 511.Google Scholar
  47. Hindin, M. J. (2000). Women’s autonomy, women’s status and fertility-related behavior in Zimbabwe. Population Research and Policy Review, 19(3), 255–282.Google Scholar
  48. Hirschman, C. (1994). Why fertility changes. Annual Review of Sociology, 20(1), 203–233.Google Scholar
  49. Hornik, R., & McAnany, E. (2001). Mass media and fertility change. Diffusion Processes and Fertility Transition: Selected perspectives, 208, 239.Google Scholar
  50. Islam, M. M., & Bairagi, R. (2003). Fertility intentions and subsequent behaviour in Matlab. Do fertility intentions matter? Journal of Biosocial Science, 35, 615–619.Google Scholar
  51. Jejeebhoy, S. J. (1995). Women’s education, autonomy, and reproductive behaviour: Experience from developing countries. OUP Catalogue.Google Scholar
  52. Johnson-Hanks, J. (2007). Natural intentions: fertility decline in the African Demographic and Health Surveys. American Journal of Sociology, 112(4), 1008–1043.Google Scholar
  53. Kishor, S., & Subaiya, L. (2008). Understanding women’s empowerment: a comparative analysis of Demographic and Health Surveys (DHS) data (No. 20). Calverton: Macro International.Google Scholar
  54. Kodzi, I. A., Johnson, D. R., & Casterline, J. B. (2010). Examining the predictive value of fertility preferences among Ghanaian women. Demographic Research, 22, 965.Google Scholar
  55. Koenig, M. A., Acharya, R., Singh, S., & Roy, T. K. (2006). Do current measurement approaches underestimate levels of unwanted childbearing? Evidence from rural India. Population Studies, 60(3), 243–256.Google Scholar
  56. Kohler, H.-P. (2001). Fertility and Social Interactions: An Economic Perspective. Oxford: Oxford University Press.Google Scholar
  57. Kohler, H.-P., Behrman, J. R., & Watkins, S. C. (2001). The Structure of Social Networks and Fertility Decisions: Evidence from South Nyanza District Kenya. Demography, 38, 43–58.Google Scholar
  58. Kulkarni, P. M., & Alagarajan, M. (2005). Population growth, fertility, and religion in India. Economic and Political Weekly, 40(5), 403–410.Google Scholar
  59. Lightbourne, R. E. (1985). Individual preferences and fertility behaviour. In Reproductive change in developing countries: Insights from the World Fertility Survey (Vol. 165, p. 198).Google Scholar
  60. Malhotra, A., Vanneman, R., & Kishor, S. (1995). Fertility, dimensions of patriarchy, and development in India. Population and Development Review, 21, 281–305.Google Scholar
  61. Mead, G. H. (1967). [Works]; Works of George Herbert Mead. 1. Mind, self, and society: from the standpoint of a social behaviorist. Chicago/London: University of Chicago Press.Google Scholar
  62. Miller, B. D. (1981). The Endangered Sex: Neglect of Female Children in Rural India. Ithaca: Cornell University Press.Google Scholar
  63. Montgomery, M. R., & Casterline, J. B. (1993). The diffusion of fertility control in Taiwan: Evidence from pooled cross-section time-series models. Population Studies, 47(3), 457–479.Google Scholar
  64. Montgomery, M. R., & Casterline, J. B. (1996). Social learning, social influence, and new models of fertility. Population and Development Review, 22, 151–175.Google Scholar
  65. Moreau, C., Bohet, A., Hassoun, D., Teboul, M., Bajos, N., & FECOND Working Group. (2013). Trends and determinants of use of long-acting reversible contraception use among young women in France: results from three national surveys conducted between 2000 and 2010. Fertility and Sterility, 100(2), 451–458.Google Scholar
  66. Murthi, M., Guio, A. C., & Dreze, J. (1995). Mortality, fertility, and gender bias in India: A district-level analysis. Population and Development Review, 21(4), 745–782.Google Scholar
  67. Population Bulltein. (2015). Haub, C. and Sharma, O.P. Vol. 70, No.1. Population Reference Bureau, Washington, DC.Google Scholar
  68. PRB (2011). Haub, C., Gribble, J., & Jacobsen, L. World Population Data Sheet 2011. Population Reference Bureau, Washington, DC.Google Scholar
  69. Pritchett, L. H. (1994). Desired fertility and the impact of population policies. Population and Development Review, 20, 1–55.Google Scholar
  70. Registrar General of India (RGI). (2017). Sample Registration System statistical report 2017. Office of the Registrar General of India, New Delhi.Google Scholar
  71. Roy, T. K., Sinha, R. K., Koenig, M., Mohanty, S. K., & Patel, S. K. (2008). Consistency and predictive ability of fertility preference indicators: Longitudinal evidence from rural India. International Family Planning Perspectives, 34(3), 138–145.Google Scholar
  72. Ryder, N. B. (1973). Contraceptive failure in the United States. Family Planning Perspectives, 5(3), 133–142.Google Scholar
  73. Sabharwal, N. S., Sharma, S., Diwakar, D., & Naik, A. K. (2014). Caste discrimination as a factor in poor access to public health service system: A case study of Janani Suraksha Yojana Scheme. Journal of Social Inclusion Studies, 1, 148–168.Google Scholar
  74. Schoen, R., Astone, N. M., Kim, Y. J., Nathanson, C. A., & Fields, J. M. (1999). Do fertility intentions affect fertility behavior? Journal of Marriage and the Family, 61(3), 790–799.Google Scholar
  75. Snijders, T., & Bosker, R. (2000). Discrete dependent variables. Multilevel analysis: an introduction to basic and advanced multilevel modelling. London: Sage.Google Scholar
  76. Speizer, I. S., Calhoun, L. M., Hoke, T., & Sengupta, R. (2013). Measurement of unmet need for family planning: longitudinal analysis of the impact of fertility desires on subsequent childbearing behaviors among urban women from Uttar Pradesh, India. Contraception, 88(4), 553–560.Google Scholar
  77. StataCorp, L. P. (2013). Stata multilevel mixed-effects reference manual. College Station: StataCorp LP.Google Scholar
  78. Thornton, A., Dorius, S. F., & Swindle, J. (2015). ‘Developmental Idealism’, The Cultural Foundations of World Development Programs. Sociology of Development, 1(2), 277–320.Google Scholar
  79. United Nations, Department of Economic and Social Affairs, Population Division. (2019). World Population Prospects 2019: Highlights.Google Scholar
  80. Upadhyay, U. D., & Karasek, D. (2012). Women’s empowerment and ideal family size: an examination of DHS empowerment measures in Sub-Saharan Africa. International Perspectives on Sexual and Reproductive Health, 38(2), 78–89.Google Scholar
  81. Upadhyay, U. D., Gipson, J. D., Withers, M., Lewis, S., Ciaraldi, E. J., Fraser, A., et al. (2014). Women’s empowerment and fertility: A review of the literature. Social Science & Medicine, 115, 111–120.Google Scholar
  82. Vlassoff, C. (2012). Desire for sons and subsequent fertility in rural India. A 20-year longitudinal study. Journal of Biosocial Science, 44(03), 345–356.Google Scholar
  83. Watkins, S. C.. (1992). More lessons from the past: Women’s informal networks and fertility decline, a research agenda. Paper presented at the seminar on Fertility in Sub-Saharan Africa, Harare, November 1991, revised January 1992.Google Scholar
  84. Watkins, S. C., Naomi Rutenberg, and David Wilkinson. (1995). “Orderly theories, disorderly women.” Paper presented at the John Caldwell Seminar on “The Continuing Demographic Tran- sition.” Canberra, Australia, 14–17 August.Google Scholar
  85. Westoff, C. F. (1972). The modernization of US contraceptive practice. Family Planning Perspectives, 4(3), 9.Google Scholar
  86. Westoff, C. F. (1991). Reproductive preferences: a comparative view. In Demographic and health surveys comparative studies (No. 3). Institute for Resource Development/Macro Systems.Google Scholar
  87. Westoff, C. F., & Bankole, A. (1996). The potential demographic significance of unmet need. International Family Planning Perspectives, 22(1), 16–20.Google Scholar
  88. World Health Organization (WHO). (2014). WHO recommendations on postnatal care of the mother and newborn. World Health Organization.Google Scholar
  89. Yoo, S. H., Guzzo, K. B., & Hayford, S. R. (2014). Understanding the complexity of ambivalence toward pregnancy: Does it predict inconsistent use of contraception? Biodemography and Social Biology, 60(1), 49–66.Google Scholar

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Authors and Affiliations

  1. 1.Department of SociologyUniversity of Maryland, College ParkCollege ParkUSA
  2. 2.National Council of Applied Economic ResearchNew DelhiIndia

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