India’s Total Fertility Rate (TFR)

Syllabus: Population and associated issues

Context

  • UNFPA’s State of World Population 2025 Report shows India’s Total Fertility Rate (TFR) has fallen to 1.9, i.e., below replacement level (2.1).

Perceived Meaning of TFR

  • Commonly viewed as the average number of children a woman bears by the end of her reproductive age.
  • In reality, it’s a statistical construct, estimating births a woman would have if she experienced current age-specific fertility rates (ASFRs) throughout life (ages 15–49 years).

Limitations of TFR Calculation

  • Synthetic Cohort Assumption Problem
    • Future fertility preferences evolve with education, lifestyle, and economy, unlike older cohorts.
    • Thus, synthetic assumption often fails in societies under rapid change (like India).
  • Tempo Effect
    • Definition: When women delay childbirth, TFR temporarily falls even if total births per woman remain unchanged.
    • Impact: Postponed births not reflected in current ASFRs → TFR artificially low.
    • Result: Misleading picture — fertility appears to fall faster than it actually does.
    • When most young women delay childbirth, future TFRs appear higher, creating statistical fluctuation.

Relevance in India

  • India in transition:
    • Higher female literacy, urban aspirations, career goals → delay in childbirth, not rejection of motherhood.
  • Hence, India’s decline in TFR may reflect timing shifts, not permanent fertility reduction.

Policy Implications

  • Historical Evidence
    • Sub-replacement fertility has not hindered economic growth (examples: Europe, U.S., East Asia).
  • India’s Challenges
    • Demographic dividend underutilized due to youth unemployment and low job creation.
    • Future automation and AI likely to reduce labour demand, making “population increase” less beneficial.

Conclusion

  • India’s reported TFR of 1.9 may not reflect real fertility patterns due to tempo effects, synthetic assumptions, and data exclusions. Policy must not rely solely on TFR numbers to justify pro-natalist measures. There is a need to incorporate longitudinal fertility data, age-specific patterns, and socioeconomic transitions before drawing conclusions.

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