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Measuring low fertility: rethinking demographic methods

  • José A. Ortega
  • Hans-Peter Kohler

    (Max Planck Institute for Demographic Research, Rostock, Germany)

In a low fertility context demographic characteristics like the parity distribution of the population and the timing of births can lead to substantial changes in period fertility. In this article we review the literature on the analysis of fertility by parity and on tempo distortions. Both approaches can be combined through the use of the parity and age fertility model as recently proposed by Kohler and Ortega (2002a). We show applications of the approach for the analysis of both period and cohort fertility. For the analysis of period fertility a new measure is proposed, the Period Fertility Index, which is free from tempo distortions and from the influence of the population parity distribution. The Period Fertility Index is connected to the TFR by two ratios: the mean tempo effect, which generalizes previous work by Bongaarts and Feeney (1998), and the parity composition effect. Besides the period fertility index, all standard life table functions can be defined as synthetic cohort measures including mean ages at birth, interbirth intervals, parity progression rates or the stable parity distribution. From the perspective of cohort fertility it is possible to determine future childbearing intensities for conditional postponement scenarios. These can then be used for cohort completion or fertility forecasting. Examples of the different measures and techniques are given based on recent Swedish data.

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Paper provided by Max Planck Institute for Demographic Research, Rostock, Germany in its series MPIDR Working Papers with number WP-2002-001.

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Length: 35 pages
Date of creation: Jan 2002
Date of revision:
Handle: RePEc:dem:wpaper:wp-2002-001
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  1. repec:cai:popine:popu_p2001_56n3_0420 is not listed on IDEAS
  2. Tomas Frejka & Gérard Calot, 2001. "Cohort Reproductive Patterns in Low-Fertility Countries," Population and Development Review, The Population Council, Inc., vol. 27(1), pages 103-132.
  3. Tuljapurkar, Shripad & Boe, Carl, 1999. "Validation, probability-weighted priors, and information in stochastic forecasts," International Journal of Forecasting, Elsevier, vol. 15(3), pages 259-271, July.
  4. Heckman, James J & Walker, James R, 1990. "The Relationship between Wages and Income and the Timing and Spacing of Births: Evidence from Swedish Longitudinal Data," Econometrica, Econometric Society, vol. 58(6), pages 1411-41, November.
  5. Lee, Ronald D., 1993. "Modeling and forecasting the time series of US fertility: Age distribution, range, and ultimate level," International Journal of Forecasting, Elsevier, vol. 9(2), pages 187-202, August.
  6. Evert Imhoff & Nico Keilman, 2000. "On the Quantum and Tempo of Fertility: Comment," Population and Development Review, The Population Council, Inc., vol. 26(3), pages 549-553.
  7. De Cooman, Eric & Ermisch, John F & Joshi, Heather, 1985. "The Next Birth and the Labour Market: A Dynamic Model of Births in England and Wales," CEPR Discussion Papers 37, C.E.P.R. Discussion Papers.
  8. Evert van Imhoff, 2001. "On the impossibility of inferring cohort fertility measures from period fertility measures," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 5(2), pages 23-64, September.
  9. Ron Lesthaeghe & Paul Willems, 1999. "Is Low Fertility a Temporary Phenomenon in the European Union?," Population and Development Review, The Population Council, Inc., vol. 25(2), pages 211-228.
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