From birth expectations to birth forecasts: a partial-adjustment approach

Area of Science:

• Demography
• Reproductive Health
• Social Statistics

Background:

• Women's subjective expectations of future fertility often diverge from actual childbearing outcomes.
• This systematic deviation limits the direct use of fertility expectations for accurate demographic forecasting.
• Understanding and correcting for this expectation-realization gap is crucial for reproductive health and social policy.

Purpose of the Study:

• To develop and evaluate a novel partial-adjustment approach for forecasting future fertility based on women's expectations.
• To assess the sensitivity of the forecasting model to different underlying assumptions.
• To provide a more reliable method for predicting fertility trends.

Main Methods:

• Utilized a partial-adjustment model to reconcile reported fertility expectations with observed fertility outcomes.
• Conducted sensitivity analyses to determine the robustness of the forecasting approach under varying assumptions.
• Employed empirical data from the Netherlands for model validation.

Main Results:

• The partial-adjustment method demonstrated a promising improvement in forecasting accuracy compared to direct use of expectations.
• Sensitivity analyses indicated that the model's performance is reasonably robust across different assumption sets.
• Empirical findings for the Netherlands suggest the approach's practical applicability.

Conclusions:

• A partial-adjustment approach offers a viable method to correct for systematic deviations in women's fertility expectations.
• This refined forecasting technique can enhance the reliability of demographic projections in reproductive health research.
• The study provides a valuable tool for policymakers and researchers analyzing fertility trends.