Stochastic Forecasting of Regional Age-Specific Fertility Rates: An Outlook for German NUTS-3 Regions

Author:

Vanella Patrizio123ORCID,Hassenstein Max J.1ORCID

Affiliation:

1. Demography Cluster, Department of Health Monitoring & Biometrics, aQua Institute, 37073 Göttingen, Germany

2. Chair of Empirical Methods in Social Science and Demography, University of Rostock, 18051 Rostock, Germany

3. Working Group of Demographic Methods, German Demographic Society (DGD), 37073 Göttingen, Germany

Abstract

Regional fertility forecasts are important for long-term planning in a variety of fields that include future birth numbers in their forecast, such as school or kindergarten planning. They are one of the major components of regional population forecasts as well. Therefore, it is important to construct reliable forecasts that are based on sophisticated models that cover the high complexity of future regional fertility. We suggest a novel forecast model for forecasting regional age-specific fertility rates that covers long-term trends by time series models, demographic and regional correlations by principal component analysis, and future uncertainty by Monte Carlo simulation. The model is applied to all German NUTS-3 regions (districts/Kreise) simultaneously, where we forecast all regional age-specific fertility rates through the period of 2022–2045. The results from the simulations are presented via median predictions with 75% prediction intervals of the regional total fertility rates. The simulation shows strong regional heterogeneities in long-term fertility trends that are associated with the historical background of Germany, housing supply for families, opportunities for education, and the strength of labor markets, inter alia.

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference58 articles.

1. A Principal Component Simulation of Age-Specific Fertility—Impacts of Family and Social Policy on Reproductive Behavior in Germany;Vanella;Popul. Rev.,2019

2. Stochastic Forecasting of Labor Supply and Population: An Integrated Model;Fuchs;Popul. Res. Policy Rev.,2018

3. Population Ageing and Future Demand for Old-Age and Disability Pensions in Germany—A Probabilistic Approach;Vanella;Comp. Popul. Stud.,2022

4. Prevalence and Economic Costs of Absenteeism in an Aging Population—A Quasi-Stochastic Projection for Germany;Vanella;Forecasting,2022

5. A probabilistic projection of beneficiaries of long-term care insurance in Germany by severity of disability;Vanella;Qual. Quant.,2020

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