Parsimonious stochastic forecasting of international and internal migration on the NUTS-3 level – an outlook of regional depopulation trends in Germany

Abstract

Substantiated knowledge of future demographic changes that is derived from sound statistical and mathematical methods is a crucial determinant of regional planning. Of the components of demographic developments, migration shapes regional demographics the most over the short term. However, despite its importance, existing approaches model future regional migration based on deterministic assumptions that do not sufficiently account for its highly probabilistic nature. In response to this shortcoming in the literature, our paper uses age- and gender-specific migration data for German NUTS-3 regions over the 1995–2019 period and compares the performance of a variety of forecasting models in backtests. Using the bestperforming model specification and drawing on Monte Carlo simulations, we present a stochastic forecast of regional migration dynamics across German regions until 2040 and analyze their role in regional depopulation. The results provide evidence that well-known age-specific migration patterns across the urban-rural continuum of regions, such as the education-induced migration of young adults, are very likely to persist, and to continue to shape future regional (de)population dynamics.

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

“…Therefore, the long-term forecasting of fertility trends is essential for sound economic or political planning [1]. The analysis of trends and disparities across regions have gained momentum in demographic research [8][9][10][11]. However, a research gap remains concerning (stochastic) forecasting of regional fertility.…”

“…Fertility is of major importance for regional development. For instance, regions with low fertility are susceptible to a long-term lack in the labor force if they cannot compensate persistent low births with, e.g., the immigration of qualified workers [11]. Regional fertility trends also have substantial implications for the planning of educational resources [14].…”

“…In the long term, low fertility is the main driver of the aging and depopulation of societies [1,16]. However, for a relatively large and heterogeneous country such as Germany [11], inequalities in fertility trends are prevalent as well. The regions mostly affected by low fertility rates are economically weaker regions, metropolises, and university cities [17,18].…”

“…Therefore, efficient approaches are a prerequisite to deal with high dimensionality. Multivariate methods, especially principal component analysis (PCA), are established approaches in this regard [11,21]. Second, fertility rates among adjacent or structurally similar regions and age groups are often strongly correlated [13,17,19].…”

“…Probabilistic forecasts, in contrast, quantify a theoretically infinitely large number of realistic future scenarios based on simulations that allow to quantify probabilities and intervals instead of point forecasts [22]. Therefore, stochastic approaches are preferable [11,13], especially in the regional context (where risks of misprojections are especially high because of a relatively small number of observations, and there is a high potential for misinformation regarding the targeted recipients of the forecasts). Stochastic forecasts, therefore, offer more information that can be used for well-informed decision making [24,25].…”