A Novel Approach to Regionalize Country‐Level GDP Projections

Socioeconomic projections are policy support tools that are often limited to country‐level data, making them insufficient for policy areas that require a more nuanced, sub‐national perspective. For granular geographical analyses in a multicountry setting, international organizations often rely on straightforward regionalization techniques, such as assuming that the observed regional shares remain constant over the projection period. This approach fails to capture the varying economic performances between regions, making the resulting regional projections unrealistic. In this paper, we propose a novel regionalization method for GDP projections based on (1) changes in population and (2) econometrically estimated factors of regional GDP per capita growth. We test our approach in the EU27 Member States for the period 2000–2019 by downscaling observed GDP from national to regional (NUTS3) level. Results show that our model substantially outperforms alternative regionalization techniques by improving the skill scores up to 18%. The performance of the proposed methodology increases for longer estimation and projection periods. Our regionalization approach shows the benefit of incorporating demographic dynamics and regional growth factors to regionalize national GDP values, especially to downscale long‐term GDP projections.