Projecting Spanish fertility at regional level: A hierarchical Bayesian approach

Abstract

The transition from a demographic regime of high mortality and high fertility to one with low mortality and low fertility is universal and comes along with the process of socio-economic modernization. The Spanish total fertility rate has decreased to below replacement levels in the last decades. The decline has persisted since the 1960s and is diverse across the country. Based on that diversity, the use of population forecasts, not only at national but at regional levels, for planning purposes (governments and private sector) with large horizons has become a must to provide essential services. Using a Bayesian hierarchical model we constructed probabilistic fertility forecasts for Spain at the regional level. Although this approach is already issued by the United Nations little research has been done focusing on the Spanish subnational level. Our objective is to disaggregate the national projections of the total fertility rate for Spain into regional forecasts. The results of this research will show the model fitting, first to the national level and then using a multifaceted and continuous evolution of fertility over time, at the regional level, to check its convergence.

Региональная Дифференциация Рождаемости В Российской Федерации: Оптика Реальных Поколений

“…На данный момент почти все международные организации при прогнозировании рождаемости используют именно байесовские иерархические модели. Этот методологический подход доказал свою эффективность на национальном уровне (Pelletier 2021), однако лишь относительно недавно стал применяться на региональном уровне к показателям рождаемости условных и реальных поколений (Rafael, García-Moreno, Pérez-Priego 2022).…”

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

“…Therefore, it randomizes over a realistic scenario space of future fertility patterns. Recently, Rafael Caro-Barrera et al [29] followed a similar approach with more detailed national data for stochastic TFR projections for all regions of Spain. In the case of Australia, Yang et al suggested a concept of including regional factors and migration backgrounds via means of the mother's birthplace into forecasts of ASFRs.…”