Puerto Rico has one of the lowest total fertility rates (TFR) in the world. Combined with a negative net migration and a high proportion of older adults, its unique situation motivates the need for further demographic analysis. Determining whether low fertility rates are mostly due to period or cohort effects is crucial for developing effective public policies that adapt to changes in fertility and population structures. The main objective of this work is to develop an Age-Period-Cohort model, in order to describe fertility data in Puerto Rico, from 1948-2022 and determine the contribution of period and cohort effects to fertility decline. The APC model was developed following a Bayesian framework, with a Poisson likelihood, RW(2) autorregressive priors for the APC parameters, and Scaled Beta2 priors for the precision parameters. Both frequentist and Bayesian methodologies attribute more importance to cohort effects when explaining fertility changes in Puerto Rico. Birth cohorts born in 1963-1967 onward have notably low fertility rates. There is no evidence of postponement of births in Puerto Rico, contrary to other countries with lowest-low fertility. Birth cohorts born in 1963-1967 onward have notably low fertility rates. This is the first application of APC analysis to fertility data in Puerto Rico, which describes fertility changes in a unique scenario in terms of demographic indicators, and the first APC analysis that shows the predominance of cohort effects when explaining fertility.

翻译：波多黎各是全球总生育率最低的地区之一。结合其净迁移为负、老年人口比例较高等特征，这一独特现象亟需更深入的人口学分析。判断低生育率主要源于时期效应还是队列效应，对于制定适应生育率与人口结构变化的有效公共政策至关重要。本研究旨在构建年龄-时期-队列（Age-Period-Cohort, APC）模型，以描述1948-2022年波多黎各的生育数据，并确定时期效应与队列效应对生育率下降的贡献。该APC模型采用贝叶斯框架开发，使用泊松似然函数、APC参数的二阶随机游走自回归先验以及精度参数的缩放Beta2先验。频率学派与贝叶斯方法论均认为队列效应在解释波多黎各生育率变化中更为重要。1963-1967年及之后出生的队列生育率显著偏低。与全球其他最低低生育率国家不同，波多黎各并未出现生育延迟现象。1963-1967年及之后出生的队列生育率显著偏低。本研究是首次将APC分析应用于波多黎各生育数据，揭示了人口学指标独特情境下的生育率变化，也是首项证明队列效应在解释生育率中占主导地位的APC分析。