Generalised count distributions for modelling parity

Legal Status and Fertility Patterns: Regulation-Induced Disruption Among Previously Undocumented Immigrant Women in Italy

We explore, using a unique survey dataset containing retrospective information on immigrants' legal status, the relationship between previous irregular experience-from arrival up to the first residence permit achievement-and fertility patterns among non-EU immigrant women in Italy. While competing hypotheses explaining migrants' fertility behaviour have been recurrently offered, there is a substantial lack of knowledge on the role of undocumented experience as a contextual barrier in shaping international migrants' family formation processes. We adopt a life-course approach, employing event history analysis and Poisson regression modelling, to investigate how irregularity among immigrant women intertwines with the timing of the first childbirth and the total number of births occurred in Italy. We find that irregular experience-as a time-dependent process-delays the transition to childbirth post-migration. Furthermore, having experienced irregular status reduces completed fertility, offering few possibilities to catch-up over the life-course with fertility levels of women continuously having the legal status. Findings suggest long-lasting effects of irregular status and the potential disruption of migrant's fertility induced by migration policies, admission systems, and regulation factors. The reduced possibility of legal entry channels and lack of migration policies for planning and managing migration into Italy may thus have an impact on family formation trajectories among international immigrant women.

Population Pyramids Yield Accurate Estimates of Total Fertility Rates

The primary fertility index for a population, the total fertility rate (TFR), cannot be calculated for many areas and periods because it requires disaggregation of births by mother's age. Here we discuss a flexible framework for estimating TFR using inputs as minimal as a population pyramid. We develop five variants, each with increasing complexity and data requirements. We test accuracy across a diverse set of data sources that comprise more than 2,400 fertility schedules with known TFR values, including the Human Fertility Database, Demographic and Health Surveys, U.S. counties, and nonhuman species. We show that even the simplest and least accurate variant has a median error of only 0.09 births per woman over 2,400 fertility schedules, suggesting accurate TFR estimation over a wide range of demographic conditions. We anticipate that this framework will extend fertility analysis to new subpopulations, periods, geographies, and even species. To demonstrate the framework's utility in new applications, we produce subnational estimates of African fertility levels, reconstruct historical European TFRs for periods up to 150 years before the collection of detailed birth records, and estimate TFR for the United States conditional on race and household income.