Abstract The COVID‐19 pandemic opened a polycrisis of interrelated disruptions and compounding economic and subjective uncertainty that likely shaped fertility in high‐income countries, especially in its second phase, in which the Ukraine war was a major source and amplifier of uncertainty. Yet fertility evidence remains largely limited to the pandemic. We estimate monthly “excess” total fertility rates (TFRs) and find that declines compared to projected pre‐polycrisis trends were short‐lived during the first phase and excess TFRs overall positive in all 26 sample countries except Eastern Europe and Portugal. Instead, during the second phase, excess TFRs are strongly and increasingly negative in Eastern and Central Europe, Greece, Portugal, France, Denmark, and Sweden. Investigating potential explanatory variables, we find that the total, energy, and housing consumer price indices and reversed consumer confidence are negatively associated with excess TFRs, especially in Eastern and Central Europe, Greece, France, Denmark, and Sweden. Refugee inflows, the economic policy uncertainty index, and the geopolitical risk index show weaker negative associations. But country heterogeneity is large. Our analysis suggests that fertility dynamics are closely linked to the polycrisis, citizens’ economic conditions and confidence are the strongest correlates, and extensive welfare regimes alone may not consistently sustain fertility under accumulating uncertainty.
Abstract Substantial demographic and democratic changes have unfolded globally in recent history, inviting inquiry into the relationship between these two phenomena. Joining the growing research in political demography, we advance a conceptual framework that links structural demographic factors to democratic progress and decline through economic, ideological, and representational mechanisms. Guided by this framework, we analyze two key demographic factors using an original longitudinal dataset covering 153 countries from 1975 to 2020. The results demonstrate a nonlinear and context‐dependent relationship between demography and democracy. Specifically, population aging and immigration levels are generally associated with lower levels of democracy; though in the case of immigration, this relationship weakens as immigrant shares increase, indicating a nonlinear pattern. Importantly, demography is not destiny: the relationship between population structure and democracy is further shaped by economic and political contexts. Overall, this paper underscores the profound and nuanced ways in which structural demographic change shapes democratic outcomes.
Abstract Despite both homicide and suicide being identified as global public health concerns, it is unclear whether and how homicide trends could shape suicide patterns, particularly in low‐or‐middle income countries. We use the case of Mexico, an upper‐middle‐income country that experienced a dramatic increase in homicide after a shift in drug‐enforcement policy in 2006, to evaluate the relationship between community violence and suicide. Our analysis relies on geocoded death certificates microdata for the entire national territory to assess the association between homicide rates and suicide rates at the municipality level for the 2000–2019 period. We find evidence of positive associations between homicide rates and suicide within six months of exposure to high homicide levels, and especially in the period immediately after homicide spikes relative to the violence baseline in the previous three years. These surges in suicide are primarily driven by auto‐inflicted strangulation. No changes in suicide were identified after more than six months of exposure to high homicide levels, or as exposure to increasing homicides accumulated in the long term. Our results are consistent with violence spikes predicting an instant but transitory increase in suicide, plausibly by causing acute fear, stress, and uncertainty in the period immediately surrounding drastic surges in violence.
Abstract Fertility preferences offer insights into how social factors shape behavior. Despite their significance, it remains unclear whether preference measures capture distinct, firm constructs in respondents’ minds, or to what extent responses reflect survey design choices like question order. In two survey experiments, we tested whether the sequence of fertility preference measures affected responses. The first experiment manipulated the sequence of general ideal, personal ideal, wanted, and expected fertility among college students. Sequence changes caused no changes in means for these measures, except for expected, which declined when asked later. Personal ideal and wanted fertility were indistinguishable from each other and were fairly unresponsive to sequencing. The second experiment compared general and personal ideals among a sample representative of U.S. adults. Preferences were firm and distinct among reproductive‐age individuals. For older respondents, the measures were equivalent when asked first, but personal ideal declined when asked after general ideal. Across both samples, general ideal fertility remained similar and higher than other measures for reproductive‐age respondents. These findings suggest that most preferences are relatively unaffected by ordering. We also offer guidance for survey design; general ideals are not interchangeable with other preference measures, and fertility expectations may not be comparable across survey designs.
Abstract Up‐to‐date subnational population estimates—disaggregated by age, sex, and to the lowest possible geographical level —are a key component of evidence‐based humanitarian action. In many humanitarian crises, however, large‐scale population mobility, combined with disruptions to national statistical systems, makes updating subnational population estimates challenging. Addressing these estimation challenges requires incorporating nontraditional population data sources, including mobility data generated for operational humanitarian response efforts, and addressing a range of data interoperability issues. In this paper, we present recent work by the United Nations Population Fund to update subnational population projections for Mozambique, Haiti, and Sudan by adapting applied demographic methods to a mix of traditional and nontraditional population data sources. These projections are used by UN Humanitarian Country Teams as a common population baseline for UN system‐wide decision‐making and operational response. We also highlight how cohort‐component Bayesian probabilistic projection techniques can be leveraged, alongside modeling of subnational mobility flows, to better measure and communicate uncertainty to humanitarian decision‐makers in limited‐data settings. Our work offers insights on key issues related to population data and estimation in humanitarian settings, including accounting for the impact of large‐scale crisis‐related mobility in subnational population projections.
