How Late Can First Births Be Postponed? Some Illustrative Population-level Calculations

I shift, stretch, and transform the observed cohort age-schedule of first birth for Danish women born in 1963 to see how late the mean age at first birth could plausibly shift. Constraints of two kinds are placed on the ultimate distribution of first births. First, no more than one-third of first births can occur after age 35. This constraint allows postponement without radical changes in childlessness or parity distribution. Second, I preserve some variability in the age at first birth by keeping the standard deviation of first birth above 4 years, the minimum value observed for Denmark during the baby boom years. Under these constraints, I find that mean ages at first birth of at least 33 years are plausible. This would represent a further increase of about 4 years in the mean age at first birth seen in recent periods. I conclude that the depressed levels of fertility seen due to postponement could continue for decades before limits are reached.

How slowing senescence changes life expectancy

Mortality decline has historically been a result of reductions in the level of mortality at all ages. The slope of mortality increase with age has been remarkably stable. A number of leading researchers on aging, however, suggest that the next revolution of longevity increase will be the result of slowing down the rate of aging, lessening the rate at which mortality increases as we get older. In this paper, we show mathematically how varying the pace of senescence influences life expectancy. We provide a formula that holds for any baseline hazard function. Our result is analogous to Keyfitz's "entropy" relationship for changing the level of mortality. Interestingly, the influence of the shape of the baseline schedule on the effect of senescence changes is the complement of that found for level changes. We also provide a generalized formulation that mixes level and slope effects.

Cohort postponement and period measures

We introduce a new class of models in which demographic behavior such as fertility is postponed by differing amounts depending only on cohort membership. We show how this model fits into a general framework of period and cohort postponement that includes the existing models in the literature, notably those of Bongaarts and Feeney and Kohler and Philipov. The cohort-based model shows the effects of cohort shifts on period fertility measures and provides an accompanying tempo-adjusted measure of period total fertility in the absence of observed shifts. Simulation reveals that when postponement is governed by cohorts, the cohort-based indicator outperforms the Bongaarts and Feeney model that is now in widespread use. The cohort-based model is applied to fertility in several modern populations.

East Germany overtakes West Germany: recent trends in order-specific fertility dynamics

Some 20 years after unification, the contrast between East and West Germany provides a unique natural experiment for studying the persistence of communist-era family patterns, the effects of economic change, and the complexities of the process of fertility postponement. After unification, fertility rates plummeted in the former East Germany to record low levels. The number of births per year fell 60 percent. The period total fertility rate (TFR) reached a low of 0.8. Since the middle of the 1990s, however, period fertility rates have been rising in East Germany, in contrast to the nearly constant rates seen in the West. By 2008, the TFR of East Germany had overtaken that of the West. In this paper, we explore why fertility in the East is higher than in West Germany, despite the severe economic situation in the East, whether the East German TFR will increase even further in the future, and whether the West German rate will remain at the constantly low level that has prevailed since the 1970s. This article seeks to shed some light on these questions by (a) giving an account of the persisting East-West differences in attitudes towards and constraints on childbearing, (b) conducting an order-specific fertility analysis of recent fertility trends, and (c) projecting completed fertility for the recent East and West German cohorts. In addition to using the Human Fertility Database, we draw upon Perinatal Statistics, which enable us to conduct an order-specific fertility analysis. This new data source allows us to calculate a tempo-corrected TFR for East and West Germany, which has not been available previously.Germany, fertility

Probabilistic forecasting using stochastic diffusion models, with applications to cohort processes of marriage and fertility

We study prediction and error propagation in Hernes, Gompertz, and logistic models for innovation diffusion. We develop a unifying framework in which the models are linearized with respect to cohort age and predictions are derived from the underlying linear process. We develop and compare methods for deriving the predictions and show how Monte Carlo simulation can be used to estimate prediction uncertainty for a wide class of underlying linear processes. For an important special case, random walk with, we develop an analytic prediction variance estimator. Both the Monte Carlo method and the analytic variance estimator allow the forecasters to make precise the level of within-model prediction uncertainty in innovation diffusion models. Empirical applications to first births, first marriages and cumulative fertility illustrate the usefulness of these methods.

Culture revisited: a geographic analysis of fertility decline in Prussia

In this paper, we re-introduce geography into the analysis of fertility decline in the first demographic transition in Europe. We reanalyze Galloway et al.'s (1994) Prussian data, fitting structural models similar to those of Galloway et al. to the data and to map the residuals. Our findings give evidence both of the predictive effect of economic as well as cultural variables. However, although testing different non-spatial model specifications, a significant unexplained geographic clustering of fertility decline always remains. Indeed, adjacency to an area of large fertility decline and location along communication and transport corridors seem to be important predictors of fertility decline beyond what one would expect from structural models. This gives support to the cultural diffusion hypothesis of the Princeton European Fertility Project.German Empire, culture, diffusion of innovations, economics, fertility decline, spatial analysis

The increasing importance of economic conditions on fertility

This paper investigates whether there has been a fundamental change in the importance of economic conditions on fertility. Through the 1980s econometric studies had found at best a mixed, neutral or negative effect of economic conditions on fertility. Notably, Butz and Ward (1979) concluded that fertility was counter-cyclical, with fertility falling in good times, as the opportunity costs of childbearing rose. More recently, there have been signs that fluctuations in fertility have been pro-cyclical, with good economic times being associated with higher birth rates, and the recent recession with lower birth rates. In this paper, we use panel methods to study short term changes in aggregate fertility and economic measures in OECD countries from 1976-2008. We find indeed that fertility became positively associated with good economic conditions. Furthermore, the increasing importance of economic conditions was detected for both tempo and quantum.economic conditions, total fertility rate

The end of 'lowest-low' fertility? (with supplementary materials)

Period fertility rates fell to previously unseen low levels in a large number of countries beginning in the early 1990s. The persistence of Total Fertility Rates under 1.3 raised the possibility of dramatic, rapid population aging as well as population decline. In an analysis of recent trends, we find, however, a widespread turn-around in so-called “lowest-low” fertility countries. The reversal has been particularly vigorous in Europe. The number of countries with period total fertility rates less than 1.3 fell from 21 in 2003 to five in 2008, of which four (Hong Kong, Korea, Singapore and Taiwan) are in East Asia. Moreover, the upturn in the period TFR was not confined to lowest-fertility countries, but affected the whole developed world. We explore the demographic explanations for the recent rise in fertility stemming from fertility timing effects as well as economic, policy, and social factors. Although the current economic crisis may push down fertility in the short-run, we conclude that formerly lowest-low fertility countries should continue to see further increase in fertility as the transitory effects of shifts to later motherhood become less and less important.

Towards an Integrated Understanding of Demographic Change and its Spatio-Temporal Dimensions: Concepts, Data Needs and Case Studies

Demographic change is a macro-phenomenon, driven by decisions and events at the individual level. However, individual-level events are often influenced by the spatial socioeconomic context in which the actors are embedded. This context usually changes slowly over time which suggests that the present circumstances depend to a large extent on past developments. In this paper, we outline how a GIS-based empirical research approach can deepen our understanding of the spatio-temporal dimensions of demographic change. This approach can benefit from the concepts and methods of at least three disciplines: demography, geography and historical sciences. In addition, we describe the recent improvements in the (geo-)data infrastructure, with the goal of overcoming data limitations that have so far restricted research in this field. Three case studies illustrate the potential of such an approach

Berkeley Unified Numident Mortality Database: Public administrative records for individual-level mortality research

Background: While much progress has been made in understanding the demographic determinants of mortality in the United States using individual survey data and aggregate tabulations, the lack of population-level register data is a barrier to further advances in mortality research. With the release of Social Security application (SS-5), claim, and death records, the National Archives and Records Administration (NARA) has created a new administrative data resource for researchers studying mortality. We introduce the Berkeley Unified Numident Mortality Database (BUNMD), a cleaned and harmonized version of these records. This publicly available dataset provides researchers access to over 49 million individual-level mortality records with demographic covariates and fine geographic detail, allowing for high-resolution mortality research. Objective: The purpose of this paper is to describe the BUNMD, discuss statistical methods for estimating mortality differentials based on this deaths-only dataset, and provide case studies illustrating the high-resolution mortality research possible with the BUNMD. Methods: We provide detailed information on our procedure for constructing the BUNMD dataset from the most informative parts of the publicly available Social Security Numident application, claim, and death records. Contribution: The BUNMD is now publicly available, and we anticipate these data will facilitate new avenues of research into the determinants of mortality disparities in the United States