Long-term projections are the bedrock of any analysis looking at the sustainability of public finances. This paper computes the changes in economic growth in individual European Union countries needed for government debt-to-GDP ratios to stay on their baseline trajectories (taken from the European Commission’s Debt Sustainability Monitor 2023) under high life expectancy, low-fertility, low-migration, and high-migration scenarios. These scenarios are provided in the Commission’s Ageing Report (2024). We find that deviations of migration from the baseline entail the largest effect on the required rate of economic growth. The effects of the low-fertility scenario are most pronounced in the very long run and sometimes exceed those of low migration. Our findings inform policymakers about the potential role of higher productivity growth in alleviating the public finance consequences of demographic shocks. The importance of higher productivity growth is increased by the fact that in some countries demographic projections tend to be optimistic.

The “demographic dividend” refers to the boost to GDP per capita growth countries experience during the part of the demographic transition when age dependency ratios plummet. The size and the source of the dividend are debated in the literature. Using newly constructed age-specific population data by country from the beginning of the demographic transition to the present day, this paper estimates the contribution of changing age structure to GDP per capita growth during the demographic transition. A quantitative overlapping-generations model is used to produce country-specific estimates of the dividend and to disentangle its drivers. Model simulations for 101 countries suggest a global average boost of 0.40 percentage points per annum to GDP per capita growth during the dividend period. Changing age structure explains 9.5% of total growth during the period of the demographic dividend on average. Countries with more rapid and more extreme changes in age structure experience larger dividends.

We analyze the effects of different pay-as-you-go public pension systems on financial imbalance, rate of return, and inequality of heterogeneous generations in terms of gender and education. We include aspects that are relevant for developing countries such as labor informality and payment of an old-age and social benefit. We introduce a new mixed system that combines components of the defined benefit (DB) and the defined contribution (DC) systems. Results show the new mixed system represents a compromise between the DB and DC systems and that a scheme (inspired in the German system) exhibits the highest rates of return and horizontal equity.

We investigate whether the diseases for which there was more biomedical innovation had larger 1999–2019 reductions in premature mortality. Biomedical innovation related to a disease is measured by the change in the mean vintage of descriptors of PubMed articles about the disease. We analyze data on 286 million descriptors of 27 million articles about over 800 diseases. Premature mortality from a disease is significantly inversely related to the lagged vintage of descriptors of articles about the disease. In the absence of biomedical innovation, age-adjusted mortality rates would not have declined. Some factors other than biomedical innovation (e.g., a decline in smoking and an increase in educational attainment) contributed to the decline in mortality. But other factors (e.g., a rise in obesity and the prevalence of chronic conditions) contributed to an increase in mortality. Biomedical innovation reduced the mortality of white people sooner than it reduced the mortality of black people.

Building on Lucas (1988) and Boucekkine et al. (2013), we develop a model in which the impact of population dynamics on per capita GDP and human capital depends on the balance of intertemporal altruism effects toward future generations and class-size effects on an individual’s education investment. We show that there is a critical level of the class-size effects that determines whether a decline in population growth will lead to a decrease or an increase in a country’s long-run growth rate of real per capita income. We take the model to OECD data, using a semi-parametric technique. This allows us to classify countries into groups based on their long-term growth trajectories, revealing patterns not captured by previous studies on the topic.

The emergence of COVID-19 has resulted in a notable rise in mortality rates, consequently affecting various sectors, including the insurance industry. This paper analyzes the reflections of a sudden increase in mortality rates on the financial performance of a survival benefit scenario under the International Financial Reporting Standard 17. For this purpose, we thoroughly examined a single insurance scenario under four different states by modifying the interest and jump elements. We use Poisson-log bilinear Lee–Carter and Vasicek models for mortality and stochastic interest rate, respectively. Integrating the mortality model with a jump model that incorporates COVID-19 deaths we constructed a temporary mortality jump model. As a result, the temporary mortality jump model reflects the effects of the pandemic more realistically. We observe that even in this case mortality has a minor impact, whereas interest rates significantly still affect the financial position and performance of insurance companies.

This paper investigates the effects of demographic shifts on labor productivity by leveraging variation in the age structure of Italian regions. These effects are analyzed along a first channel – the direct relation between population age and productivity – and a second channel capturing the productivity implications of a more or less dispersed age distribution. We propose an estimation framework that relates regional productivity to the entire age distribution of the working-age population and use instrumental variable techniques to address endogeneity issues. The estimates yield a hump-shaped age-productivity profile peaking between 35 and 40 years. We also document non-linear effects of regional age dispersion on productivity.

This study investigates the linkages between changes in agricultural land use and population growth in India. We have employed long-term time series and a panel dataset of 1869 samples (267 districts × 7 time points from 1961 to 2021) to determine this. We theorize that there is an inverted “U-shape” relationship between changes in population growth and agricultural land. Our findings suggest a positive impact of population growth on the change in cultivated land. However, this relationship was not static during 1961–2021. We found a two-stage split relationship with a breakpoint in 1981. Prior to the 1980s, there was a 12% expansion in cultivated land in response to a unit increase in population growth. During the post-1980s, with a unit decline in population growth, there was a 5% reduction in cultivated land. The findings were reaffirmed through several robustness checks: analyses using alternative outcome variables, alternative break points in a segmented regression model, and spatial modeling. From a policy perspective, this study advances the need for the reduction of population growth rate in high-fertility states and the adoption of superior and green technology for agricultural intensification and diversification to stop cropland expansion at the cost of environmental sustainability.

Using a polynomial cointegration technique, this paper shows that the bilateral US current account balance with China has a U-shaped relationship with the life expectancy gap between the US and China. A narrowing gap initially increases the US deficit with China, but eventually, this increased US deficit falls with the further catching-up of Chinese life expectancy. The life expectancy gap between the two countries has been below the threshold level since 2013, and this demographic trend has the potential to improve the US deficit with China. This U-shaped relationship can be theoretically reproduced. A two-country overlapping generations model indicates that the effect of life expectancy is decomposed into four components: retirement savings, social security burden, the number of elderly workers, and the productivity of elderly workers. The total effect of foreign life expectancy on the home current account balance exhibits a sign change in the catching-up of foreign life expectancy.

The construction industry is experiencing high demand for workers. Apprenticeship programmes are essential pipelines of skilled workers into the construction industry; however, apprenticeship completion rates are only around 25%. To promote apprenticeship retention and increase the number of apprentices, it is necessary to identify factors that relate to cancellation from apprenticeship programmes (i.e., leaving prior to programme completion). Using data from the Registered Apprenticeship Partners Information Database System, we descriptively characterised completion and cancellation, then conducted a time-to-event analysis of n = 335,212 construction apprentices from 2012 to 2023 to examine factors related to cancellation. Among all apprentices, 40.1% cancelled from their apprenticeship programmes, while 24.8% completed and 35.0% were actively registered at the end of the study period. Results from the time-to-event analysis show females had significantly higher odds of cancellation than males (OR: 1.11; 95% CI: 1.08, 1.15). Compared to White apprentices, American Indian/Alaska Native (OR: 1.13; 95% CI: 1.08, 1.18), Black/African American (OR: 1.41; 95% CI: 1.39, 1.44), and multiracial apprentices (OR: 1.09; 95% CI: 1.02, 1.17) had significantly higher odds of cancellation, while Asian apprentices had significantly lower odds of cancellation (OR: 0.79; 95% CI: 0.75, 0.83). Non-unionised workers were significantly more likely to cancel their apprenticeship programmes (OR: 1.77; 95% CI: 1.74, 1.80). These results indicate that individual demographic and organisational factors can influence apprenticeship cancellation. Reducing barriers to apprenticeship completion can help address the current skilled worker shortage, and identifying factors that impact entry into the industry for minoritised groups can promote equity within the industry.

This paper examines the effects of heterogeneous biased expectations between the young and old on business cycles and explores its policy implications. Empirical findings reveal that individuals, particularly the young, can have more optimistic or pessimistic views about the future state of the economy compared to the data-generating measure. This study relates these results to the learning-from-experience literature, which suggests that individuals, particularly the young, place greater weight on recent observations when forming their expectations. Incorporating household weighting schemes into a life-cycle learning model, I show that household sensitivity to recent observations amplifies the effects of economic shocks. However, the amplification effects become less extensive as the population ages due to the lower sensitivity of the old. My simulation results indicate that a 10 percentage point increase in the old population ratio leads to a 16 percent decrease in output volatility. Regarding policy implications, this paper suggests that the government spending multiplier declines by approximately 10 percent when the old population ratio rises by 10 percentage points due to weak amplification effects. Moreover, the weakened output effects deteriorate the welfare of the population, particularly that of the young.

We study whether the increased adoption of available automation technologies allows economies to avoid the negative effect of aging on per capita output. We develop a quantitative theory in which firms choose to which extent they automate in response to a declining workforce and rising old-age dependency. An important element in our model is the integration of two capital types: automation capital that acts as a substitute to human labor, and traditional capital that is a complement to labor. Empirically, our model's predictions largely match data regarding automation (robotization) density across OECD countries. Simulating the model, we find that aging-induced automation only partially compensates the negative growth effect of aging in the absence of technical progress in automation technology. One reason is that automated tasks are no perfect substitutes for non-automated tasks. A second reason is that automation raises the interest rate and thus inhibits positive behavioral reactions to aging (later retirement and investment in human capital). Moreover, increased automation generates a falling net labor share of income and rising welfare inequality. We evaluate alternative policy responses to cope with this inequality.

As the heterogeneity in life expectancy by socioeconomic status increases, many pension systems imply a wealth transfer from short- to long-lived individuals. Various pension reforms aim to reduce inequalities that are caused by ex-ante differences in life expectancy. However, these pension reforms may induce redistribution effects. We introduce a dynamic general equilibrium-overlapping generations model with heterogeneous individuals that differ in their education, labor supply, lifetime income, and life expectancy. Within this framework we study six different pension reforms that foster the sustainability of the pension system and aim to account for heterogeneous life expectancy. Our results highlight that pension reforms have to be evaluated at various dimensions. Reforms that may increase the sustainability of the pension system are not necessarily conducive to reduce the redistributive wealth transfers from short- to long-lived individuals. Our paper emphasizes the need for studying pension reforms in models with behavioral feedback and heterogeneous socioeconomic groups.

It is well-known that marital status is an important predictor for life expectancy. However, non-married individuals are often misclassified as singles which ignores the heterogeneity within the group. This paper shows the importance of distinguishing between types of singles, and in particular whether they are cohabiting, when predicting life expectancies. We use unique and detailed longitudinal register data to track marital status throughout the individual's lifetime. We find that all types of singles consistently benefit from living with a spouse, i.e., after divorce, becoming widower or being never married. This result holds for both men and women. For certain types of cohabiting singles we reject significant differences in life expectancy compared to married individuals. Finally, we use a case study to show that, like married individuals, all types of singles that cohabit also serve as informal caregivers and have the potential to limit the end-of-life long-term care expenditure levels.

Mortality shocks such as the one induced by the COVID-19 pandemic have substantial impact on mortality models. We describe how to deal with them in the period effect of the Lee–Carter model. The main idea is to not rely on the usual normal distribution assumption as it is not always justified. We consider a mixture distribution model based on the peaks-over-threshold method, a jump model, and a regime switching model and introduce a modified calibration procedure to account for the fact that varying amounts of data are necessary for calibrating different parts of these models. We perform an extensive empirical study for nine European countries, comparing the models with respect to their parameters, quality of fit, and forecasting performance. Moreover, we define five exemplary scenarios regarding the future development of pandemic-related mortality. As a result of our evaluations, we recommend the peaks-over-threshold approach for applications with a possibility of extreme mortality events.

This paper presents an empirical investigation of the hypothesis that exposure to the restrictive fertility policies of the Chinese “Later, Longer, Fewer” campaign in the 1970s contributes to the dynamics and patterns of elderly suicides in China in the period 2004–2017. We apply an identification strategy that exploits variation in exposure to this policy across birth cohorts that is based on the different timing of the implementation of the fertility policies across Chinese provinces. The results show that cohorts with a greater exposure to the restrictive fertility policy in the 1970s exhibit higher suicide rates during old ages.

Greater labor migration can establish more channels for information flows, directly contributing to faster economic growth and improved innovation and work. It can also expand international remittances, which can be invested by recipient households in home countries in education, entrepreneurship, and improved and sustainable agricultural technologies. At the same time, however, increased emigration of medical professionals and technical workers from poor countries can reduce quality of local services, innovation, health status, and productivity. This analysis attempts to quantify the economic benefits and costs of permitting an immediate 10% increase in the bilateral migration of skilled workers (physicians, engineers or science, engineering, technology, and mathematics workers, and other persons with advanced educations) among the nations of the African Continental Free Trade Area and, more broadly, among 25 global regions. Economic benefits include higher migrant incomes abroad, welfare gains in destination countries associated with higher economic efficiency, spillover productivity gains, and an improved ability of the younger and more skilled working force to support the needs of the wider population, resulting in higher national production. Benefits in source countries include productivity enhancements from two sources: (a) greater access to knowledge associated with more bilateral trade and investment and (b) the ability of local households to invest remittances in productivity-enhancing activities. Welfare losses in source nations include static efficiency reductions and a worsened demographic support capability. In Africa, the benefit-cost ratios range from 3.7 to 6.9; in the global analysis, 17 to 38.

In the first half of the twentieth century, deaths from infectious disease, especially among the very young, fell dramatically in American cities. However, as infant mortality fell and life expectancy rose, racial inequality in urban infectious disease mortality grew. In this paper, we show that the fall in mortality and the rise in racial inequality in mortality reflected two countervailing processes. The dramatic decline in infant mortality from waterborne diseases drastically reduced the total urban infectious disease mortality rate of both Black and white Americans while having a comparatively small effect on the total racial disparity in urban infectious disease mortality. In contrast, the unequal fall in tuberculosis mortality, particularly in the prime of life, widened racial inequality in infectious disease mortality in US cities.

This study develops a Malthusian model for the evolution of human society from hunting-gathering to agriculture and from agriculture to industrial production. Human society evolves across these stages as the population grows. However, under endogenous population growth, the population may stop growing at any stage. If it fails to reach the first threshold, the population remains as hunter-gatherers. If it reaches the first threshold, an agricultural society emerges. Then, if the population fails to reach the industrial threshold, it remains in an agricultural Malthusian trap without experiencing industrialization. Interestingly, high agricultural productivity triggers not only the Neolithic Revolution but also the subsequent industrialization. Using cross-country data to test this result, we employ an index of prehistoric biogeographic conditions that affect agricultural productivity as an instrument for the timing of transitions to agriculture and find that an earlier transition to agriculture has a positive effect on industrialization in the modern era.

This paper examines inter-industry patterns of the employment of older workers over the last 20 years to understand where employment opportunities have grown the most. The underlying premise is that firms strategically align their age mix depending on production function and labor cost parameters. The industries that had the largest increases in the percentage of older workers were those that had the broadest pension coverage and those that made the greatest use of high-tech capital. There also is evidence in 2001–07 that the percentage of older workers increased more in the industries most exposed to increased Chinese imports.