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on Economics of Ageing |
| By: | Kristin F. Butcher; Kelsey Moran; Tara Watson |
| Abstract: | The U.S. population is aging. We examine whether immigration causally affects the likelihood that the U.S.-born elderly live in institutional settings. Using a shift-share instrument to identify exogenous variation in immigration, we find that a 10 percentage point increase in the less-educated foreign-born labor force share in a local area reduces institutionalization among the elderly by 1.5 and 3.8 percentage points for those aged 65+ and 80+, a 26-29 percent effect relative to the mean. The estimates imply that a typical U.S-born individual over age 65 in the year 2000 was 0.5 percentage points (10 percent) less likely to be living in an institution than would have been the case if immigration had remained at 1980 levels. We show that immigration affects the availability and cost of home services, including those provided by home health aides, gardeners and housekeepers, and other less-educated workers, reducing the cost of aging in the community. |
| JEL: | I11 J14 J15 J61 |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:29520&r= |
| By: | Fuchs, Johann (Institute for Employment Research (IAB), Nuremberg, Germany); Söhnlein, Doris (Institute for Employment Research (IAB), Nuremberg, Germany); Weber, Brigitte (Institute for Employment Research (IAB), Nuremberg, Germany) |
| Abstract: | "In the long term, demographic developments in Germany will lead to a decline in the number of people of working age and thus also in the potential labor force. Higher labor force participation by women and, above all, by older people can only mitigate this trend. Immigration from abroad strengthens the demographic base, but is not necessarily sufficient to fully compensate for the demographic effect. As in previous projections of the labor force potential, several projection variants are calculated to show the impact of migration. We discuss two variants in more detail: a variant derived from a stochastic forecast model and a variant with extremely high migration, in which the labor force potential would remain roughly constant in the long term. A sensitivity analysis supplements the analysis with the question of what effects could result from significantly higher increases in labor force participation rates." (Author's abstract, IAB-Doku) ((en)) |
| Date: | 2021–11–23 |
| URL: | http://d.repec.org/n?u=RePEc:iab:iabkbe:202125&r= |
| By: | Martin Hackmann (UCLA, NBER, and CESifo); Joerg Heining (Institut für Arbeitsmarkt-und Berufsforschung (IAB)); Roman Klimke (Harvard University); Maria Polyakova (Stanford University, NBER and CESifo); Holger Seibert (Institut für Arbeitsmarkt-und Berufsforschung (IAB)) |
| Abstract: | Arrow (1963) hypothesized that demand-side moral hazard induced by health insurance leads to supply-side expansions in healthcare markets. Capturing these effects empirically has been challenging, as non-marginal insurance expansions are rare and detailed data on healthcare labor and capital is sparse. We combine administrative labor market data with the geographic variation in the rollout of a universal insurance program—the introduction of long-term care (LTC) insurance in Germany in 1995—to document a substantial expansion of the inpatient LTC labor market in response to insurance expansion. A 10 percentage point expansion in the share of insured elderly leads to 0.05 (7%) more inpatient LTC firms and four (13%) more workers per 1,000 elderly in Germany. Wages did not rise, but the quality of newly hired workers declined. We find suggestive evidence of a reduction in old-age mortality. Using a machine learning algorithm, we characterize counterfactual labor market biographies of potential inpatient LTC hires, finding that the reform moved workers into LTC jobs from unemployment and out of the labor force rather than from other sectors of the economy. We estimate that employing these additional workers in LTC is socially efficient if patients value the care provided by these workers at least at 25% of the market price for care. We show conceptually that, in the spirit of Harberger (1971), in a second-best equilibrium in which supply-side labor markets do not clear at perfectly competitive wages, subsidies for healthcare consumption along with the associated demand-side moral hazard can be welfare-enhancing. |
| Keywords: | long-term care, universal insurance expansion, Germany, LTC labor market, second-best efficiency |
| JEL: | D61 I11 I13 J21 J23 |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:upj:weupjo:21-357&r= |
| By: | Jos\'e Manuel Aburto; Ugofilippo Basellini; Annette Baudisch; Francisco Villavicencio |
| Abstract: | The Gini coefficient of the life table is a concentration index that provides information on lifespan variation. Originally proposed by economists to measure income and wealth inequalities, it has been widely used in population studies to investigate variation in ages at death. We focus on a complementary indicator, Drewnowski's index, which is as a measure of equality. We study its mathematical properties and analyze how changes over time relate to changes in life expectancy. Further, we identify the threshold age below which mortality improvements are translated into decreasing lifespan variation and above which these improvements translate into increasing lifespan inequality. We illustrate our theoretical findings simulating scenarios of mortality improvement in the Gompertz model. Our experiments demonstrate how Drewnowski's index can serve as an indicator of the shape of mortality patterns. These properties, along with our analytical findings, support studying lifespan variation alongside life expectancy trends in multiple species. |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2111.11256&r= |
| By: | Nicole El Karoui; Kaouther Hadji; Sarah Kaakai |
| Abstract: | The aim of this paper is to study the long-term consequence on longevity of a mortality shock. We adopt an historical and modeling approach to study how the population evolution following a mortality shock such as the COVID-19 pandemic could impact future mortality rates. In the first of part the paper, we study the several cholera epidemics in France and in England starting from the 1830s, and their impact on the major development of public health at the end of the nineteenth century. In the second part, we present the mathematical modeling of stochastic Individual-Based models. Using the R package IBMPopSim, this flexible framework is then applied to simulate the long-term impact of a mortality shock, using a toy model where nonlinear population compositional changes affect future mortality rates. |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2111.08338&r= |
| By: | Jens Robben; Katrien Antonio; Sander Devriendt |
| Abstract: | We aim to assess the impact of a pandemic data point on the calibration of a stochastic multi-population mortality projection model and its resulting projections for future mortality rates. Throughout the paper we put focus on the Li & Lee mortality model, which has become a standard for projecting mortality in Belgium and the Netherlands. We calibrate this mortality model on annual deaths and exposures at the level of individual ages. This type of mortality data is typically collected, produced and reported with a significant delay of -- for some countries -- several years on a platform such as the Human Mortality Database. To enable a timely evaluation of the impact of a pandemic data point we have to rely on other data sources (e.g. the Short-Term Mortality Fluctuations Data series) that swiftly publish weekly mortality data collected in age buckets. To be compliant with the design and calibration strategy of the Li & Lee model, we have to transform the weekly mortality data collected in age buckets to yearly, age-specific observations. Therefore, our paper constructs a protocol to ungroup the deaths and exposures registered in age buckets to individual ages. To evaluate the impact of a pandemic shock, like COVID-19 in the year 2020, we weigh this data point in either the calibration or projection step. Obviously, the more weight we place on this data point, the more impact we observe on future estimated mortality rates and life expectancies. Our paper allows to quantify this impact and provides actuaries and actuarial associations with a framework to generate scenarios of future mortality under various assessments of the pandemic data point. |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2111.10164&r= |