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on Economics of Ageing |
| By: | Euamporn Phijaisanit (Faculty of Economics, Thammasat University) |
| Abstract: | Ageing societies pose a unique challenge for Thailand, where a large informal sector excludes most workers from mandatory retirement ages and social security coverage. While extending retirement ages is a pertinent consideration for the formal sector, policy considerations should also encompass the informal sector. Specifically, policies should strive to enhance the physical and cognitive abilities of older workers in the informal sector through appropriate guidance, empowering them to prolong their working years and bolster their financial security. Despite the availability of voluntary social security schemes, enrollment rates among informal workers remain low due to a combination of factors, including lack of awareness, perceived benefit inadequacy, financial burden, and reliance on alternative social welfare programs. Even those receiving the government's old-age allowance may struggle financially. This article highlights the underutilized potential of Thailand's extensive informal sector as a source of employment opportunities for older adults. Despite cross-country data suggesting a positive association between a large informal sector and high elderly employment rates, Thailand's labor force participation rate (LFPR) for individuals aged 65 and above remains comparatively low among similar developing nations. Furthermore, the LFPR decline for people transitioning from age group 55-64 to 65 and above is sharper in Thailand than in many other countries. The Active Ageing Index (AAI) can serve as a tool to investigate the factors contributing to Thailand's relatively low old-age LFPR by evaluating active ageing scores across various aspects. By identifying the missing elements in specific localities, the AAI and its sub-indices can guide local-area policy prioritization to address these gaps and enhance national policy effectiveness in promoting higher LFPR in old age. Fostering an active-ageing ecosystem within the informal sector will empower older individuals to continue working for longer periods and mitigate poverty risks in their later years. |
| Keywords: | Active Ageing, Informal Economy, Ageing Society, Labor Force Participation, Thailand |
| JEL: | E26 H53 I38 J14 J26 |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:tha:wpaper:20240215&r=age |
| By: | Huo, Shutong (University of California, Irvine); Feng, Derek (Yale University); Gill, Thomas M. (Yale University); Chen, Xi (Yale University) |
| Abstract: | Childhood circumstances may impact senior health, prompting this study to introduce novel machine learning methods to assess their individual and collective contributions to health inequality in old age. Using the US Health and Retirement Study (HRS) and the China Health and Retirement Longitudinal Study (CHARLS), we analyzed health outcomes of American and Chinese participants aged 60 and above. Conditional inference trees and forest were employed to estimate the influence of childhood circumstances on self-rated health (SRH), comparing with the conventional parametric Roemer method. The conventional parametric Roemer method estimated higher IOP in health ( China: 0.039, 22.67% of the total Gini coefficient 0.172; US: 0.067, 35.08% of the total Gini coefficient 0.191) than conditional inference tree ( China: 0.022, 12.79% of 0.172; US: 0.044, 23.04% of 0.191) and forest ( China: 0.035, 20.35% of 0.172; US: 0.054, 28.27% of 0.191). Key determinants of health in old age were identified, including childhood health, family financial status, and regional differences. The conditional inference forest consistently outperformed other methods in predictive accuracy as measured by out-of-sample mean squared error (MSE). The findings demonstrate the importance of early-life circumstances in shaping later health outcomes and stress the early-life interventions for health equity in aging societies. Our methods highlight the utility of machine learning in public health to identify determinants of health inequality. |
| Keywords: | life course, inequality of opportunity, childhood circumstances, machine learning, conditional inference tree, random forest |
| JEL: | I14 J13 J14 O57 C53 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16764&r=age |
| By: | Huo, Shutong; Feng, Derek; Gill, Thomas M.; Chen, Xi |
| Abstract: | Childhood circumstances may impact senior health, prompting this study to introduce novel machine learning methods to assess their individual and collective contributions to health inequality in old age. Using the US Health and Retirement Study (HRS) and the China Health and Retirement Longitudinal Study (CHARLS), we analyzed health outcomes of American and Chinese participants aged 60 and above. Conditional inference trees and forest were employed to estimate the influence of childhood circumstances on self-rated health (SRH), comparing with the conventional parametric Roemer method. The conventional parametric Roemer method estimated higher IOP in health (China: 0.039, 22.67% of the total Gini coefficient 0.172; US: 0.067, 35.08% of the total Gini coefficient 0.191) than conditional inference tree (China: 0.022, 12.79% of 0.172; US: 0.044, 23.04% of 0.191) and forest (China: 0.035, 20.35% of 0.172; US: 0.054, 28.27% of 0.191). Key determinants of health in old age were identified, including childhood health, family financial status, and regional differences. The conditional inference forest consistently outperformed other methods in predictive accuracy as measured by out-of-sample mean squared error (MSE). The findings demonstrate the importance of early-life circumstances in shaping later health outcomes and stress the earlylife interventions for health equity in aging societies. Our methods highlight the utility of machine learning in public health to identify determinants of health inequality. |
| Keywords: | Life Course, Inequality of Opportunity, Childhood Circumstances, Machine Learning, Conditional Inference Tree, Random Forest |
| JEL: | I14 J13 J14 O57 C53 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:glodps:1384&r=age |
| By: | Guthmuller, Sophie; Heger, Dörte; Hollenbach, Johannes; Werbeck, Anna |
| Abstract: | We investigate the short- and long-term effects of retirement on loneliness using panel data from the Survey of Health, Aging, and Retirement in Europe. To estimate causal effects, we exploit differences in retirement eligibility rules across and within countries and use retirement thresholds in an instrumental variable setting. On average, we find that entering retirement leads to a significant reduction in loneliness in the long run, although our results show no clear effect in the short run. The reduction is driven by individuals being less likely to feel socially isolated and lacking companionship. Our results suggest that individuals adapt to retirement by increasing their activity levels and reap the benefits in terms of reduced loneliness and social isolation. Heterogeneity analysis by gender reveals that retirement increases feelings of loneliness for women in the short term, and that this effect appears to be driven by women lacking companionship when their partner is not yet retired. |
| Abstract: | Wir untersuchen die Auswirkungen von Renteneintritt auf Einsamkeit in der kurzen und langen Frist mit Hilfe von Fragebogendaten der Survey of Health, Aging, and Retirement in Europe. Um einen kausalen Zusammenhang aufzuzeigen, nutzen wir die Unterschiede in den Altersgrenzen der Rentenberechtigungsregelungen zwischen und innerhalb der Länder in einer Instrumentenvariablenschätzung. Kurzfristig zeigen unsere Analysen keine Auswirkungen. Langfristig reduziert der Renteneintritt aber das Einsamkeitsgefühl, da sich die Menschen weniger sozial isoliert fühlen und weniger enge Kontakte vermissen. Unsere Ergebnisse legen nahe, dass Menschen nach einer gewissen Zeit im Ruhestand ihr Aktivitätsniveau erhöhen, was Einsamkeit und sozialer Isolation entgegenwirkt. Unsere geschlechtsspezifische Analyse zeigt allerdings, dass Frauen sich nach Renteneintritt kurzfristig einsamer fühlen und enge Kontakte vermissen, wenn ihr Partner zu dem Zeitpunkt noch nicht im Ruhestand ist. |
| Keywords: | Loneliness, social isolation, retirement, instrumental variable, causal effect |
| JEL: | J26 J14 I10 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:rwirep:282008&r=age |
| By: | Matías Mrejen; Letícia Nunes; Karla Giacomin |
| Keywords: | socioeconomic inequalities, elderly health, healthcare utilization, population aging |
| Date: | 2023–04–25 |
| URL: | http://d.repec.org/n?u=RePEc:amc:stdies:10&r=age |
| By: | Stipica Mudrazija; Barbara A. Butrica |
| Abstract: | This paper explores whether exposure to tight labor markets at working ages is linked to improved financial wellbeing at older ages especially for groups traditionally disadvantaged in the labor market, including people with low income, those without college degrees, and people of color. We also examine what role the timing of exposure to tight labor markets may play with respect to the outcomes of interest. |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:crr:crrwps:wp2023-21&r=age |
| By: | John Beshears; Matthew Blakstad; James J. Choi; Christopher Firth; John Gathergood; David Laibson; Richard Notley; Jesal D. Sheth; Will Sandbrook; Neil Stewart |
| Abstract: | Does automatic enrollment into retirement saving increase household debt? We study the randomized roll-out of automatic enrollment pensions to ~160, 000 employers in the United Kingdom with 2-29 employees. We find that the additional savings generated through automatic enrollment are partially offset by increases in unsecured debt. Over the first 41 months after enrollment, each additional month increases the average automatically enrolled employee’s pension savings by £32-£38, unsecured debt (such as personal loans and bank overdrafts) by £7, the likelihood of having a mortgage by 0.05 percentage points, and mortgage balances by £118. Automatic enrollment causes loan defaults to fall and credit scores to rise modestly. |
| JEL: | D14 D15 D90 G51 J32 |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32100&r=age |
| By: | Donner, Herman (Department of Real Estate and Construction Management, Royal Institute of Technology); Kulander, Maria (University of Gävle) |
| Abstract: | Utilizing a large-scale public health survey in Sweden, this paper analyzes the relationship between the fraction of elderly above the age of 80 who live in various tenure forms, and their social engagement. Social engagement is a measure of both social interaction with others, and overall engagement in society. This measure has an established relationship with mental and physical health, even as the causal mechanism are still understudied. Across 130 municipalities, we find that a higher fraction of elderly living in elderly housing is associated with a lower fraction of elderly classified as having a low level of social engagement. We also find that a higher fraction of elderly living in single-family houses is associated with a higher fraction of elderly classified as having a low level of social engagement. The results support that closer proximity to neighbors, and potentially the engagement offered through services in elderly care, increases overall social engagement among the elderly, thereby also assumably promoting better mental and physical health. The findings can inform housing policies towards elderly populations. |
| Keywords: | Elderly; Housing; Mental Health; Social Engagement; Social Interactions; Well-Being |
| JEL: | I31 J14 J26 |
| Date: | 2024–02–04 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:kthrec:2024_001&r=age |
| By: | Jolles, Daniel; Juanchich, Marie; Piccoli, Beatrice |
| Abstract: | Past research has shown that people are more likely to make the decision to hire candidates whose gender would increase group diversity when making multiple hiring choices in a bundle (i.e., when selecting multiple team members simultaneously) compared to making choices in isolation (i.e., when selecting a single team member). However, it is unclear if this bundling effect extends to age diversity and the selection of older candidates, as older workers are often the target of socially acceptable negative stereotypes and bias in recruitment, leaving them unemployed for longer than their younger counterparts. Across five preregistered experiments (total N = 4, 096), we tested if the positive effect of bundling on diversity of selections extends to older candidates in hiring decisions. We found evidence of bias against older job candidates in hiring decisions but found inconsistent effects of choice bundling on the selection of older candidates across experiments. An effect of bundling was found in two of five experiments, with no meta-analytic effect found across the five studies. Making older candidates more competitive and introducing a diversity statement aimed at increasing their selection both significantly increased older candidate selections, but failed to activate the bundling effect. We discuss the theoretical implications for choice bundling interventions and for age as a diversity characteristic to support the design of interventions that meet the challenges of an aging workforce. |
| Keywords: | hiring decisions; aging; diversity; decision making; Open Access funding |
| JEL: | R14 J01 |
| Date: | 2023–12–14 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:120910&r=age |
| By: | Lauren Hersch Nicholas; Kenneth M. Langa; Scott D. Halpern; Mario Macis |
| Abstract: | Despite the growing need for surrogate decision-making for older adults, little is known about how surrogates make decisions and whether advance directives would change decision-making. We conducted a nationally representative experimental survey that cross-randomized cognitive impairment, gender, and characteristics of advance care planning among hospitalized older adults through a series of vignettes. Our study yielded three main findings: first, respondents were much less likely to recommend life-sustaining treatments for patients with dementia, especially after personal exposure. Second, respondents were more likely to ignore patient preferences for life-extending treatment when the patient had dementia, and choose unwanted life-extending treatments for patients without dementia. Third, in scenarios where the patient's wishes were unclear, respondents were more likely to choose treatments that matched their own preferences. These findings underscore the need for improved communication and decision-making processes for patients with cognitive impairment and highlight the importance of choosing a surrogate decision-maker with similar treatment preferences. |
| JEL: | C99 I12 J14 |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32116&r=age |
| By: | Amy Finkelstein; Matthew J. Notowidigdo; Frank Schilbach; Jonathan Zhang |
| Abstract: | We leverage spatial variation in the severity of the Great Recession across the United States to examine its impact on mortality and to explore implications for the welfare consequences of recessions. We estimate that an increase in the unemployment rate of the magnitude of the Great Recession reduces the average, annual age-adjusted mortality rate by 2.3 percent, with effects persisting for at least 10 years. Mortality reductions appear across causes of death and are concentrated in the half of the population with a high school degree or less. We estimate similar percentage reductions in mortality at all ages, with declines in elderly mortality thus responsible for about three-quarters of the total mortality reduction. Recession-induced mortality declines are driven primarily by external effects of reduced aggregate economic activity on mortality, and recession-induced reductions in air pollution appear to be a quantitatively important mechanism. Incorporating our estimates of pro-cyclical mortality into a standard macroeconomics framework substantially reduces the welfare costs of recessions, particularly for people with less education, and at older ages where they may even be welfare-improving. |
| JEL: | E3 I1 |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32110&r=age |
| By: | - |
| Abstract: | In this edition of the Demographic Observatory, the impact of population dynamics is illustrated through an analysis of selected indicators of labour force estimates and projections by sex, age and area of residence for the 1980–2050 period in the 20 countries of Latin America, using the 2023 Revision prepared by the Latin American and Caribbean Demographic Centre (CELADE)-Population Division of the Economic Commission for Latin America and the Caribbean (ECLAC). The analysis highlights that structural changes in the labour force over the 1980–2022 period and projections through to 2050 show markedly different scenarios depending on age group, sex, and urban or rural area. This has implications for public policy in areas such as labour, education, health and care. The report also outlines the methodology applied and the data sources used to produce the estimates and projections. Labour force estimates and projections for urban and rural populations and by sex and by age groups for the 1950–2100 period are available at [online] https:// www.cepal.org/en/subtopics/demographic-projections/latin-america-andcaribbean- population-estimates-and-projections/population-estimates-andprojections- excel-tables. |
| Date: | 2024–01–10 |
| URL: | http://d.repec.org/n?u=RePEc:ecr:col044:68808&r=age |
| By: | Colasurdo, Andrea; Omenti, Riccardo |
| Abstract: | Background: Online genealogies are promising data sources for demographic research, but their limitations are understudied. This paper takes a critical approach to evaluating the potential strengths and weaknesses of using online genealogical data for population studies. Objective: We propose novel measures to assess the completeness and the quality of demographic variables in the FamiLinx data at both the individual and the familial level over the 1600-1900 period. Utilizing Sweden as a test country, we investigate how the age-sex distribution and the mortality levels of the digital population extracted from FamiLinx diverge from the registered population. Method: We employ descriptive statistics, logistic regression modeling, and standard life table techniques for our measures of completeness and quality. Results: When one demographic variable is available, researchers can effectively anticipate the availability of other demographic information. The completeness and the quality of the demographic variables within the kinship networks are markedly higher for individuals with more complete and accurate demographic information. Lower mortality levels are observed in populations drawn from FamiLinx, which may be attributed to selectivity bias in favor of individuals experiencing more favorable demographic conditions. However, the representativeness of genealogical populations improved toward the end of the 19th century, especially when selecting individuals with more accurate birth and death dates. Conclusions: FamiLinx offers new opportunities for demographic research, due to its vast amount of individual information from various historical populations and their recorded kinship ties. Nonetheless, missing values and accuracy in its demographic information are selective. This selectivity needs to be addressed. |
| Date: | 2024–01–23 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:62yxm&r=age |