Fertility and mortality decline are major drivers of Iran’s population aging. A rapid and sharp fall in fertility rates over the past three decades as well as a substantial rise in life expectancy ...are causing rapid aging of Iran’s population. The present paper uses the 2015 United Nations Population Division data to discuss the trends, determinants and the implications of population aging in Iran. According to the medium fertility variant, people age 60 and older will represent 31% (almost 29 million people) of Iran’s population by 2050. The population age 65 and older is projected to be 22% (more than 20 million) and that of aged 80 and older 3.8% (around 3.5 million) in 2050, that are almost four-times higher than the corresponding figures in 2015. Data on the speed of population aging show that Iran is the second fastest aging country in the world in terms of the percentage point increase in the population age 60 and over between 2015 and 2050; Iran is second only to South Korea, by less than .01%. The rapid population aging of Iran has significant implications for all societal institutions and decision makers that have to be addressed by the Iranian society. Gender-related issues and socio-economic security in old age are two key issues resulting from such a fast population aging. As with many rapidly aging populations, Iran needs a strategy for social and economic supports for an aging population that will not promote views of aging people as a burden.
This study examines the impact of population aging on labor investment efficiency in Chinese listed firms from 2009 to 2020. Our main findings reveal that aging can positively influence labor ...investment efficiency, particularly in firms with labor redundancies such as state-owned enterprises, those with labor unions, high labor costs, and financial constraints. The positive effect is lessened in regions with abundant human capital, within the manufacturing sector, and labor-intensive industries. The results show that improvements in labor efficiency are distinct from changes in capital investment efficiency, indicating no general rebalancing of resources due to demographic shifts. Firms with limited investment opportunities and under strict external monitoring benefit more from an aging workforce. Overall, our findings suggest that an aging population can offer opportunities for firms to enhance labor investment efficiency, challenging the conventional view of population aging as solely a threat.
•There is a positive effect of population aging on labor investment efficiency.•This effect is stronger in state-owned enterprises and companies with labor unions and higher hiring costs.•There are two underlying mechanisms involved, ie, a firm's reduced labor redundancy and optimized decisions on employment.
Population ageing is an increasingly severe global issue. And this has been posing challenges for public health policies and medical resource allocation There are various features of population ...ageing in different regions worldwide.
All data were obtained from the health data of World Bank Open Data. Quantile linear regression was used to subtly measure the common variation tendency and strength of the global ageing rate and ageing population. The Bayesian space-time hierarchy model (BSTHM) was employed to assess the detailed spatial temporal evolution of ageing rate and ageing population in global 195 countries and regions.
Annual growth of the ageing (65 and above) rate occurred on six continents: Europe (0.1532%), Oceania (0.0873%), Asia (0.0834%), South America (0.0723%), North America (0.0673%) and Africa (0.0069%). The coefficient of variation of the global ageing rate increased from 0.54 in 1960 to 0.69 in 2017. The global ageing rate and ageing population increased over this period, correlating positively with their quantiles. Most countries (37/39) in Europe belong to the top level with regard to the ageing rate, including the countries with the greatest degree of ageing-Sweden, Germany, Austria, Belgium and the UK-whose spatial relative risks of ageing are 3.180 (3.113-3.214), 3.071 (3.018-3.122), 2.951 (2.903-3.001), 2.932 (2.880-2.984) and 2.917 (2.869-2.967), respectively. Worldwide, 44 low ageing areas which were distributed mainly in Africa (26 areas) and Asia (15 areas) experienced a decreasing trend of ageing rates. The local trends of ageing population in the 195 areas increased.
The differentiation of global population ageing is becoming increasingly serious. Globally, all 195 areas showed an increasing local ageing trend in absolute terms, although there were 44 low-ageing areas that experienced a decreasing local trend of ageing rate. The statistical results may provide some baseline reference for developing public health policies in various countries or regions, especially in less-developed areas.
Both economic globalization and population aging have given rise to changes in environmental quality, but the research that integrates these two crucial factors into the same environment policy ...framework is still a blank. Therefore, using panel data of the Organization for Economic Cooperation and Development (OECD) over the period 1971–2016, this study examines the long-term impact of economic globalization and population aging on CO2 emissions. First, second-generation panel regression approaches are employed to verify the panel data, including unit root tests, cointegration tests and causality tests. Next, Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) are respectively used for empirical analysis of the long-term impact between variables. The augmented mean group (AMG) is also applied to ascertain the robustness results of the estimation coefficients. Finally, using Dumitrescu and Hurlin non-causality test to examine the causal associations between variables to avoid the contingency of the results. The overall results show that economic globalization and population aging decrease the long-term CO2 emissions. The inverted U-shaped relationship between economic growth and environmental pollution confirms the effectiveness of the Environmental Kuznets Curve (EKC) in OECD countries. In addition, unidirectional causal relationships have been found from economic globalization and population aging to CO2 emissions in this study. Policy suggestions in response to these findings are discussed.
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•The effects of economic globalization and aging on CO2 emissions are explored.•Economic globalization and aging improve environmental quality.•Causal relationships between the variables of interest are verified.•Policy suggestions for promoting sustainable goals and mitigating climate change
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•Examined the impact of aging and renewable energy budget on CO2 emission.•Advanced panel data estimation techniques are employed for the G7 countries.•Aging and renewable energy ...budgets promote environmental sustainability.•Aging affects renewable energy budgets by increasing health expenditures.•Policy recommendations for G7 on environmental sustainability are presented.
From the last few centuries, the human population has grown exponentially around the globe, and an increase in affluence has increased resource usage and pollutant emissions. In this respect, investment in renewable energy technologies plays an essential role in fighting against climate change and helps to achieve carbon neutrality targets. However, the pace of population aging is also increasing dramatically, which may require more health expenditures that may affect the renewable energy budgets. In this context, this study investigates the linkage between population aging, health expenditures, renewable energy budgets and carbon dioxide (CO2) emissions in G7 (Group of Seven) countries from 1985 to 2019. The second-generation estimation techniques robust to cross-sectional dependence and slope heterogeneity are used. The findings of Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) depict that population aging and renewable energy budgets enhance the environmental quality of G7 countries by decreasing CO2 emissions. In contrast, health expenditures and economic growth attenuate environmental sustainability. The finding of CS-ARDL is also confirmed by the Augmented Mean Group (AMG) method. The Dumitrescu and Hurlin causality test outcomes indicate the unidirectional causality from population aging and renewable energy to CO2 emissions. There is a feedback effect between health spending, economic growth, and CO2 emissions. Another interesting discovery is that population aging leads to health expenditures and consequently affects renewable energy budgets. We also find that population aging can affect renewable energy budgets directly. In addition, this paper also reveals a bidirectional causal relationship between health expenditures and renewable energy budgets. Finally, drawing on these consequences, this paper proffers some policy recommendations to help G7 countries to achieve climate-related goals.
•Estimates of PM2.5 concentrations in 2030 declined compared with 2015.•If the age structure maintains, PM2.5-related premature death in 2030 related to 2015 decreased.•With the population aging, ...PM2.5-related premature death would sharply increase in 2030.
Fine particulate matter (PM2.5) pollution is one of the most critical environmental and public health problems in China and has caused an enormous disease burden, especially long-term PM2.5 exposure. Global climate change represents another environmental challenge in the coming decades and is also an essential factor affecting PM2.5 pollution. Moreover, China has an aging population with a changing population size and falling age-standardized mortality rates. However, little evidence exists evaluating the potential impacts from climate change and population aging on the long-term PM2.5 exposure-related disease burden. This study quantifies the impacts of climate and population changes on changes in the disease burden attributed to long-term PM2.5 exposure from 2015 to 2030 in mainland China, which could add evidence for the revision of relevant environmental standards and health policies.
This modeling study investigated long-term PM2.5 exposure-related mortality across China based on PM2.5 projections under Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) and population scenarios from shared socioeconomic pathways (SSPs). PM2.5 concentrations were simulated by the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) modeling systems. In addition, three types of population projections in 2030 relative to 2015 were set up as follows: (i) the population remained the same as that in 2015; (ii) the population size changed under SSPs, but the age structure remained the same; (iii) both the population size and age structure changed under SSPs. The global exposure mortality model (GEMM) was adopted to estimate PM2.5-related premature deaths.
Ambient PM2.5 concentrations decreased from 2015 to 2030 under the two climate and emission scenarios. Estimates of related premature mortality in 2030 declined compared with that in 2015 due to lower PM2.5 concentrations (RCP4.5: −16.8%; RCP8.5: −16.4%). If the age structure of the population remained unchanged and the population size changed under SSPs, the nonaccidental premature mortality also showed a decrease ranging from −18.6% to −14.9%. When both population size and age structure changed under SSPs, the population in China would become older. Nonaccidental premature mortality would sharply increase by 35.7–52.3% (with a net increase of 666–977 thousand) in 2030.
The PM2.5 pollution in 2030 under both RCP4.5 and RCP8.5 would slightly improve. The population sizes in 2030 projected by SSPs are relatively stable compared with that in 2015. However, the modest decrease due to air pollution improvement and stable population size would be offset by population aging.
Abstract
Background
China is one of the world’s fastest-aging countries. Population aging and social-economic development show close relations. This study aims to illustrate the spatial-temporal ...distribution and movement of gravity centers of population aging and social-economic factors and thier spatial interaction across the provinces in China.
Methods
Factors of elderly population rate (EPR), elderly dependency ratio (EDR), per capita gross regional product (GRP
pc
), and urban population rate (UPR) were collected. Distribution patterns were detected by using global spatial autocorrelation, Kernel density estimation, and coefficient of variation. Further, Arc GIS software was used to find the gravity centers and their movement trends yearly from 2002 to 2018. The spatial interaction between the variables was investigated based on bivariate spatial autocorrelation analysis.
Results
The results showed a larger variety of global spatial autocorrelation indexed by Moran’s
I
and stable trends of dispersion degree without obvious convergence in EPR and EDR. Furthermore, the gravity centers of the proportion of EPR and EDR moved northeastward. In contrast, the economic and urbanization factors showed a southwestward movement, which exhibited an reverse trend compared to population aging indicators. Moreover, the movement rates of EPR and EDR (15.12 and 18.75 km/year, respectively) were higher than that of GRP
pc
(13.79 km/year) and UPR (6.89 km/year) annually during the study period. Further, the bivariate spatial autocorrelation variation is in line with the movement trends of gravity centers which showed a polarization trend of population aging and social-economic factors that the difference between southwest and northeast directions and exhibited a tendency to expand in China.
Conclusions
In sum, our findings revealed the difference in spatio-temporal distribution and variation between population aging and social-economic factors in China. It further indicates that the opposite movements of gravity centers and the change of the BiLISA in space which may result in the increase of the economic burden of the elderly care in northern China. Hence, future development policy should focus on the social-economic growth and distribution of old-aged supporting resources, especially in northern China.
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