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.
Whether an aging China is increasingly losing its low-cost export advantages? More importantly, which type of inputs' dynamics occurs to adapt to the above-mentioned circumstance? Using an ...instrumental-variable strategy, our empirical analysis finds that population aging leads to a contraction in China's export share since it causes a shortage of middle-aged workers and thereby higher labor cost. We also show that population aging leads to a substitution of labor with capital, but does not promote technology level in the context of China. Moreover, we document that the substitution of labor with capital occurs mainly in the firms with high productivity, large scale, high capital intensity, low credit constraint, high export intensity and private firms.
•Using an instrumental-variable strategy, we estimate the impact of population aging.•Population aging, causing a higher labor cost, leads to a contraction in China's export share.•Population aging leads to a substitution of labor with capital but does not promote technology level in the context of China.•A further firm-level analysis shows that the substitution of labor with capital has firm heterogeneity.
Population aging is a conspicuous demographic trend shaping the world profoundly. Walking is a critical travel mode and physical activity for older adults. As such, there is a need to determine the ...factors influencing the walking behavior of older people in the era of population aging. Streetscape greenery is an easily perceived built-environment attribute and can promote walking behavior, but it has received insufficient attention. More importantly, the non-linear effects of streetscape greenery on the walking behavior of older adults have not been examined. We therefore use readily available Google Street View imagery and a fully convolutional neural network to evaluate human-scale, eye-level streetscape greenery. Using data from the Hong Kong Travel Characteristic Survey, we adopt a machine learning technique, namely random forest modeling, to scrutinize the non-linear effects of streetscape greenery on the walking propensity of older adults. The results show that streetscape greenery has a positive effect on walking propensity within a certain range, but outside the range, the positive association no longer holds. The non-linear associations of other built-environment attributes are also examined.
Renewable energy is one of the key clean production pathways to achieve the global energy transition and combat climate change. This research is aimed to investigate the impact of changes in social ...structure, economic structure, demographic structure, and trade structure on per capita renewable energy consumption. Four threshold panel regression models are developed using the updated data of 116 countries. In these models, social structure, economic structure, demographic structure, and trade structure are set as both explanatory variables and threshold variables, whereas per capita renewable energy consumption is set as the explained variable. These models verify the existence of the threshold (1% confidence level), which indicates that there is a non-linear relationship between social-, economic-, demographic- and trade-structure changes and renewable energy consumption. Changes in the social structure (urbanization level) promote per capita renewable energy consumption, and when it crosses the threshold, this promotion effect become more significant. Changes in the economic structure (industrialization level) inhibits the growth of per capita renewable energy consumption. However, as industrialization level rises above the threshold, this inhibition is weakening. Changes in the demographic structure (population aging) and trade structure (trade openness) contributes to the growth of per capita renewable energy consumption. Moreover, after the demographic structure and trade structure cross the threshold value, this promotion strengthened. The above findings provide theoretical support for policymakers to formulate energy and population policies.
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•Explanatory variables are also threshold variables in these four panel threshold models.•Social structural change (urbanization level) contributes to renewable energy consumption.•The early stage of industrialization is not conducive to the development of renewable energy.•Aging of population contributes renewable energy consumption.•Free trade benefits to the renewable energy development.
Japan and Germany are at the vanguard of a new population dynamics in developed countries: population decline in the absence of war, famine and pandemics. This book presents an in-depth overview of ...the social and economic implications of this development.
A neutral interest rate is a key indicator of the monetary policy stance. This study estimates South Korea’s neutral interest rates and their determinants. Based on the results, we investigate the ...prior monetary policy patterns of the Bank of Korea (BOK) and evaluate its stance. We adopted a time-series model approach, with a Bayesian econometric strategy. We can summarize the empirical findings as follows. First, the neutral interest rate has continued to fall, and it tends to fall sharply during downturns, such as the global financial crisis and COVID-19 pandemic. Second, the fall over the past two decades is largely attributable to population aging and the neutral US interest rate. Meanwhile, the recent rebound in the neutral interest rate seems to be due to the increase in the net issuance of government bonds. Finally, the BOK responded substantially to aggregate demand shocks over recent decades. In particular, the BOK’s current monetary policy stance is contractionary because of its active response to inflation rather than real activity.
Carbon emissions and population aging have risen as two major challenges of the sustainable development of human society. This study explores the nonlinear effects of population aging on carbon ...emission by developing a panel threshold regression (PTR) model, using data from 2002 to 2012 of 137 countries or regions. In the PTR model, carbon emission is the explained variable, whereas population aging is the threshold variable; industrial structure and urbanization are the explanatory variables; and level of economic development, trade freedom, population size, and financial level are the four control variables. With the increase in population aging, the correlation between industrial structure and carbon emissions in the high-income, upper-middle-income, low-income groups are positive, negative, and inverted “U” shaped, respectively. Moreover, with the increase in population aging, the correlations between urbanization and carbon emissions in the high-income group is inverted “U” shaped, whereas the correlation in upper-middle-, lower-middle-, and low-income- groups is nonlinear and positive.
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•The effects of different aging lever on carbon emissions are explored.•The Panel Threshold Regression is devloped with the panel data of 137 countries.•Industrial structure and urbanization contribute carbon emissions with aging as the threshold.•Different income groups have different effects.
Urbanization and population aging are key indicators of human-related social attributes. With economic progress and urban development, human living conditions and the level of medical and health care ...have been continuously improved. Population aging has become a global trend, which brings serious challenges to the world. Environmental sustainability is closely linked to both urbanization and aging. Most of the existing studies only focus on the linear relationship between urbanization and the environment, and the effect of aging on the ecological environment is also controversial. It is of great significance to conduct systematic research on urbanization-aging-environment. This paper aims to reconstruct the linear relationship between urbanization and the environment, investigating the nonlinear effect of population aging on the nexus of urbanization-environment in 156 countries. This paper focuses on exploring ways to improve environmental quality from the perspective of population aging. To this end, the panel threshold regression models of urbanization‑carbon emissions and urbanization-ecological footprint are developed respectively. In which, urbanization is set as the explanatory variable, carbon emissions and ecological footprint are set as the explained variables, and population aging is set as the threshold variable. This paper divides four income groups according to the income standard of the World Bank, and regresses the panel data of the global and four income groups respectively to reflect the comprehensiveness of this work. The results show that there is a threshold effect of population aging on the nexus of urbanization‑carbon emissions/ecological footprint both the global scale and different income groups. On a global scale, urbanization has a positive effect on carbon emissions and ecological footprint. When aging crosses the threshold in turn, the promotion effect of urbanization on carbon emissions gradually becomes smaller, and the influence coefficient of urbanization on the ecological footprint shows an inverted U-shaped change trend. Aging can reduce the environmental pressures related to urbanization. There is heterogeneity in the nonlinear regression results for different income groups. Population aging variable in high income group, upper middle income group helps to improve environmental quality. In lower middle income countries and low income countries, aging slightly increases the coefficients of urbanization and ecological footprint.
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•Develop aging-urbanization-environment panel threshold regression models.•Nonlinear nexus of aging on urbanization-carbon emissions/ecological footprint.•Urbanization has a positive effect on carbon emissions and ecological footprint.•Aging can reduce the environmental pressures related to urbanization.•There is heterogeneity in the regression results for different income groups.
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