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The health of older adults is crucial for the overall health of the entire life cycle. Based on population sampling survey data and census data from 131 prefecture level units in the Yangtze River Economic Belt (YREB) during 2010–2020, this study used exploratory spatial data analysis, geographical detector, stepwise regression analysis, and GTWR model to analyze the spatiotemporal pattern and influencing factors of the health level of older adults in the YREB. The results show that the health level of older adults in the YREB slightly increased from 2010 to 2020, with the most significant improvement in the upstream region and the most significant decline in the midstream region. The older adults' health level in the YREB displays a gradient decreasing pattern of the downstream, midstream, and upstream regions. The health level of older adults in the YREB is influenced by a combination of natural and social environment factors. Areas with lower altitude and moderate humidity climates are more conducive to the health of older adults. The increase in influencing factors such as population migration rate, per capita GDP, average years of education, per capita housing construction area, per capita park green area, and green coverage rate in built-up areas is conducive to improving the health level of older adults, while lower number of health institutions per 1,000 people and higher household support rate are not conducive to improving the health level of older adults. In addition, over time, the health-promoting effect of natural environmental factors is enhanced from 2010 to 2020, and the influence of annual precipitation on shaping the spatial pattern of older adults' health level became more obvious. Although the promoting effect of population migration on the health level of older adults tends to weaken, it remains the primary factor affecting the spatiotemporal differentiation of older adults' health level in the YREB. The impact of social development on the health level of older adults has changed from a positive health effect (improvement) to a negative health effect (loss). The health-promoting effect of living environment factors is enhanced. The health-inhibitory effect of household support rate increased, and showed a gradient decreasing pattern from downstream to midstream to upstream. The findings of this study can provide a more in-depth understanding of the spatiotemporal pattern of the health level of older adults in the YREB and the factors influencing it, improve the health level of older adults in the region, and promote the development of healthy and active aging in the YREB, and improve the human health. At the same time, this study also supplements the related research on aging and the health level of the elderly. Firstly, it can provide reference for the research on the health of old adults in other countries and regions around the world. Secondly, it can also provide a basis for research on aging and the health of old adults in cities and counties under YREB. [ABSTRACT FROM AUTHOR]

This study utilizes data from A-share listed companies between 2011 and 2020 to empirically investigate the impact and mechanism of public welfare donations on the internal income gap of enterprises. The research findings indicate that public welfare donations significantly increase the per capita salary of management, while their impact on the per capita salary of ordinary employees is not significant, thus leading to an expansion of the internal income gap within enterprises. The results from mechanism testing reveal that the income tax benefits resulting from charitable donations and the rise in corporate operating income have contributed to an increase in excess rent shared by enterprises and employees. Due to a stronger bargaining power, management shares more excess rents, thereby widening the income gap within the enterprise. Heterogeneity analysis demonstrates that public welfare donations have a greater impact on the internal income gap of non-state-owned enterprises; however, limiting executive compensation and enhancing employees' bargaining power can mitigate this widening effect caused by public welfare donations on enterprise's internal income gap. The research value of this study is threefold. Firstly, there is a scarcity of studies on the impact of public welfare donations on the income gap within enterprises, and this study contributes to enriching the research in this area. Secondly, this paper examines the effect of tax incentives for public welfare donations on the internal income gap of enterprises, thereby deepening the research on the impact of tax reduction and fee reduction, as well as expanding our understanding of corporate income tax preferential policies. Thirdly, it offers insights into improving enterprise compensation systems and enhancing corporate governance. Senior executives can potentially allocate more excess rent through their strong bargaining power. If their compensation remains unrestricted, it may lead to a widening internal income gap and negatively affect company operational efficiency. [ABSTRACT FROM AUTHOR]

The relationship between economic growth and CO2 emissions has been analyzed testing the environmental Kuznets curve hypothesis, but traditional econometric methods may be flawed. An alternative method is proposed using segmented-sample regressions and implemented in 164 countries (98.34% of world population) over different periods from 1822 to 2018. Results suggest that while the association between GDP per capita and CO2 emissions per capita is weakening over time, it remains positive globally, with only some high-income countries showing a reversed association in recent years. While 49 countries have decoupled emissions from economic growth, 115 have not. Most African, American, and Asian countries have not decoupled, whereas most European and Oceanians have. These findings highlight the urgency for effective climate policies because decoupling remains unachieved on a global scale, and we are moving away from, rather than approaching, the Paris Agreement goal of limiting temperature increase to 1.5 °C above preindustrial levels. [ABSTRACT FROM AUTHOR]

Innovation can lead to wage inequalities through different channels. This paper explores this relationship, focusing on the direct and spillover (indirect) effects of these channels on personal wage inequalities in Brazilian regions. Product and process innovation are measured by patents and the acquisition of foreign technology through imports of capital goods respectively. Based on data that covers 482 regions from 2003 to 2014, we use the Spatial Durbin Model with spatial fixed effects to control spatial dependence and heterogeneity across regions. The results point to a positive association between our measures of innovation and wage inequalities. However, as we found a non‐linear relationship between imports of capital goods and wage inequality, an increase in imports of capital goods may reduce wage inequality. Other variables may also cause inequality to fall, such as the share of the population with a higher education degree and social skills. Drivers behind an increase in inequality are female participation in the workforce and the level of GDP per capita. [ABSTRACT FROM AUTHOR]

Although China's carbon emission trading schemes (CETS) garnered significant attention in the field of climate mitigation, limited data availability has hindered exploration into the impact of CETS on economic inequality at the county level in China. Given its potential to facilitate industrial upgrading and generate employment opportunities, the adoption of CETS holds promise for reducing economic inequality. To address data limitations, we employed a combination of gridded nighttime light data and land use data to estimate China's county-level Dagum Gini coefficient and its components. Subsequently, we applied a difference-in-difference-in-difference method to examine how CETS affected economic inequalities between and within urban and rural areas in China. Our findings reveal that: (1) CETS significantly reduced overall economic inequality in counties with a high proportion of secondary industry output; (2) this reduction primarily occurred within urban and rural areas rather than between them. Further heterogeneity analysis demonstrates that while CETS effectively mitigated economic inequality between urban and rural areas in central and western regions, it did not achieve similar outcomes in the eastern region; (3) service industry development and rural GDP per capita served as important channels through which CETS reduced economic inequality within rural areas. Infrastructure development driven by CETS primarily addressed economic inequality within urban areas rather than rural areas. Key policy insights: It is confirmed that China's CETS made a significant contribution to mitigating economic inequalities within urban and rural areas. This empirical evidence provides new decision-making support for the future promotion of CETS at the county level. It is recommended to propose higher quotas for service industries in rural areas and allocate a portion of revenue from carbon emission trading markets to promote entrepreneurship among rural residents and support upgrades in the rural industrial structure. Considering that the infrastructure development driven by CETS has predominantly addressed economic inequality within urban areas rather than rural areas, it is imperative to allocate a greater proportion of revenue from CETS towards supporting rural infrastructure construction. [ABSTRACT FROM AUTHOR]

Among major development organizations, the unchallenged consensus is that war and conflict are development issues ravaging local economies, often leading to forced migration, refugee populations, and acute food insecurity. Food insecurity when caused by a rise in food prices is a threat for violent conflict. This study was conducted in Nigeria using three types of quantitative data which are the general household panel data, monthly retailed commodity prices, and violent conflict data from 2010 to 2019. This study examines the linkages between conflict, food price shocks, and food security outcomes of households in Nigeria. Per capita daily calorie intake, household dietary diversity, and per capita monthly food consumption were the three food security outcomes used for this study. Fixed effects panel regression models were used to determine the effects of conflict-induced food price shocks on the food security outcomes of households. I was found that dietary diversity appeared to be higher in the first wave than in the other three waves. The measure of dietary diversity for the post-harvests were slightly higher than the post-plantings. The high dietary diversity associated with the post-harvest periods is partly related to the relatively higher net value of foods consumed during the same season. This is because the amount of food calories consumed during the post-harvest periods are relatively lower than the amount consumed during the post-planting periods. Regardless of the conflict level in Nigeria, an increase in conflict-induced price shock of wheat, and rice is associated with a decline in calorie intake, dietary diversity, and the actual food value consumed. The conflict-induced price shocks of other cereals negatively influence the actual food value consumed, and dietary diversity. It is concluded that violent conflict influences some aspects of food insecurity, through adjustment in diets in response to price increases. Conflict-induced price shocks is a necessary condition for food security. Therefore, policy issues aimed at improving the food security outcomes of households in the face of conflict-induced price shocks should focus on price scheme that will stabilise price placing a price floor on food commodities. [ABSTRACT FROM AUTHOR]

Non-native species can react to changes to their thermal environment by altering their feeding behaviour, thereby potentially causing shifts in predator–prey dynamics and competitive dominance over native species. In this study, we measured intraspecific variation in the functional response (i.e., predation rate as a function of prey density) of the rusty crayfish Faxonius rusticus (Girard, 1852) at two temperatures (18 °C and 26 °C) in the laboratory. We compared six invasive populations spanning a 2° latitudinal gradient in eastern North America to test the prediction that under warmer conditions individuals from more southerly populations exhibit a higher functional response than those from northern populations. Temperature, latitude, and the interaction between these two variables had significant effects on attack rates and handling times of individual crayfish from the tested populations. Contrary to our prediction, the attack rates of individuals from northern populations were consistently higher than those from southern populations at both temperatures. We propose that these interpopulation differences in functional response could arise, at least in part, from countergradient selection. Our results suggest that climate warming promotes spatiotemporal variation in per capita effects across latitudinally distributed populations of aquatic invasive species. [ABSTRACT FROM AUTHOR]

This paper analyzes the persistence of the sovereign debt / GDP and sovereign debt / GDP per capita series for the five largest European economies and the US using fractional integration. We use historical data starting in 1800 for the US and the UK, in 1861 for Italy and in 1880 for Germany, France and Spain. The results indicate high degrees of persistence of debt-to-GDP and debt per capita ratios with clear evidence of no mean reversion in both debt indicators. We also find evidence of correlation with the primary deficit, supporting the idea that one of the causes of this debt persistence is precisely the primary deficit persistence. Empirical results support the need for a better coordination between fiscal and monetary policies to enhance debt control in the countries under examination. [ABSTRACT FROM AUTHOR]

Recent literature revisits cross-country convergence patterns over the last six decades. Whilst the debate has been about unconditional or conditional convergence, we question whether convergence rates differ across countries. Using the same dataset as in the recent studies of Kremer et al. (NBER Macroecon Annu 36:337–412, 2022) and Acemoglu and Molina (NBER Macroecon Annu 36:425–442, 2022) (GDP per capita for 108 countries over 58 years, 1960–2017), we systematically search models where the degree of heterogeneity varies from the mean group, pooled mean group, fixed effects and pooled estimators of convergence. The Bayesian Information Criterion selects the heterogeneous model whether we use the U.S., a common factor or country-specific trends as the steady state. We estimate a multi-country technological catch-up statistical model using the U.S. as the technological frontier. We show empirically that a failure to allow for heterogeneous rates of convergence creates a bias in the convergence coefficient towards zero. The long-run elasticity to the U.S.—another convergence parameter of interest—associates positively (0.79) with the country's average growth. Countries that learn from the technological frontier also grow faster. [ABSTRACT FROM AUTHOR]

Pakistan has struggled for a political system suitable for its postindependence development; however, repeated struggles between democracy and dictatorship have slowed Pakistan's economic growth. I quantified the impact of military dictatorship on Pakistan's economy from 1999 to 2008 using synthetic control methods. I found that while the average annual GDP per capita growth grew during the military dictatorship, it was four times lower than synthetic Pakistan's. I conclude that the military did not help Pakistan with its economic malaise. The increase in military expenditure and the prevalence of terrorism due to the military dictatorship may have hindered Pakistan's economic growth. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Planning Education & Research is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We construct an overlapping generations model in which the government chooses the tax rate that determines publicly provided education and healthcare. Education increases human capital accumulation, and healthcare improves life expectancy. Each policy is financed by taxes. Two sectors of government, the public education and public healthcare sectors, uncooperatively determine the tax rates for education and healthcare that maximize the GDP per capita and an adult's welfare. Our main findings are as follows. First, the optimal tax rates for both branches of government based on per capita GDP maximization are uniquely determined. Second, in the case based on welfare maximization, there are multiple equilibria that can be ranked. The conclusion relies on the strategic complementary relationship between public education and healthcare, and the result is consistent with empirical data. [ABSTRACT FROM AUTHOR]

This paper proposes an asymmetric grouping estimator for forecasting per capita carbon emissions for a country panel. The estimator relies on the observation that a bias‐variance pooling trade‐off in potentially heterogeneous panel data may be different across countries. For a specific country, cross validation is used to determine the optimal country‐specific grouping. A simulated annealing algorithm deals with the combinatorial problem of group selection in large cross sections. A Monte Carlo study shows that in case of heterogenous parameters, the asymmetric grouping estimators outperforms symmetric grouping approaches and forecasting based on individual estimates. Only in the case where the signal is very weak, pooling all countries leads to better forecasting performance. Similar results are found when forecasting carbon emission. The asymmetric grouping estimator leads to more pooling than a symmetric approach. Being on the same continent increases the probability of pooling, and African countries seem to benefit most from using asymmetric grouping and European countries least. [ABSTRACT FROM AUTHOR]

The topic of the research is whether better human capital, as determined by secondary school learning outcomes measured by PISA scores, promotes economic growth. The literature often uses the PISA results as a proxy for growth, while its use and impact on growth are not empirically proven. These questions are analyzed through two hypotheses. The first hypothesis (H1) states that in a worldwide sample of countries, GDP per capita growth between 2006 and 2019 was positively impacted by rising PISA results. The second hypothesis (H2) states that between 2006 and 2019, the rise in PISA scores in East Asia had a stronger influence on economic growth than in the rest of the world. The study examines 59 nations that have administered two PISA tests during the period of 2006–2019. The findings imply that there is generally no causal connection between PISA results and growth and the PISA results play no additional role in the development of East Asian nations. The results can be explained in two ways. The first is that human capital includes more than just skills. The second is that the data only covers a short period of time, which may limit the analysis of long-term patterns. [ABSTRACT FROM AUTHOR]

The Wells–Riley model has been widely used to estimate airborne infection risk, typically from a deterministic point of view (i.e., focusing on the average number of infections) or in terms of a per capita probability of infection. Some of its main limitations relate to considering well‐mixed air, steady‐state concentration of pathogen in the air, a particular amount of time for the indoor interaction, and that all individuals are homogeneous and behave equally. Here, we revisit the Wells–Riley model, providing a mathematical formalism for its stochastic version, where the number of infected individuals follows a Binomial distribution. Then, we extend the Wells–Riley methodology to consider transient behaviours, randomness, and population heterogeneity. In particular, we provide analytical solutions for the number of infections and the per capita probability of infection when: (i) susceptible individuals remain in the room after the infector leaves, (ii) the duration of the indoor interaction is random/unknown, and (iii) infectors have heterogeneous quanta production rates (or the quanta production rate of the infector is random/unknown). We illustrate the applicability of our new formulations through two case studies: infection risk due to an infectious healthcare worker (HCW) visiting a patient, and exposure during lunch for uncertain meal times in different dining settings. Our results highlight that infection risk to a susceptible who remains in the space after the infector leaves can be nonnegligible, and highlight the importance of incorporating uncertainty in the duration of the indoor interaction and the infectivity of the infector when estimating risk. [ABSTRACT FROM AUTHOR]

Geographical indications (GIs) embody distinctive regional elements characterized by widespread spatial distribution, serving as vital agricultural intellectual properties and significant tourism assets. This case study introduces a multiscale and multi-perspective quantification framework for Shandong Province, focusing on spatial agglomeration, association, and heterogeneity. This approach quantitatively explores GIs' spatial patterns and influencing mechanisms, analyzing both at the monomer and regional scales, considering static and dynamic perspectives. Leveraging methods such as kernel density analysis, Moran's I index, Geary's C index, Internet hot word analysis, and Geodetector, the coastal municipalities, prosperous urban areas, and zones with high-quality arable soils were identified as spatial agglomeration areas for GIs. The study revealed a strong correlation between the spatial distribution pattern of socioeconomic factors and GIs' spatial density from a static perspective. However, diminished spatial autocorrelation was observed for GIs' public perception from a dynamic standpoint, indicating a reduced influence of Internet connectivity. The spatial heterogeneity in GIs is determined by multiple interconnected factors, displaying an enhancement effect between any two influencing factors. Among the 15 influencing factors analyzed, urbanization rate; gross value of agricultural, forestry, animal husbandry, and fishery production; and per capita gross domestic product significantly contribute to spatial heterogeneity effects at both urbanization rate, gross value of agriculture, forestry, animal husbandry, fishery production, and per capita gross domestic product significantly contributed to spatial heterogeneity effects at regional and monomer scales. The results suggest that GIs are likely to flourish with regional economic growth. The analytical framework and quantification methods support exploring and sustainably utilizing GIs, improving output quality, and modernizing GIs' production, ultimately contributing to regional agriculture's high-quality and sustainable development. [ABSTRACT FROM AUTHOR]

This study delves into the impact of banking sector development (BSD), renewable energy consumption (REC) and economic growth (EG) on environmental quality (EQ), using the load capacity factor (LCF) in Sudan. Utilizing time series data from 1990 to 2018 and the Autoregressive Distributed Lag (ARDL) method, this research aims to explore both short-term and long-term dynamics, and cointegration, to provide a detailed understanding of these relationships. The study's primary objective is to elucidate the effects of BSD, REC, and EG on Sudan's EQ through the LCF metric and to test the Load Capacity Curve (LCC) hypothesis. The results indicate that the squared values of per capita GDP (long-term) and REC (short- and long-term) contribute to an increase in Sudan's LCF, thereby enhancing EQ,while BSD and per capita GDP negatively affect EQ, thus confirming the LCC hypothesis. Sudan authorities are urged to prioritize environmentally friendly economic policies, sustainable urban development, and the transition to renewable energy sources. However, the revelation that BSD diminishes environmental sustainability suggests a reevaluation of the financial sector's role. Encouraging green technologies could amplify the LCF and mitigate environmental degradation, enabling Sudan to create a sustainable environment by promoting renewable energy investments and long-term GDP per capita growth while curbing financial expansion. This research provides a critical framework for policymakers to create strategies that balance economic development with ecological preservation, ensuring Sudan's long-term sustainability. [ABSTRACT FROM AUTHOR]

Background: High clinical value national reimbursement anticancer medications (NRAMs) are pivotal treatments for patients with cancer. However, the availability of NRAMs in medical institutions is unknown. This study aimed to assess the availability of NRAMs in national and provincial medical institutions. Methods: This cross-sectional study utilized national health insurance data to access the availability of NRAMs in national and provincial medical institutions. Further statistical analyses and visualizations were conducted in terms of medical institution level and daily cost. Using the Spearman's rank correlation test (α = 0.05), we calculated the correlation between the availability rates of NRAMs and their negotiation access time, daily cost, per capita disposable income, provincial gross product, and number of policy releases. Results: Overall, 81 NRAMs, with an average availability rate of approximately 1.01% nationwide, were included. There were significant differences between provinces for each drug, and the availability of NRAMs gradually decreased in tertiary (13.41%), secondary (1.58%), and primary medical institutions (< 0.05%). Differences were also observed in the availability rate of NRAMs in various daily drug cost ranges. Among the factors examined, negotiation access time (r1 = 0.425), daily cost (r2 = − 0.326), per capita disposable income (r3 = 0.645), provincial gross product (r4 = 0.433), and number of policy releases (r5 = 0.461) were all correlated with the availability of NRAMs. Conclusions: The low availability of NRAMs in national and provincial medical institutions indicates that their willingness to equip NRAMs needs to be improved. All factors examined in this study affected the availability of NRAMs. Our findings can guide policymakers in improving relevant policies. [ABSTRACT FROM AUTHOR]

Despite the abundance of research on reducing carbon emissions, there is a significant gap in understanding the influence of macroeconomic factors on carbon dioxide (CO2) emissions from a spatial-structural perspective. This study aims to contribute to the literature by investigating the impact of macroeconomic factors on carbon dioxide emissions in six East African countries between 1989 and 2020. Using spatial econometric panel models, the study analyzed spatial dependence among the variables. The empirical findings indicate that gross domestic product (GDP) per capita and electricity consumption have positive direct and indirect effects on carbon emissions, while fuel prices and exports have negative direct effects, but positive spillover effects on neighboring countries. Imports have a positive impact on local economies, but negative spillover effects. Additionally, the urban population has no significant impact on the environment. These findings provide important policy implications for optimizing spatial growth patterns and achieving a low-carbon economy in East African countries. [ABSTRACT FROM AUTHOR]

This study examines Finland's increasing investment in solar energy as part of its broader strategy to transition to renewable energy sources. Despite its northern location and limited sunlight during winter months, Finland has effectively harnessed solar power, especially during its long summer days. We conducted a PESTLE analysis, highlighting political commitment to climate agreements, economic benefits of solar energy, public support for clean energy, technological advancements, regulatory support, and environmental benefits. In addition, we applied the autoregressive distributed lag model (ARDL) to study the impact of GDP per capita, urbanization (URB), foreign direct investments (FDI), and the share of primary energy consumption from solar (SOL) on C O 2 emissions for Finland during 1990–2022. The long-term findings show that SOL, URB, and FDI negatively impact C O 2 emissions, while GDP positively impacts C O 2 emissions. Solar energy deployment reflects the effectiveness of solar energy as a cleaner alternative to fossil fuels. Urbanization also shows a negative impact on C O 2 emissions due to better infrastructure and more efficient energy use in urban areas. FDI suggests that investments are oriented towards sustainable technologies. Industrial activity associated with economic expansion may indicate the positive effect of GDP in C O 2 emissions. Although economic growth has typically resulted in increased emissions, strategic investments in renewable energy and sustainable urban development can greatly reduce this effect. Policy initiatives in Finland should concentrate on promoting green investments and enhancing urban planning with a focus on environmental sustainability. [ABSTRACT FROM AUTHOR]

Energy policy has a significant impact on the state of the environment and, therefore, on residents' health and life expectancy, especially in highly urbanized areas. Reducing emissions is currently one of the necessary actions that must be taken at the scale of individual countries to ensure sustainable development. The article aims to identify the best ways to shape energy policy by evaluating development scenarios for air protection and their environmental impact. The realization of the goal is based on the data included in three groups: (1) Economic factors, Health factors, and Demographic factors; (2) Clima-e related economic losses, Renewable Energy sources in electricity, heating, and cooling, Premature deaths due to exposure to fine particulate matter (PM2.5), Health impacts of air pollution, Population change; (3) Demographic balance and crude rates at the national level, GDP per capita in purchasing power PPS, GDP, and principal components; covering 36 EU countries in 2019 and 2021. The study proposes an advanced methodology for assessing development strategies by integrating the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Bayesian networks (BN) and incorporating them into a multicriteria decision-making (MCDM) support system. The TOPSIS model based on BN allowed for the illustration of the features of many criteria and the identification of relationships between scenarios, allowing for selecting the best way to develop energy policy. The results showed a 60.39% chance of achieving success in extending the life of residents by five years. At the same time, the most favorable development path was the scenario promoting activities aimed at reducing air pollution by introducing renewable energy sources to produce energy used for lighting and preparing domestic hot water urban areas. By presenting possible scenarios and the probability of success, it is possible to achieve the goal of practical energy policy at the level of the country and individual European cities and also by extending the life of city inhabitants, as presented by the authors in this study. [ABSTRACT FROM AUTHOR]

This paper identifies patterns in total and per capita CO2 emissions among 208 countries considering different emission sources, such as cement, flaring, gas, oil, and coal. This research uses linear and non-linear dimensional reduction techniques, combining K-means clustering with principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE), which allows the identification of distinct emission profiles among nations. This approach allows effective clustering of heterogeneous countries despite the highly dimensional nature of emissions data. The optimal number of clusters is determined using Calinski–Harabasz and Davies–Bouldin scores, of five and six clusters for total and per capita CO2 emissions, respectively. The findings reveal that for total emissions, t-SNE brings together the world's largest economies and emitters, i.e., China, USA, India, and Russia, into a single cluster, while PCA provides clusters with a single country for China, USA, and Russia. Regarding per capita emissions, PCA generates a cluster with only one country, Qatar, due to its significant flaring emissions, as byproduct of the oil industry, and its low population. This study concludes that international collaboration and coherent global policies are crucial for effectively addressing CO2 emissions and developing targeted climate change mitigation strategies. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Economic welfare is essential in the modern economy since it directly reflects the standard of living, distribution of resources, and general social satisfaction, which influences individual and social well-being. This study aims to explore the relationship between national income accounting different attributes and the economic welfare in Pakistan. However, this study used data from 1950 to 2022, and data was downloaded from the World Bank data portal. Regression analysis is used to investigate the relationship between them and is very effective in measuring the relationship between endogenous and exogenous variables. Moreover, generalized methods of movement (GMM) are used as the robustness of the regression. Our results show that foreign direct investment outflow, Gross domestic product growth rate, GDP per capita, higher Interest, market capitalization, and population growth have a significant negative on the unemployment rate, indicating the rise in these factors leads to a decrease in the employment rate in Pakistan. Trade and savings have a significant positive impact on the unemployment rate, indicating the rise in these factors leads to an increase in the unemployment rate for various reasons. Moreover, all the factors of national income accounting have a significant positive relationship with life expectancy, indicating that an increase in these factors leads to an increase in economic welfare and life expectancy due to better health facilities, many resources, and correct economic policies. However, foreign direct investment, inflation rate, lending interest rate, and population growth have significant positive effects on age dependency, indicating these factors increase the age dependency. Moreover, GDP growth and GDP per capita negatively impact age dependency. Similarly, all the national income accounting factors have a significant negative relationship with legal rights that leads to decreased legal rights. Moreover, due to better health facilities and health planning, there is a negative significant relationship between national income accounting attributes and motility rate among children. Our study advocated the implications for the policymakers and the government to make policies for the welfare and increase the social factors. [ABSTRACT FROM AUTHOR]

Using Coefficient of Variation and GIS spatial analysis, we detected the spatial and temporal evolution and development patterns of border trade in Yunnan counties, analyze the de‐ velopment pattern of border trade in depth by combining with the model of border trade develop‐ ment level, and explore the driving mechanism of border trade by using geographic probes. The results show that: ① the overall trend of county border trade in Yunnan Province is on the rise, and the total volume varies unevenly among counties, with Ruili City in the west and Mengla County in the south as the representative counties with higher total trade volume, while the over‐all trade volume in Ximeng County in the southwest and Lushui County in the northwest is smaller. ② From 2010 to 2020, the development pattern of county border trade in Yunnan Prov‐ ince varies. ③ During the same period, the border trade development in the western and south‐ eastern border counties is high and the growth rate is stable; the development in the northwestern and southwestern counties is low and the growth is fast; the development in the southern coun‐ ties is high and the growth is slow. ④ The main driving factors affecting the border trade in the counties factors are policy and transportation factors, and the secondary driver is GDP per capita, while there are differences in the driving factors of border counties with different neighboring countries. [ABSTRACT FROM AUTHOR]

Plant resistance and predators can influence density‐dependent survivorship and growth of herbivores, and their damage to plants. Although the independent effects of plant resistance and predators on herbivores and herbivory are well known, little is known about their interactive and density‐dependent effects on herbivores and the amount and distribution of damage on plants. These relationships are important for understanding how herbivore and plant populations influence each other. We used a laboratory density‐manipulation experiment to determine how plant resistance (three treatments: jasmonate‐insensitive, unmanipulated wild type, and jasmonate‐sprayed wild‐type plants) and predation (two treatments: predator or no predator) affect the survivorship and growth of an herbivore, as well as per capita damage and the distribution of damage on plants. We found evidence that the density dependence of herbivore survivorship was influenced by predators and an interactive effect of plant resistance and predation. Herbivore growth was reduced by higher plant resistance but was not density‐dependent nor affected by predation. Per capita plant damage was reduced by plant resistance, predation, and herbivore density. The within‐plant distribution of damage became more even with increasing herbivore density but was not affected by predation or the independent effect of plant resistance. The distribution of damage was also affected by an interaction between plant resistance and herbivore density; damage became less aggregated with density across all plant resistance treatments, but the decrease was strongest for the jasmonate‐insensitive plants. These results show that predators influence herbivore density dependence, and that plant resistance can affect the impact of predators on herbivores. Though plant resistance, predation, and herbivore density all reduced per capita herbivore damage to plants, only herbivore density and plant resistance affected the distribution of damage. Distributions of herbivory can influence plant success; documenting patterns of herbivory is an under‐appreciated avenue for integrating effects of plant resistance, predators, and herbivore density on plant–herbivore interactions. [ABSTRACT FROM AUTHOR]

Urban underground space (UUS) development has been acknowledged as a positive contribution to urban resilience (UR). Such contribution has been qualitatively addressed in recent years, but only quantitatively discussed in few studies. Quantitative evaluation methods for UR are widely used in China and around the world, but the role of underground space is barely included. This paper provides a way to bridge this gap on the city scale. A UR evaluation framework was carefully constructed that covers the basic aspects and elements of UR. The contributions of UUS to UR were identified and integrated into the UR evaluation framework, and the measurement methods for each indicator related to UUS were determined. A case study of 19 sample cities in China were conducted using the integrated evaluation model. Correlation analysis and clustering analysis were further adopted to interpret the evaluation results, mainly with three indicators reflecting the level of UUS development, namely UUS area (m²), UUS density (104 m² /km² ) and UUS area per capita (m² / person). The results showed a strong correlation between UUS area and UR. The average proportion of UR provided by UUS in the 19 sample cities was 16.46%, while the maximum figure reached 29.20%. The sample cities were clustered into four categories based on the relationship between the proportion of UR provided by UUS, UUS area, and GDP per capita, where both high and low UUS area tend to provide less proportion of resilience than the medium UUS area. Corresponding suggestions for UUS utilization were proposed to assist cities in achieving urban resilience. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Civil Engineering & Architecture is the property of Journal of Beijing University of Civil Engineering & Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Studying changes in land use per capita is critical for understanding the interactions between humans and ecosystems, and for modeling the impacts of land use changes on climate systems. However, many uncertainties in historical estimates significantly hinder climate modeling. This study estimated the per capita cropland area in traditional agricultural regions of China over the past millennium using historical-document-based and modern statistical cropland and population data. The findings showed that changes in the per capita cropland area in the provinces of the middle and lower reaches of the Yellow River could be characterized into three stages: slow decrease, rapid increase, and fluctuating decrease, whereas, in the provinces of the middle and lower reaches of the Yangtze River, there was a continuous decrease. Spatially, the per capita cropland area was higher in the middle and lower reaches of the Yellow River and lower in the middle and lower reaches of the Yangtze River during the study period. The per capita cropland areas showed clear differences in the HYDE dataset and our study; the corresponding values of our study were 2.1–8.0, 1.7–8.2, and 1.6–8.8 times higher than those from the HYDE dataset for the early Song, Yuan, and Ming dynasties, respectively. [ABSTRACT FROM AUTHOR]

Income is a relevant factor for explaining outbound tourism demand. However, when working with regional- or country-level data, it is difficult to disentangle the role of income in stimulating tourism travelling from other factors that correlate with greater income levels. This paper exploits a natural experiment from Spanish Christmas Lottery to estimate the causal effect of income shocks on outbound tourism. We leverage the staggered and quasi-random assignment of lottery winnings across Spanish regions to estimate the elasticity of outbound annual trips and expenditure to windfall gains. Using difference-in-differences with the amount of lottery prizes as an indicator of treatment intensity, we show that lottery winnings per capita increase both the annual number of tourism trips and expenditure per capita. This effect operates during the first 2 years following the draw, which is likely explained by bandwagon and income multiplier effects. [ABSTRACT FROM AUTHOR]

The objective of this study was to establish the relationship between certain institutional variables and the effectiveness of fiscal decentralisation in Latin America. To fulfil this objective, we took a sample of 15 Latin American countries for the years 1996 to 2020 to estimate the logarithm of GDP per capita based on the level of fiscal decentralisation, as well as its interaction with six institutional variables plus three control variables. The results show that institutional variables always modulate the effects of fiscal decentralisation, in most cases significantly and negatively, the exceptions being accountability with a positive result and government effectiveness with a non-significant result. It was concluded that in the presence of weak regulations, political conflicts, and corruption, fiscal decentralisation can worsen social or economic circumstances in Latin America. [ABSTRACT FROM AUTHOR]

The article explores the relationship between population dynamics, economic growth, and planetary boundaries. It emphasizes the impact of population size, consumption, and resource intensity on the environment. While consumption growth is the main driver of environmental impact, population growth indirectly contributes as well. The United Nations' stance on population growth and its connection to environmental harm is also discussed. The article concludes that reducing population size and focusing on welfare rather than economic growth is necessary to address the environmental crisis. Additionally, the article examines the different mortality transitions in China and India, with China's population starting to decline and India's population still growing. The need to address the healthcare needs of India's growing older population is highlighted. The global issue of population aging is also discussed, with the proportion of people over 65 expected to increase by 2050. The challenges and concerns of population aging for high-income countries are addressed, and potential solutions such as pronatalist policies and immigration are debated. The article suggests that the growthist paradigm, which prioritizes economic growth, may need to be reevaluated in light of social and environmental problems. [Extracted from the article]

This note examines evidence of non-fundamentalness in the rate of variation of annual per capita capital stock for OECD countries in the period 1955–2020. Leeper et al. (2013) proposed a theoretical model in which, due to agents performing fiscal foresight, this economic series could exhibit a non-fundamental behavior (in particular, a non-invertible moving average component), which has important implications for modeling and forecasting. Using the methodology proposed in Velasco and Lobato (2018), which delivers consistent estimators of the autoregressive and moving average parameters without imposing fundamentalness assumptions, we empirically examine whether the capital data are better represented with an invertible or a non-invertible moving average model. We find strong evidence in favor of the non-invertible representation since for the countries that present significant innovation asymmetry, the selected model is predominantly non-invertible. [ABSTRACT FROM AUTHOR]

Although several studies examine the convergence of per capita carbon dioxide (CO2) at the country level, research at the regional level is scarce except in countries like China and the USA. This study bridges this research gap by considering India's regional-level CO2 emissions convergence. In particular, this study proposes to undercover the convergence patterns of carbon emissions towards designing effective carbon reduction policies in the future at the regional level in India. Addressing this research is vital since this question is closely allied with fairness in the distribution of per capita emissions. In order to achieve the stated objective, this study first computes per capita CO2 emissions. Then, it uses the convergence notion to analyse the CO2 emissions in the case of 16 Indian states from 2003–04 to 2018–19. By employing Phillips and Sul's clustering procedure, this study supports the presence of overall divergence when all 16 Indian states are considered as a group. This suggests that all states together are not forming a single steady state rather, they are forming multiple steady (or club convergence) due to heterogeneity in per capita CO2 emissions. Moreover, 16 states cluster into three clubs which have distinct transition paths. From the policy perspective, it is important for the government of India to target reducing per capita CO2 emissions by focusing on clusters of states in a phase-wise manner. [ABSTRACT FROM AUTHOR]

This study addresses the relationship between education-job mismatch and aggregate labor market performance in a cross-country setting. We examine the effect of education-job mismatch on aggregate productivity across 15 countries using data from the OECD Survey of Adult Skills (PIAAC). We measure mismatch levels and compute their incidence across countries. Next, the paper develops a model linking mismatch to aggregate productivity. In the model the allocation of labor across the types of mismatch is derived from the endogenous process. The findings show that reducing mismatch results in increases in output per capita. This provides evidence for an important role of the allocation of workers according to jobs that match their fields of study and qualification levels not only for individual earnings but also for aggregate outcomes. [ABSTRACT FROM AUTHOR]

A key question in economic history is the degree to which preindustrial economies could generate sustained increases in per capita productivity. Previous studies suggest that, in many preindustrial contexts, growth was primarily a consequence of agglomeration. Here, we examine evidence for three different socioeconomic rates that are available from the archaeological record for Roman Britain. We find that all three measures show increasing returns to scale with settlement population, with a common elasticity that is consistent with the expectation from settlement scaling theory. We also identify a pattern of increase in baseline rates, similar to that observed in contemporary societies, suggesting that this economy did generate modest levels of per capita productivity growth over a four-century period. Last, we suggest that the observed growth is attributable to changes in transportation costs and to institutions and technologies related to socioeconomic interchange. These findings reinforce the view that differences between ancient and contemporary economies are more a matter of degree than kind. [ABSTRACT FROM AUTHOR]

Objective Methods Results Conclusion This study mainly focuses on the relationship between development aid and growth as well as examines the role of the institutional development levels of countries in this relationship and makes economic inferences.The analysis is conducted for 64 countries receiving official development assistance in the 2000–2020 period. To provide robust estimates in these studies, the Driscoll and Kraay estimator is used after fixed and random effects models.In almost all of the estimated models, a significant relationship between official development assistance per capita and growth is found. Moreover, the models with institutional factors and interaction terms also support the results. According to the robust estimation results, official development assistance per capita positively affects growth.The results for all countries do not mean that good policies and strong institutions are unnecessary. In contrast, they show that the priority is the sum of aid per capita. [ABSTRACT FROM AUTHOR]

In recent years, policymakers and researchers have shown increased interest in subjective well-being across countries. While previous research primarily focused on country averages, measuring the distribution of subjective well-being through standard deviation has become more frequent. This article introduces a new approach to assess subjective well-being: focusing on the "worst off," or the group with the lowest levels of well-being. Based on several ethical and political theories, this measure is deemed the most relevant when assessing well-being levels in society. The study constructs new measures of low subjective well-being (the bottom 10%) to evaluate differences across countries, changes over time, and associations with economic growth, using data from 33 European countries from 2002 to 2018. The findings indicate significant variations in well-being for the worst off across countries, with improvements observed in almost all countries studied, particularly in Poland, Germany, and the Czech Republic. Improvements are generally larger for the worst off compared to the general population. Furthermore, both GDP per capita and financial satisfaction are positively associated with the subjective well-being of the worst off, both over time and when countries are compared cross-sectionally. The implications of these findings for future research and benchmarking quality of life are discussed. [ABSTRACT FROM AUTHOR]

In this paper, we aim to identify the covariates associated with the proportion of votes of candidates elected in Brazilian municipalities with a population of more than 300,000 inhabitants. We analyzed the vote proportions from the 2018 presidential runoff election using distributions within the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) class. Unit distributions are quite useful for modeling vote proportions due to their flexibility to accommodate asymmetry and heavy tails. Furthermore, they provide adequate representations of the physiological properties and the empirical distribution of the data. We fit the beta, simplex, unit gamma, and unit Lindley regression models, considering random and fixed effects components to verify spatial correlation among the municipalities. The beta regression with fixed components regarding Brazilian regions is superior. The covariates with significant effects are the proportion of evangelicals, monthly household income per capita, the political spectrum of the governors' party elected in 2014 and 2018, and if the municipality is the capital of the state. We note that some Brazilian regions impact the vote proportions' mean and dispersion. [ABSTRACT FROM AUTHOR]

The purpose of this study is to determine the factors that influence deaths in road accidents in India. The study uses panel econometric methodologies such as the fixed effects model, random effects model, and Hausman–Taylor instrumental variable technique to achieve this goal. Unobserved heterogeneity between states/union territories (UTs) and time is accounted for by time-fixed and state-fixed effects. Based on the panel data set from Indian states/UTs for the period 2004–2018, the study confirms previous results that motorisation, population, urbanisation and income level are all potential contributors to road accidents and fatalities. It also shows that spending on health care and law enforcement appears to help the Indian states minimise mortality in road traffic accidents. On the one hand, spending on health care facilities can provide health-related assistance to persons who have been involved in traffic accidents; on the other hand, spending on police increases the enforcement of rules, resulting in a reduction in traffic accidents. Thus, to lessen the economic and financial cost of road accidents in the country, the government should focus on boosting both per capita health expenditure and per capita police expenditure. JEL Codes: C23, C26, H51, I18, L92, O18, R41, R42 [ABSTRACT FROM AUTHOR]

This study examines the influence of demographic changes on India's economic growth from 1999 to 2019, emphasizing the impact of the rising working-age population on state domestic product per capita and sectoral value-added. While the overall influence of the working-age population ratio and core working-age proportions on per capita economic growth is limited, a higher proportion of high-skilled workers and urban residents positively affects per capita output. Furthermore, our analysis highlights sector-specific effects, with particular significance observed in the industry sector, where the influence of the working-age population is most pronounced. [ABSTRACT FROM AUTHOR]

Copyright of Mexican Journal of Economics & Finance / Revista Mexicana de Economia y Finanzas is the property of Instituto Mexicano de Ejecutivos de Finanzas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study uses a bioeconomic regional computable general equilibrium (CGE) model to assess the economic and welfare effects on a sub-national region of transitioning from regulated open access to rationalization for a mackerel fishery in a region (Busan), Korea. Results from the baseline simulation demonstrate that the resource rent from the fishery increases, but that the aggregate and per capita welfares in the region can deteriorate due to an out-migration of the factors of production. However, sensitivity analyses reveal that the sign and size of the aggregate and per capita welfare changes depend on, among other things, (i) regional factor mobility, (ii) the ratio of the initial level of biomass to the carrying capacity, and (iii) the magnitude of the rationalization-induced enhancement in the fishing efficiency. [ABSTRACT FROM AUTHOR]

We use district-level data from India to study the implications of two historical institutions, direct British rule and the heterogeneous land tenure institutions implemented by the British, on the disparity in present-day development in India. Using night-lights per capita as a proxy for district-level per capita income, we find that modern districts that were historically under direct British rule had significantly fewer night-lights per capita in 1993 relative to modern districts that were historically under indirect British rule. The large gap persists even after including correlates of development such as educational attainment, health, and physical and financial infrastructure. Looking at the growth pattern from 1993 to 2013, directly ruled districts had a lower annual growth rate compared with that of indirectly ruled districts. Much of the development gap between areas under indirect rule and areas under direct rule can be accounted for by the adverse effect of landlord-based revenue-collection systems in the directly ruled areas. [ABSTRACT FROM AUTHOR]

How much green space is available for individuals is a major question that city planners are generally interested in, and the present study aimed to address this issue in the context of Vellore, India, through two approaches, namely, the per capita and the geographical area approach. In existing studies, urban green space (UGS) was only calculated at the macro level, i.e., for the city as a whole. Micro-or ward-level analysis was not attempted before, and the present study carried out the same to get a clear picture of the amount of greenery available in each ward of a city. For this purpose, a two-step approach was proposed where the histograms of Google Earth (GE) images were analyzed first to check whether the green cover types such as trees, shrubs/grassland, and cropland were spectrally different. Then, classification techniques such as ISODATA, maximum likelihood, support vector machine (SVM), and objectbased methods were applied to the GE images. It was found that SVM performed well in extracting different green cover types with the highest overall accuracy of 93% and Kappa coefficient of 0.881. It was found that when considering the city as a whole, the amount of UGS available is 42% of the total area, which is more than the recommended range of 20-40%. Similarly, the available UGS per person is 97.84 m2, which is far above the recommended 12 m2/person. However, the micro-level analysis revealed that some of the wards have not satisfied the criteria of per capita and percentage area, though the city as a whole has satisfied both the criteria. Thus, the results indicate the importance of calculating the urban green space availability at the ward level rather than the city level as the former gives a closer look at the surplus and deficit areas. The results of terrestrial LiDAR survey at individual tree level revealed that if trees are located adjacent to buildings or roads, it results in fewer heat islands compared to the case where there are no trees. [ABSTRACT FROM AUTHOR]

"Backway" is the Gambian term for the outflow of people, mostly via the Mediterranean and oceanic routes that during the 2010s turned the country into one of the highest per capita origin points for sub-Saharan migrants in Europe. From the standpoint of Kerewan, a Gambian rural community proud of its migratory legacy, a mobility rules perspective uncovers the specificity of the "backway" in sensible arenas of village life: household and family networks, intergenerational relationships, and development. Since 2017, initiatives linked to the Euro-African mobility regime to immobilize young Gambians meet the practical rationality on the ground of communities like Kerewan engaged in a moral conversation about what family, village, intergenerational and transnational solidarity, and development should and do mean in the current predicament. [ABSTRACT FROM AUTHOR]