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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]

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]

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]

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]

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 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 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]

Some governments distribute profits from state-owned enterprises to citizens on a per capita basis while others do not. Does the use of per capita payments affect how governments trade off pro-economy policies with other constituent interests such as environmental quality and public health? We study that question in the context of tribal government decisions to close or keep open casinos on American Indian reservations during the COVID-19 pandemic. Relying on per capita payment data and administrative information on the operational status of over 200 tribal casinos, we investigate how the distribution of per capita payments relates to the number of days casinos were closed from February 2020 through February 2022. After controlling for casino size at the onset of COVID-19, as well as demographic, economic, and geographic characteristics of the reservations on which the casinos operate, we find that casinos governed by per capita payments remained open about 17–29% longer than other reservation-based casinos. That finding suggests that per capita payments create a pro-economy constituency and implies that the decision to pay dividends directly to citizens affects the sizes of revenues from state-owned enterprises, such as tribal-government-owned casinos, rather than merely determining how they are distributed. [ABSTRACT FROM AUTHOR]

The article explores the causal effect of local climate conditions on household consumption in South Africa. The climatic conditions are represented by monthly average temperature and precipitation. The study utilises the nationally representative 2017 National Income Dynamics Study (NIDS), wave 5 data and 2017 Climate Research Unit (CRU) climate data. The parsimonious quantile regression shows that climatic conditions (precipitation, temperature, wet days, and cloud cover) impact household per capita consumption. The quadratic quantile regression model analysis shows that household per capita consumption is convex in precipitation. Below the turning point, increased precipitation is associated with decreased household per capita consumption. Above the turning point, increased precipitation is related to increased household per capita consumption. Regions that receive very low precipitation or experience extreme temperatures (very cold or very hot) require tailor-made interventions to alleviate consumption. When we control for household characteristics, the impact of climatic conditions on household per capita consumption is weak. Providing inclusive development policies and programmes can mitigate the impact of climatic conditions on household per capita consumption. [ABSTRACT FROM AUTHOR]

This study delves into the dynamics shaping happiness levels in Indonesia before and during the COVID-19 pandemic, specifically emphasizing gender and residence-type disparities. Using data from the 2017 and 2021 Happiness Level Measurement Survey, it offers insights into how different population segments were affected. The analysis employs a multilevel mixed-effects ordered logistic model, considering individuals nested within provinces, and measures pandemic severity using positive COVID-19 cases per 100,000 residents. This study evaluates pandemic-related happiness shifts using nationwide cross-sectional survey data from two timeframes. It derives substantial statistical strength from data involving 137,000+ respondents gathered through comprehensive face-to-face interviews. It mitigates recall bias by capturing happiness at two distinct time points, avoiding retrospective measures. The study examines and validates four research questions. First, higher COVID-19 cases in provinces correlate with lower happiness. Second, though women were happier than men, the pandemic reduced this gender-based gap. Third, urban residents were generally happier than rural residents, but the pandemic narrowed this difference. All the estimates exhibit statistical significance at the 1 percent level. Finally, while provincial poverty showed minimal happiness impact, a negative association between unequal per capita expenditure and happiness emerged, providing partial backing for investigating the role of macroeconomic conditions. This study reveals that the COVID-19 pandemic altered happiness dynamics in Indonesia, narrowing gender and residence-based gaps. It also emphasizes the role of socioeconomic factors, particularly unequal per capita expenditure, in influencing individual happiness, highlighting implications for targeted policy interventions. [ABSTRACT FROM AUTHOR]

Exponentially increasing amounts of copper mined over the last 120 years and Cu's central place in modern society raise concerns about its long-term availability. Estimates of copper production from mines made here based on projected population (R2 = 0.95) are lower than many previous studies. Projected world production of copper from mines in 2100 of 28.2 million tons Cu is approximately 34% more than 2021 production. Rough estimates of recycled Cu added to mine production are less than previous estimates of future consumed Cu. Although annual mined copper will peak in about 2086, production will continue in a gentle decline through 2100. Future availability of consumed copper is dependent on availability of mined copper plus recycled copper. Estimated total copper demand including new technologies is 33 million tons in 2040. Total expected copper from mines estimated here is 24 million tons in 2040, but with a recycling rate of 30%, required demand of 33 million tons would be satisfied. Per capita GDP effects on copper consumption require a logistic growth curve to model. In countries with high per capita GDP, per capita copper consumption is likely to reach saturation and stabilize or perhaps reduce demand for copper. Most countries will achieve high incomes at some point. If earlier studies of high-income copper consumption rates hold in the future, 10 kg per capita of copper for 10 billion people expected before 2100 leads to estimated total annual copper consumption of 100 million tons. This worst-case demand estimate greatly exceeds projected copper from mines and recycling and ignores increased demand due to electrification scenarios and declines in demand due to declining population by 2100 and possible dematerialization. [ABSTRACT FROM AUTHOR]

This study analyses the impact of GDP per capita, domestic credit, savings, and population on the environment in Pakistan from 1995 to 2019. The country has consistently been ranked eighth, fifth, and eight as an environmentally vulnerable nation from 1998 to 2017, 1999 to 2018, and 2000 to 2019, respectively. Therefore, the study explores the role of environmental awareness as a potential strategy for making peace with nature. Findings of the ARDL bounds testing approach confirm the long-run cointegration among variables of concern. In further assessment, the study determines that increased per capita income is detrimental to environmental quality in the long run. However, in the short run, it shows a favourable impact. On the other hand, domestic credit worsens the environment in the long and short runs. However, savings are positively insignificant in this regard. Furthermore, the total population significantly harms the environment in the long and short run. Fortunately, environmental awareness has emerged as a key solution to environmental degradation in Pakistan. Findings show that an increase in the dissemination of environmental awareness through the Internet, mobile, and landline phones, as well as by increasing education expenditures, mitigates the populations' detrimental impact on the environment and improves environmental quality in the long run. [ABSTRACT FROM AUTHOR]

This study predicted that the relationship between income and life satisfaction would be stronger for individuals with lower eudaimonic (psychosocial) well-being and weaker for individuals with higher eudaimonic well-being. A sample of 151,874 individuals from 141 countries was used to test this hypothesis. The results of Bayesian multilevel modeling showed that, as expected, per capita household income and subjective satisfaction with income were more strongly associated with life satisfaction among individuals with lower (versus higher) eudaimonic well-being. Individuals with high levels of eudaimonic well-being tend to attach less importance to materialistic and extrinsic values and have more psychological resources (e.g., meaning in life and social support) to cope with difficulties in life and are therefore likely to be less dependent on money when evaluating their lives. [ABSTRACT FROM AUTHOR]

Currently, extensive empirical studies exist on the impact of financial inclusion on socio-economic outcomes such as economic growth, inequality, and poverty. However, research on financial inclusion and population health is limited and still at the infant stage. Therefore, this article adds to knowledge by inquiring into the health implications of financial inclusion using a global panel dataset for 121 countries between 2004 and 2020. After accounting for endogeneity with heteroskedasticity-based instrumental variable regression and cross-sectional dependency with the Driscol–Kraay estimator, we documented that financial inclusion improves population health outcomes. We found that the effect of financial inclusion on population health outcomes also depends on the level of information and communication technology penetration and existing socio-economic conditions in a country. Following this, we showed that financial inclusion improves population health outcomes in countries with lower income inequality and higher GDP per capita, mobile and internet penetration. We further found heterogeneity in the results across geographical regions and income groups. Following these findings, we suggest that financial inclusion policies could enhance population health. [ABSTRACT FROM AUTHOR]

Using panel data from Luxembourg, we investigate the relationship between young individuals' perceived coping with the COVID-19 pandemic context and subjective well-being during the short and mid-term phases of the pandemic (i.e., a few months after its outbreak in July 2020 and one year later in July 2021). Additionally, the study examines how this relationship evolves depending on youths' subjective social status. Luxembourg is an important setting, as it is one of the happiest countries in the world, with the highest GDP per capita. According to our results, perceived coping with the COVID-19 context matters for subjective well-being beyond individual and macro characteristics. We found a strong correlation between perceptions of coping with the COVID-19 pandemic context and subjective well-being in high-social-status individuals and a weaker correlation for low- and middle-social-status individuals. Furthermore, the relationship between perceptions of coping with the pandemic and well-being was stable over time. The article stipulates several reasons for these results, such as a 'comfort conditioning' response to the pandemic for young high-social-status individuals. [ABSTRACT FROM AUTHOR]

This research investigates the effects of tourism, GDP per capita, renewable energy, energy intensity, urbanization, and population on the environment in 40 Asian countries. Data from 1995 to 2019 are used in this analysis. Slope heterogeneity (SH), cross-sectional dependency (CSD), and the combination of level and first differenced stationary are all addressed using a new cross-sectionally autoregressive distributed lag (CS-ARDL) model in this work. Using Westerlund's cointegration method, these variables can be connected throughout time. To validate the findings, both augmented mean groups (AMG) and Common correlated effect mean groups (CCEMG) were utilized. The study results indicate that tourism helps slow the degradation of the natural environment. CO2 emissions increase as a result of variables such as population growth, energy use, and economic development. Only tourism and renewable energy can help cut CO2 emissions. As a consequence, CS-ARDL results are supported by results from AMG and CCEMG tests. Policymakers may be encouraged countries to adopt renewable energy and foster the expansion of the sustainable tourism industry. [ABSTRACT FROM AUTHOR]

Ecosystems provide a wide range of services crucial for human well-being and decision-making processes at various levels. This study analyzed the major land cover types of north-central Ethiopia and their impact on total and per-capita ecosystem service value (ESV). The ESV was estimated using the benefit-transfer method along the established global and local coefficient values for the periods 1973, 1986, 2001, 2016, and 2024. The findings show that agricultural lands continued to expand at a rate of 563.4 ha year−1, at the expense of forests and grasslands. As a result, the total ESV of the study area declined from $101.4 to $61.03 million and $60.08–$43.69 million, respectively. The ESV per capita was also diminished by $152.4 (37.7%) and $257 (40.6%), respectively. However, land-cover improvement during the period 2001–2016 enhanced the total and per capita ESV in the study area. Therefore, potential future research may be required to develop a valid approach for assessing the robustness and sensitivity of value coefficients for the valuation of the ESV at the landscape level. [ABSTRACT FROM AUTHOR]

Research over the past three decades has provided rich empirical evidence for the inverted U-shaped EKC theory, but current problems facing advancing climate mitigation actions require us to re-examine the shape of global EKC rigorously. This paper examined the N-shaped EKC in a panel of 214 countries with 12 traditional and emerging variables, including institutions and risks, information and communication technology (ICT), artificial intelligence(AI), resource and energy use, and selected social factors. The two-dimensional Tapio decoupling model based on N-shaped EKC to group homogeneous countries is developed to explore the inter-group heterogeneous carbon emission effects of each variable. Global research results show that the linear and cubic terms of GDP per capita are significantly positive, while the quadratic term is significantly negative, regardless of whether additional variables are added. This means the robust existence of an N-shaped EKC. Geopolitical risk, ICT, and food security are confirmed to positively impact per capita carbon emissions, while the impact of composite risk, institutional quality, digital economy, energy transition, and population aging are significantly negative. The impact of AI, natural resource rents, trade openness, and income inequality are insignificant. The inflection points of the N-shaped EKC considering all additional variables are 45.08 and 73.44 thousand US dollars, respectively. Combining the turning points and the calculated decoupling coefficients, all countries are categorized into six groups based on the two-dimensional decoupling model. The subsequent group regression results show heterogeneity in the direction and magnitude of the carbon emission impacts of most variables. Finally, differentiated carbon emission reduction strategies for countries in six two-dimensional decoupling stages are proposed. [ABSTRACT FROM AUTHOR]

In the grey prediction, the GM(1, 1) model is an important type, but it sometimes shows big prediction errors. To improve the prediction precision of GM(1, 1) model, the paper makes improvements from the following three aspects: (1) to improve the data's adaptability to the model, the paper transforms the accumulated generating sequence of original time sequence; (2) to make the model meet the variation characteristics of data, the paper extends the grey action of traditional GM(1, 1) model; (3) to avoid big average simulation or prediction relative error of model, the paper considers the minimum of the maximum of the two errors as the optimization objective function. The new extended grey model is called the GM(1, 1, exp × sin, exp × cos) model. The paper uses an improved particle swarm optimization (PSO) algorithm for the parameter optimization of GM(1, 1, exp × sin, exp × cos) model and thus improves the model's convergence rate and precision. According to the model and method proposed, the paper builds a GM(1, 1, exp × sin, exp × cos) model for China's GDP per capita. Results show that the model has high precision. [ABSTRACT FROM AUTHOR]

The immigrant population has grown dramatically in the US in the last 50 years. This study estimates housing demand among immigrants and discusses how immigration may be altering the structure of the US urban areas. Immigrants are found to consume less housing per capita than native-born US residents. [ABSTRACT FROM AUTHOR]

Treating waste as a resource can provide many social and economic benefits and develop policies accordingly. In this study, the relationship between municipal waste, income, human capital, material footprint, consumption and urban population is analyzed with panel data models within the framework of the Kuznets curve, using the data for the period of 1995 – 2018 for 22 OECD countries. Various economic, demographic and human variables that are thought to have an impact on municipal waste generation were added to the models created with cubic functional forms. The analysis results show that the relationship between municipal waste and income is inverted N-shaped. In line with expectations, the increase in human capital reduces the amount of waste per capita. The urbanization rate causes a higher increase in the amount of waste per capita compared to the population. Real consumption per capita and material footprint similarly have a positive effect on waste. The findings have calculated the first and second-order conditions for an inverted N-shaped relationship and verified that this relationship is mathematically valid. [ABSTRACT FROM AUTHOR]

In this paper we aim to propose a new method for improving the design effect of household surveys based on a two-stage design in which the first stage clusters, or Primary Selection Units (PSUs), are stratified along administrative boundaries. Improvement of the design effect can result in more precise survey estimates (smaller standard errors and confidence intervals) or in the reduction of the necessary sample size, i.e. a reduction in the budget needed for a survey. The proposed method is based on the availability of a previously conducted poverty maps, i.e. spatial descriptions of the distribution of per capita consumption expenditures, that are finely disaggregated in small geographic units, such as cities, municipalities, districts or other administrative partitions of a country that are directly linked to PSUs. Such information is then used to select PSUs with systematic sampling by introducing further implicit stratification in the survey design, so as to maximise the improvement of the design effect. Since per capita consumption expenditures estimated at PSU level from the poverty mapping are affected by (small) standard errors, in the paper we also perform a simulation study in order to take into account this addition variability. [ABSTRACT FROM AUTHOR]

Businesspeople and politicians seem to be afraid that population reduction will be accompanied by economic recession. In this paper we examine the experience of some countries of various sizes in which population has been declining and observe how GDP, GDP per capita, unemployment rate, and labour force participation rate are evolving during the period that population is declining. Using the pooled mean group (PMG) estimation method, we find that population decline can go hand in hand with growing GDP and increasing per capita GDP, and at the same time the labour participation rate may increase and unemployment may fall. [ABSTRACT FROM AUTHOR]

During the late 1800s and early 1900s, Argentina was among the ten richest economies in terms of gross domestic product per capita with the United States being the leading economy most of the time. However, Argentina grew less and was less stable than the United States in a period of over 140 years (1875–2018). Structural breaks (1935 and 1975) were identified in the declining ratio of Argentina's gross domestic product per capita long-term trend to that of the United States, as well as in the long-term per capita growth rates of Argentina (1911 and 1975) and the United States (1935). The declining ratio partly reflects that growth in the United States accelerated after 1935 (during the post-1930 Great Depression recovery and the Second World War years) while it decelerated in Argentina after 1975 (in the context of large government deficits, high inflation, the first oil crisis, and the Latin American debt crisis). A Bayesian estimation model suggests that long-term growth was generally higher and less volatile in the United States than in Argentina, with relatively low spillovers from one country to the other. [ABSTRACT FROM AUTHOR]

Transport energy use contributes to pollution, so it generates negative externalities. This paper analyzes the effect of urbanization on the transport final energy consumption in African countries. To that end, the paper applies the panel threshold regression (PTR) model for a panel of 25 African countries over the period 1992–2017. The findings show that there is a significant positive relationship between total and per capita transport energy consumption and the share of the urban population in the total population. Thus, urbanization fosters transport energy consumption, either per capita energy consumption or total energy consumption. Therefore, the results from this study suggest that African countries should promote sustainable urbanization in terms of transportation. [ABSTRACT FROM AUTHOR]

Dietary methylmercury (MeHg) exposure increases the risk of many human diseases. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is the world's most populous bay area and people there might suffer a high risk of dietary MeHg exposure. However, there lacks a time-series high spatial resolution dataset for dietary MeHg exposure in the GBA. This study constructs a high spatial resolution (1 km × 1 km) dataset for dietary MeHg exposure in the GBA during 2009–2019. It first constructs the dietary MeHg exposure inventory for each county/district of the GBA, based on MeHg concentrations of foods (i.e., rice and fish in this study) and per capita rice and fish intake. Subsequently, this study spatializes the dietary MeHg exposure inventory at 1 km × 1 km scale, using gridded data for food consumption expenditure as the proxy. This dataset can describe the spatially explicit hotspots, distribution patterns, and variation trend of dietary MeHg exposure in the GBA. This dataset can support spatially explicit evaluation of MeHg-related health risks in the GBA. [ABSTRACT FROM AUTHOR]

This paper contributes to the debate on the evolution of living standards in preindustrial England. It emphasizes the need to depart from the approach of focusing only on the time paths of observables, like income per capita and population size, in order to assess the validity of Malthusian predictions. It first constructs a Malthusian model and then develops a robust algorithm for identifying the latent forces that have shaped aggregate outcomes in the preindustrial era. The analysis suggests the existence of two distinct Malthusian regimes in preindustrial England: a survival-driven regime, where mortality is the main latent force in economic-demographic interactions, and a later technology-driven regime that emerges after the mid-fifteenth century and is characterized by both population and productivity growth but stable mortality and long-run stagnation in per capita income. The paper discusses the role of various historical accidents (e.g., the Black Death, the discovery of the New World, the English Reformation) in triggering the emergence of the technology-driven regime, and it also highlights some mediating mechanisms through which subsequent productivity growth may have been sustained. The existence of long-run stagnation in income per capita in England through the mid-seventeenth century, despite the technological dynamism of the early modern period, is consistent with the predictions of Unified Growth Theory. [ABSTRACT FROM AUTHOR]

We propose a new set of indices to capture the multidimensionality of a country's institutional setting. Our indices are obtained by employing a dimension reduction approach on the institutional variables provided by the Fraser Institute (2018). We estimate the impact that institutions have on the level and the growth rate of per capita GDP, using a large sample of countries over the period 1980–2015. To identify the causal effect of our institutional indices on a country's GDP we employ the Generalized Propensity Score method. Institutions matter especially in low- and middle-income countries, and not all institutions are alike for economic development. We also document non-linearities in the causal effects that different institutions have on growth and the presence of threshold effects. [ABSTRACT FROM AUTHOR]

This paper studies regional income convergence and its conditioning factors across 81 provinces of Turkey over the 2007–2019 period. Through the lens of a nonlinear dynamic factor model, we first test the hypothesis that all provinces would eventually converge to a common long-run equilibrium. We reject this hypothesis and find that the provincial dynamics of income per capita are characterized by 6 convergence clubs. Next, we evaluate the conditioning factors behind club formation. Our results suggest that spatial dependence across provinces plays an essential role in the formation of convergence clubs. The spatial distribution of the convergence clubs has a clear spatial pattern, and the dynamics of the provincial income distribution are spatially integrated. We also find that geographical neighbors are more important for middle and high-income provinces. Finally, we show that the performance of geographical neighbors affects the probability of club membership through spillovers in capital accumulation and structural change. [ABSTRACT FROM AUTHOR]

Rural populations are particularly exposed to increasing weather variability, notably through agriculture. In this paper, we exploit longitudinal data for Turkish provinces from 2008 to 2018 together with precipitation records over more than 30 years to quantify how variability in a standardized precipitation index (SPI) affects out-migration as an adaptation mechanism. Doing so, we document the role of three potential causal channels: per capita income, agricultural output, and local conflicts. Our results show that negative SPI shocks (droughts) are associated with higher out-migration in rural provinces. A mediated-moderator approach further suggests that changes in per capita income account for more than one quarter of the direct effect of droughts on out-migration, whereas agricultural output is only relevant for provinces in the upper quartile of crop production. Finally, we find evidence that local conflict fatalities increase with drought and trigger out-migration, although this channel is distinct from the direct effect of SPI shocks on out-migration. [ABSTRACT FROM AUTHOR]

This study aims to investigate whether higher equity in government social protection spending strongly predicts positive changes in income poverty and inequality. Our approach was to regress the measures of absolute poverty and inequality on the indicators of equity in social protection spending at the country level, controlling for the level of spending and the country wealth measured by per capita GDP. For that purpose, we have compiled a dataset of 535 observations from 101 countries over years 1998–2017, including 199 observations for 70 low- and middle-income countries from Europe, Asia, North and South America, and Africa. Our findings support the proposition that equity in social spending (measured by the share of social protection spending going to the bottom quintile) is a significant and strong predictor of improved distributional outcomes (poverty measured at Int$1.90 a day and inequality measured by the Gini index). Moreover, in low- and middle-income countries in our sample the poverty and inequality reducing impact of this equity measure is stronger than in the sample including all countries. The presence of a significant gap in equity of social protection spending between the high-income countries and the rest of countries included in the study signifies that there is a large potential in improving equity in social protection spending in low- and middle-income countries. Social protection reforms in these countries should be focused on extending the coverage of social protection programs and improving access to social protection for the poorest segments of the population. [ABSTRACT FROM AUTHOR]

Traditional villages are repositories for preserving human artifacts and cultural heritage. An investigation of the spatial distribution characteristics and factors influencing traditional villages in provincial administrative regions can provide new insights regarding the protection of traditional villages and rural development. This study focused on 275 traditional villages in Henan Province. Using ArcGIS and GeoDa software, we analysed the spatial autocorrelation and heterogeneity of the nearest neighbour index, Gini coefficient, Moran's I, and kernel density of the villages. Additionally, in conjunction with the Python sklearn library and GeoDetector, 15 indicators were selected to construct a decision tree model, spatial lag regression model, and geographic detector. Then the influence and interaction mechanisms of each indicator were analysed. The results revealed that (1) the spatial distribution of traditional villages in Henan Province was clustered and uneven, with a spatial layout comprising "3 high-density areas + 1 medium-density belt"; (2) overall, the number of traditional villages was negatively correlated with altitude, slope, rainfall, population density, proportion of the minority population, and historical-cultural intensity; and (3) the decision tree model results demonstrated that the selected 15 indicators had good predictive ability and that population density was particularly important. The spatial lag regression model results showed that the spatial distribution of traditional villages was positively correlated with distance from rivers, urbanization rate, and tourism resources, and negatively correlated with population density, per capita GRP, historical-cultural intensity, and NDVI. (4) The GeoDetector results indicated that historical-cultural intensity and population density were the two factors with the most significant explanatory power for the spatial differentiation of traditional villages in Henan Province. In terms of interactive factors, population density ∩ population was the strongest interactive driving force, followed by population ∩ historical-cultural intensity. [ABSTRACT FROM AUTHOR]

As declining state and federal aid forces regional governments to become more self-reliant, there is new interest in understanding factors that support regional resilience to economic and natural disasters. Using a sample of 365 metropolitan statistical areas, we examine one such factor: how regional government fragmentation shapes patented innovation, a known mechanism for bolstering resilience. While we find no evidence that the number of general-purpose governments (per capita) impact regional innovation, we do find that regions with a higher density of special-purpose governments have less inclusive innovation. This is true in terms both of who does the inventing and what is invented. Previous research links higher numbers of special-purpose government units to weaker economic performance; our results suggest higher numbers may also hinder regions' abilities to adapt to disruptions. [ABSTRACT FROM AUTHOR]

Population aging, economic globalization, and economic growth simultaneously cause changes in environmental quality, but so far no studies have integrated these key factors into the same environmental policy framework. Thus, this study uses the more robust Westerlund cointegration test and the augmented mean group (AMG) estimator (robust to cross-sectional dependence (CD), heterogeneity, and endogeneity) to estimate the long-term relationship between population aging, economic globalization, economic growth, and per capita carbon emissions in East Asian countries during the period 1975–2018. The analysis results reflect that population aging significantly reduces the long-term per capita carbon emissions of specific East Asian countries. However, energy generation and economic globalization make significant contributions to long-run per capita carbon emissions. Moreover, the impact of economic growth on long-term per capita carbon emissions is significantly positive, while the impact of square of economic growth on long-run per capita carbon emissions is significantly negative, thus validating the inverted U-shaped environmental Kuznets curve (EKC) hypothesis for specific East Asian countries. The results of the causality test indicated a two-way causality between energy generation and per capita carbon dioxide emission, supporting the feedback hypothesis. There is also a two-way causal relationship between aging population and per capita carbon dioxide emission. Policy recommendations are discussed in response to the empirical findings of this study. [ABSTRACT FROM AUTHOR]

Climate change in context of environmental issues is pushing most of the countries to set the goals in order to achieve carbon neutrality and sustainable development. The recognition of Sustainable Development Goal (SDG) thirteen (13) is aided by the objective of this study which is to take an urgent action to combat climate change. In this context, this study investigates the effect of technological progress, income, and foreign direct investment on carbon dioxide emission by taking into consideration the moderating effect of economic freedom in 165 global countries from 2000 to 2020. The study employed ordinary least squares (OLS), fixed effects (FE), and two-step system generalized method of moments for analysis. The findings reveal that economic freedom, income per capita, foreign direct investment, and industry increase carbon dioxide emission while technological progress reduces emission in global countries. Surprisingly, economic freedom indirectly increases the level of carbon emissions by technological progress; however, economic freedom indirectly decreases the level of carbon emissions by income per capita. In this regard, this study favors clean eco-friendly technologies and seeks methods for development without harming the environment. Furthermore, the findings of this study have considerable policy suggestions for the sample countries. [ABSTRACT FROM AUTHOR]

Despite the growing literature on subjective well-being (SWB), few studies have focused on developing countries. Applying robust OLS and ordered probit models to the India Human Development Survey panel data in 2005 and 2012, we empirically assess SWB changes in 2005–2012, based on a self-reported measure of changes in economic well-being, as a function of household and state covariates in 2005. This is in sharp contrast with earlier studies' focus on the levels of SWB. Another point of departure of our study is to compare the covariates of SWB changes with those of objective well-being (OWB) changes, proxied by the relative growth in real per capita household consumption expenditure between 2005 and 2012, to identify specific micro-level correlates of SWB changes. Households with an older and educated head in a larger household, located in urban areas or affluent states in 2005 tend to experience improvement in both SWB and OWB between 2005 and 2012. In contrast, households with a female household head, with more male members in the labour market, with regular access to mass media, without members suffering from non-communicable diseases or disabilities are more likely to be better off subjectively without experiencing the corresponding improvement in OWB. The policy challenges raise serious concerns. [ABSTRACT FROM AUTHOR]

This paper takes the panel data of 283 prefecture-level cities in China from 2011 to 2020 as the research sample, measures the comprehensive index of industrial structure optimization and air quality by using GRA-TOPSIS comprehensive evaluation method, explores the spatial and temporal divergence characteristics of industrial structure optimization and air quality and the spatial and temporal evolution pattern of coupled and coordinated development by using ArcGIS spatial analysis and coupled coordination degree model, and analyzes the driving factors of coupled coordination degree of industrial structure optimization and air quality by combining multi-scale geographically weighted regression model. The study found the following: (1) The overall level of China's urban industrial structure is low, and shows an obvious eastern > central > western decreasing trend; urban air quality has a strong spatial clustering and spatial locking effect. (2) During the study period, the coupling coordination degree of industrial structure optimization and air quality showed an inverted "W" shape fluctuation from 2011 to 2020. The coupling degree and coupling coordination degree in 2020 were both higher than that in 2011, and most cities were in the run-in stage and moderate coordination stage. (3) There is a consistency in the temporal evolution trend and spatial evolution pattern of industrial structure optimization and air quality coupling degree and coupling coordination degree. (4) The driving factors are ranked according to the scale of action: public transportation intensity > population density > government intervention > GDP per capita > industrialization level. At present, China is in a critical period of promoting high-quality development by ecological civilization, and it is recommended to optimize regional industrial structure, improve urban air quality, and promote coordinated urban development. [ABSTRACT FROM AUTHOR]

Research on the impact of foreign direct investment (FDI) on environmental quality has not reached consensus. This paper examines the potential structural break in the relationship between FDI and the environment from the perspective of economic scale. The results of the panel threshold estimation for 67 countries of different income groups show that the impact of FDI on carbon emissions shifts from positive to negative at different income level stages, using GDP as the threshold. This conclusion is further verified by the group regression results of the robustness test. When the GDP per capita is below $541.87, FDI shows a significant positive impact on carbon emissions, and this interval corresponds to a wide range of low-income economies today, however, when the GDP per capita exceeds $541.87, this positive impact almost disappears. The negative impact of FDI on carbon emissions manifests itself once the GDP per capita reaches $46515, and the sample countries corresponding to this interval since 2014 are mainly Switzerland, Iceland, Denmark, Sweden, the United States, Singapore, and Australia. Therefore, we call on countries to raise their income levels so that they can cross the lower threshold and thus take advantage of the emission reduction effect provided by FDI. [ABSTRACT FROM AUTHOR]

We experimentally investigate the impact of information disclosure on managing common harms that are caused jointly by a group of liable agents. Subjects interact in a public bad setting and must choose ex ante how much to contribute in order to reduce the probability of causing a common damage. If a damage occurs, subjects bear a part of the loss according to the liability-sharing rule in force. We consider two existing rules: a per capita rule and a proportional rule. Our aim is to analyze the relative impact of information disclosure under each rule. We show that information disclosure increases contributions only under a per capita rule. This result challenges the classical results regarding the positive effects of information disclosure, since we show that this impact may depend upon the legal context. We also show that while a proportional rule leads to higher contributions than a per capita one, the positive effect of disclosure on a per capita rule makes it as efficient as a proportional rule without information disclosure. [ABSTRACT FROM AUTHOR]

This research explores theoretically, empirically, and quantitatively the role of age diversity in determining aggregate productivity and output. Age diversity has two conflicting effects on output. On the one hand, due to the complementarity between education and experience, age diversity may be beneficial. On the other hand, rapid skill-biased technological change makes age diversity costly as up-to-date education tends to be concentrated among younger cohorts. To study this trade-off, I first build an overlapping-generations (OLG) model which, in view of these two opposing forces, predicts a hump-shaped relationship between age diversity and GDP per capita. This prediction is established analytically, and also quantitatively using real-world population data in an extended computational version of the model. The prediction is then tested using country-level panel data with a novel instrument and regional data from Europe. Moving one standard deviation closer to the optimal level of age diversity is associated with a 1.5% increase in GDP per capita. [ABSTRACT FROM AUTHOR]

We analyze how rising labor costs contribute to economic restructuring in China. In a panel of prefectural cities and industries, spanning the years 1999-2007, we employ instrumental variables to identify the effect of increasing local wage levels. We find adverse effects on performance of (low-skilled) labor intensive industries in China's advanced regions. Consistent with cost-saving industry relocation, such industries expand in other locations, where wages are comparatively low. Comparing locations where such industries expand to those where they do not, we find that both economic complexity and subsequent per capita income increased faster in the former group. [ABSTRACT FROM AUTHOR]

Every country intends to enhance national production by achieving sustainable development. The purpose of this study is to examine whether there exists any long-run association among environmental deterioration measured by territorial emissions in CO2, demographic factors (total population, population density, and urban population) and some other variables, namely, energy use, per capita income, energy intensity, and industrial value added for the 16 countries from the Middle East and North African (MENA) over 1990–2018. We implemented the generalized method of moments (GMM), fully modified ordinary least square (FMOLS), robust least square estimators, and panel Granger causality techniques for estimation. The empirical estimates reveal that there exists a long run cointegration among the series. Results also exhibit that energy use, per capita income, energy intensity, industrial value added, population density, total population, and urban population have positive effects on CO2 emissions. Furthermore, in each panel, there is bi-directional causality between population density and CO2 emissions, total population and CO2 emissions, and urban population and CO2 emissions. These findings suggest that the policymakers need not exclusively to focus on the transformation of rural labor from an agricultural-based model to urban regions with powerful, dominant industry and services sectors but also related to the changing of rural establishments into urban spaces is required. These changes in demographics involve changes in the demand for additional transportation services, food, shelter, clothing, and other necessities. [ABSTRACT FROM AUTHOR]

We develop a novel global perspective of the complexity of the relationships between three COVID-19 datasets, the standardised per-capita growth rate of COVID-19 cases and deaths, and the Oxford Coronavirus Government Response Tracker COVID-19 Stringency Index (CSI) which is a measure describing a country's stringency of lockdown policies. We use a state-of-the-art heterogeneous intrinsic dimension estimator implemented as a Bayesian mixture model, called Hidalgo. Our findings suggest that these highly popular COVID-19 statistics may project onto two low-dimensional manifolds without significant information loss, suggesting that COVID-19 data dynamics are generated from a latent mechanism characterised by a few important variables. The low dimensionality imply a strong dependency among the standardised growth rates of cases and deaths per capita and the CSI for countries over 2020–2021. Importantly, we identify spatial autocorrelation in the intrinsic dimension distribution worldwide. The results show how high-income countries are more prone to lie on low-dimensional manifolds, likely arising from aging populations, comorbidities, and increased per capita mortality burden from COVID-19. Finally, the temporal stratification of the dataset allows the examination of the intrinsic dimension at a more granular level throughout the pandemic. [ABSTRACT FROM AUTHOR]

While previous studies have emphasised several important factors associated with the spread of COVID-19 and strategies to reduce transmission, few studies have focused on the social and cultural factors that may influence its spread. This study analyses the spread of COVID-19 from a cross-country/region cultural perspective and finds that countries and regions with a collectivistic, Confucian or tight (restrictive) culture experience a lower spread rate of COVID-19. The results are robust to controlling for several factors, including population, age structure, gross domestic product (GDP) per capita, previous SARS occurrence, smoking prevalence, and religion. A one standard deviation increase in the collectivism score is associated with a 1.38% reduction of the weekly growth rate of COVID-19 cases. More importantly, the effect of culture on the spread of COVID-19 becomes stronger during national or regional lockdowns. Corroborating these main results, supporting analyses find a significant effect of culture on national and regional COVID-19 death rates. These findings suggest that to manage the ongoing surges in COVID-19 outbreaks, governments should implement public health policies that emphasise the ideas of common interest, personal responsibility and strong cultural norms, and sense of community, as this pandemic has revealed that people all live together in a small global village. Why did Korea, Japan & Taiwan have so few deaths? I see face-covering and the Confucian idea of common good as key. –Michael Levitt, the Nobel Prize Laureate (2020) [ABSTRACT FROM AUTHOR]

As a country with one of the highest per capita gambling losses per year in the world, and an evolving multicultural profile, Australia has become an important setting in which to examine the harms and benefits related to gambling. The Australian population includes people from East Asian cultural backgrounds who are a key demographic of interest for gambling operators planning to grow revenue. However, Australian gambling research has concentrated primarily on those belonging to the dominant cultural group. Most of the previous and limited number of studies to examine gambling among culturally and linguistically diverse (CALD) residents have focused on people of Chinese descent, and much of the literature is now becoming relatively old. This review examines the current evidence around cultural variations in gambling prevalence, motivations, beliefs, behaviours, and help service utilisation, focusing on gamblers with an East Asian cultural background. Numerous domains in which gambling motivations and behaviours vary across cultural groups are identified, and methodological considerations related to ethnographic gambling research are discussed. This review found that while barriers and predictors to help-seeking for CALD gamblers have been studied extensively, contemporary evidence of help service utilisation and effectiveness in Australia is lacking. Further research providing an accurate assessment of the impacts of gambling for CALD gamblers is needed to ensure that harm minimisation resources are effective for those most vulnerable to harm. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to identify the impact of prominent drivers on drug expenditure for diabetes. Method: Following the examination of previous studies, this study identified possible factors contributing to diabetes pharmaceutical expenditures. The explanatory variables for the study were the median population age, access to innovative drugs, GDP per capita, prevalence, price, and consumption of diabetes drugs. Then, to estimate the per capita expenditure among diabetic patients, this study developed the panel data model and two time-series regression models for OECD countries and Iran, respectively. Results: In the panel data regression model, R2 was 0.43. The influence of the age, prevalence, consumption volume and GDP per capita coefficients were + 1.79, + 0.704, + 3.86057, + 0.00054, respectively. Also, the probability level of all variables was less than 0.05. In Iran's comparative time-series regression model, R2 was 0.9, and the only significant influence coefficient was the age (β=+0.91). In the another model for Iran, R2 was 0.99, the influence coefficient of age was + 0.249, the prevalence was + 0.131, innovation was + 0.029, and the price was + 0.00054; all the probability levels were less than 0.05. Conclusion: Pharmaceutical per capita expenditure is affected by several factors. These factors are not the same in various counties. Passing a judgment on drug utilization only based on pharmaceutical per capita expenditure cannot be perfect. Also, judging whether the per capita drug expenditure in one country is desirable without attention to the affecting factors and only relying on the value of utilized medicines is defective. [ABSTRACT FROM AUTHOR]

This paper redefines the connotation of China's human development in the context of the new development concept and high-quality development, and constructs the China Human Development Index (CHDI) indicator system accordingly. Then, based on the inequality adjustment model and DFA model, the human development level of each region in China from 1990 to 2018 is measured, and the spatial and temporal evolution characteristics of China's CHDI and the current situation of regional imbalance are analyzed accordingly. Finally, LMDI decomposition technique and spatial econometric model were used to study the influencing factors of China's human development index. The results show that: (1) The weights of the CHDI sub-index estimated by the DFA model have good stability, and it is a relatively good objective weighting method. (2) Compared with the HDI, the CHDI in this paper can better reflect the level of human development in China. (3) China's human development has made great achievements and has basically achieved the leap from the low human development level group to the high human development level group. However, there are still significant gaps between regions. (4) From the results of LMDI decomposition, the livelihood index is the most important driving index of CHDI growth in each region. From the results of spatial econometric regressions, there is a strong spatial autocorrelation of China's CHDI among the 31 provinces. GDP per capita, financial education expenditure per capita, urbanization rate, and financial health expenditure per capita are the main influencing factors of CHDI. Based on the above research findings, this paper proposes a scientific and effective macroeconomic policy with important reference value for promoting the high-quality development of China's economy and society. [ABSTRACT FROM AUTHOR]

This study analyses empirically the effects of applying the OECD modified scale to the household income in order to measure the monetary poverty, which is a headline indicator in the framework of the UN sustainable development goal. We find that the reduction in the number of household consumption units derived from using the OECD modified scale, that is a standard in the EU, transforms the distribution of the disposable income to the right, raising the risk of poverty threshold per inhabitant, especially in households with fewer members. In contrast, the application of a per capita scale offers a higher degree of temporal link with the population rate in severe material deprivation, and it also prevents a disposable income transformation that introduces breaks on the left side of the distribution by type of household, showing a satisfactory soundness and reliability degree when estimating the proportion of people and households with a higher level of vulnerability. [ABSTRACT FROM AUTHOR]