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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]

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]

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]

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]

Societies' use of material resources is increasingly recognized as a key factor behind sustainability problems. The mass of materials used per capita and year differs substantially between countries. However, a limited range of variables (mostly per‐capita gross domestic product [GDP]) were analyzed to explain this variation. Spatial patterns of cities influence their resource use, but the role of patterns of settlements and infrastructures as co‐determinants of national‐level material use is unknown, mainly due to lacking data to investigate their effects at that scale. Here we start closing this gap by systematically analyzing a broad set of potential determinants of national per‐capita material demand, including built structures. Material demand is represented by both production‐ and consumption‐based indicators. Among its potential determinants, we analyze eight novel indicators representing extent and spatial patterns of settlements and transport infrastructures in each country, along with GDP and other indicators considered so far. Analyzing 123 countries inhabited by 91% of the world population and accounting for 92% of world GDP, we show that built structures strongly co‐determine resource use. Indicators of extent and spatial patterns of built structures have substantial additional explanatory power beyond GDP and other conventional indicators for both production‐ and consumption‐based material flow indicators. The area of built‐up land per capita emerges as the strongest predictor, but several other indicators representing built structures are also highly relevant. Limiting built‐up land and designing spatial patterns of built structures hence deserve attention in attempts to reduce societies' resource throughput. [ABSTRACT FROM AUTHOR]

This research investigates the spatial correlation among per capita electricity consumption, per capita industrial electricity consumption, and economic growth by employing various regression models, including linear regression, geographically weighted regression, and multi-stage geographically weighted regression. The primary goal is to illustrate the presence of spatial effects in the connection between electricity consumption and economic growth. In this context, this study made for Turkey distinguishes itself from previous research by utilizing the multi-stage spatially weighted regression model to examine this relationship. The findings reveal that the multi-scale spatial regression model is the most effective in explaining the relation between economic growth at the provincial level and per capita electricity consumption and per capita industrial electricity consumption. Moreover, the study emphasizes that per capita Gross Domestic Product emerges as the most influential regional economic indicator when assessing its impact on per capita electricity consumption and per capita industrial electricity consumption. [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.)

Cross-border cooperation is a major instrument of European policy to overcome the barriers posed by national borders and correcting regional imbalances. But the question of whether it is leading to the convergence of cross-border regions (CBRs) is still open for debate, given the significant heterogeneity of borders and the localized and spatially bound nature of many border effects. This article analyses the beta and sigma convergences in GDP per capita growth for the NUTS-3 at the Portuguese-Spanish border between 2000 and 2018, also considering their population growth. The main finding is that, even if their population growth is below the national averages, the CBR is converging in economic terms. This convergence is visible in the reduced dispersion of the GDP in the border regions and is also confirmed by spatial models, which showed that being a border region increases the probability of having above-average growth rates and that the NUTS-3 with initially low GDP in the cross-border region were also growing above average. This convergence was found to be robust, considering different model specifications and important factors for convergence, such as population growth and spatial dependence. A negative relationship between population and GDP per capita growth was found. [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]

• Evidence that GDP and gender equality are predictors of gender gap in the acceptance of AVs. • Gender gap in the acceptance of AVs was larger in countries with higher GDP. • Gender gap in the acceptance of AVs was larger in countries with higher gender equality. • There is no common trend that could be generalised on gender gap in the acceptance of AVs. Previous research suggests that there might be a gender gap in the acceptance of automated vehicles (AVs): males are typically found to have a higher intention to use AVs than females, although opposite results have been reported in different countries. The conflicting results have yet to be addressed, and only a few studies have attempted to explain the country-level differences based on quantifiable socio-economic indicators. We investigated the gender gap in the acceptance of AVs (SAE Level 3) using a questionnaire study among 8412 car-drivers in eight European countries as part of the European L3Pilot project. For this study, the gender gap in the acceptance of AVs is defined as the difference in the willingness to use, buy and activate the automated driving function in AVs between men and women. Results showed two distinct realities for Europe: in one group of countries, females were less willing to use AVs than males, while in another group, both males and females had similar acceptance towards AVs with higher ratings overall. These country groups were different in terms of Gross Domestic Product (GDP) per capita and the Gender Equality Index (GEI). The gender gap in the acceptance of AVs was larger in countries with a higher GDP and GEI. The study findings suggest that the gender gap in the acceptance of AVs is not universal, and the countries' progress in economics and gender equality are related to people's attitudes toward AVs. This finding enhances policy development and planning future transport solutions to ensure that all potential users can benefit from AVs. [ABSTRACT FROM AUTHOR]

The goal of this paper is to quantitatively evaluate the impact of PT's governments on the GDP per capita of the Brazilian economy. To do that, we use a synthetic control approach to create a contrafactual of Brazil's GDP per capita and, after that, we compare the economic growth under PT's administration against the contrafactual. Once we estimate the standard model using one donor pool of emerging market economies, performed a placebo test and executed some robustness exercises, we did not find strong evidence that the effect of PT's governments on GDP per capita was negative. [ABSTRACT FROM AUTHOR]

This article aimed to analyze the behavior of the northeastern municipal economic dynamics explained in the Gross Domestic Product (GDP) in relation to the volume of the Bolsa Família Program (PBF) destined for each entity, the proportion obtained from the Votes by the Mayor Elected (VPE) in the face of the set of voters participating in the election on the spot and the Mayor-Elect Party Coalition (CPPE) established or not with the state governor, based on per capita variables, in the period of 2004, 2008, 2012 and 2016. Methodologically, it was used to measurement of research results the quantile regression model for panel data. The results showed that GDP responded positively to PBF and negatively in most countries. municipalities to the VPE and CPPE did not bring favorable impacts on the northeastern municipal economy. [ABSTRACT FROM AUTHOR]

Within a wider framework of institutional factors of economic growth and the relationship between population growth and GDP growth, this article focuses on the population growth and GDP growth per capita for 30 countries in Africa between 1960 and 2020. We provide a comparative analysis of approaches to methodology and results obtained in the impact of population growth on GDP/pc growth discourse. By performing the Bootstrapped Panel-Granger Causality test, the estimation results show that half of the countries showed no causality and other half of countries showed different levels of significant causality. The most seen causality is the unidirectional causality from GDP growth per capita to population growth. In addition, unidirectional causality is observed from population growth to GDP growth per capita and bidirectional causality. Overall, the results add more evidence into the research of endogenous population growth theory, which implies that there is country-specific environment which determines the causality between these two variables. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of the main criterion employed by the European Commission for the allocation of the largest portion of Structural Funds, based on the threshold of the 75% of European Union (EU) average gross domestic product (GDP) per capita. We focus on the 2014–2020 programming period and on EU‐15 regions to analyze if this criterion has penalized some of them, as a consequence of the 2004 EU enlargement, which has represented an exogenous shock in the allocation process, due to the economic backwardness of new member states. Through the application of Synthetic Control Methods and Difference‐in‐Differences estimators at different geographical scales, we show that regions that did not obtain the less developed status in both the programming period 2007–2013 and 2014–2020, but that would have obtained it in the period 2014–2020 without the 2004 EU enlargement, experienced a significantly lower GDP per capita growth between −10.5% and −5.7%. Conversely, territories that in the period 2014–2020 lost the less developed status, previously obtained in the time frame 2007–2013, were not characterized by a significantly lower economic growth, providing some evidence of the effectiveness of the safety net. [ABSTRACT FROM AUTHOR]

The scientific impact and rankings are considered important metrics for determining national recognition and prestige, as well as for determining scientific priorities and funding. This paper analyzes the distribution of leading scientists across all scientific fields and countries, examining the similarity graphs between them. Our analysis also reveals further regional and continental patterns. By measuring the correlation between top scientists with GPD data, we show that the ratio of scientists maintains a high correlation with the GDP per capita. We also study the link between the scientific performances of a country (in terms of top research personnel it hosts) with its economic wealth. Finally, we analyze the case of Greece and show that the scientific impact of a country changes significantly when we take into consideration its scientific personnel that has migrated abroad (i.e., brain-drain). [ABSTRACT FROM AUTHOR]

Copyright of Informacion Comercial Espanola Revista de Economia is the property of S.G.E.E.I.P.C., Secretaria de Estado de Comercio, Ministerio de Industria, Comercio y Turismo 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.)

Copyright of Equidad y Desarrollo is the property of Equidad y Desarrollo 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.)

Purpose: This paper aims to explore the interplay between industrial diversity and sustainable economic development in US counties. Design/methodology/approach: Among other popularly used measures, this study uses an underused measure, Hachman index, to gauge the degree of industrial diversity in the models. To capture the impact of industrial diversity on the local community, this study estimates the relationship of two diversity measures to four traditional socioeconomic indicators: per capita personal income growth, gross domestic product per worker, income inequality ratio and poverty rate. Findings: Statistical results suggest that industrial diversity, which is measured by Hachman index, is significantly related to the four socio-economic indicators. Industrial diversity can positively contribute to regional per capita personal income growth and mitigate income inequality and poverty stress; however, it is negatively related to the gross domestic product (GDP) per worker, which means industrial specialization may contribute to GDP per worker growth. Originality/value: The findings of this study show that there is a nonlinear relationship between industrial diversity and all socioeconomic indicators. Most of the control variables, human capital variables and business and industry profile variables also display significant and positive impacts on economic development. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate whether income has different relationships to subjective well‐being in richer countries compared to poorer ones. We report analyses based on interview data collected in the European Social Survey (n = 72,574) that examine how income relates to life satisfaction (LS) and emotional well‐being (EWB) in 28 European countries, varying in gross domestic product (GDP) per capita. Our results indicate that the within‐country correlations of income with LS and EWB decrease as GDP per capita increases. Partial correlations controlling for EWB are positive but do not vary with GDP per capita, whereas partial correlations controlling for LS vary inversely with GDP per capita. We hypothesise that the invariant income‐LS relationships result from effects of relative income on social comparisons, while the varying income‐EWB relationships result from the negative impacts of time scarcity in richer countries and the buffering of negative experiences in poorer ones. [ABSTRACT FROM AUTHOR]

In recent years, gender inequality has been considered the main characteristic of insufficient gross domestic product (GDP) growth. This paper discusses the evolution of GDP per capita in 21 countries of the European Union between 2015 and 2019. Using panel regression, we investigated the change in GDP per capita through five variables. The analysis results showed that female employment rate is the most statistically significant and positive variable on GDP. Gender Equality Index also appeared to be an essential variable. The second part of our analysis consisted of an explanatory spatial data analysis of all variables to examine the spatial dimension of the variables. To explain spatial econometrics, we used selected methods, namely, choropleth maps, Local Indicators of Spatial Association (LISA) cluster analysis, Moran's scatter plots, and Moran's I statistics. Based on the visualization of choropleth maps, GDP per capita did not change during the observed period, even though the values of the explanatory variables changed. For GDP per capita, the same applies in the case of LISA cluster analysis. At the end of the monitored period, the countries were included in the same cluster as at the beginning. When plotting Moran's scatter plot, it was found that GDP per capita did not tend to have positive or negative spatial autocorrelation or no spatial autocorrelation. Moran's I statistic showed that GDP per capita values were not randomly dispersed; they were grouped according to a specific formula into clusters. [ABSTRACT FROM AUTHOR]

The rapid development of information and communication technologies (ICT) in recent years has brought about significant changes in many social sectors such as communication, economy, entertainment, and others. To define the key role that ICT plays in its development course, the European Union (EU) has developed a composite indicator, the Digital Economy and Society Index (DESI), to assess the digital policy performance of its Member States. In the current work, an attempt is made to evaluate the performance of the EU countries on the digital economy and society with respect to implemented EU digital policies by studying the five dimensions of the DESI for the years 2014–2019, using the corresponding DESI reports (DESI 2015 – DESI 2020). Moreover, the digital convergence among EU Member States, in terms of similarity of their performance in the five dimensions of the DESI by grouping them according to the optimal number of clusters, is also examined. Since the optimal number of clusters is two, EU Member States are classified in two groups, one of high and one of low performance in the five dimensions of the DESI. The evolution of each member country and the possible transitions from one group to another during the years 2014–2019 is also a point of interest. The grouping of EU Member States into the two clusters showed that socioeconomic factors may affect the overall DESI. Linear mixed effect models confirm the positive effect of Gross Domestic Product per capita, the public expenditure for education and research and development (R&D) on the DESI and the negative effect of the average number of weekly working hours. The results could be used to reform the existing EU digital policies and identify areas where further improvement is needed. [ABSTRACT FROM AUTHOR]

A well-developed management structure is the backbone for the successful operation of any enterprise. The underrepresentation of women in managerial positions has been a persistent concern in the context of gender equality and economic development. This paper investigates the percentage participation of women managers in European countries and its potential connection to GDP per capita. Utilizing a comprehensive dataset comprising various European countries, we conduct a comparative analysis of the proportion of women in managerial roles across different economies with a special reference to North Macedonia. Additionally, GDP per capita data is incorporated to explore potential correlations between women's representation in management and economic prosperity. The analysis covers the following regions: Scandinavia, Nordic region, as well as Eastern, Western and Southern Europe. The analysis refers to two consecutive years, 2020 and 2021. The results indicate that the percentage participation of women managers and GDP per capita are inversely proportional in the Scandinavian region, the Nordic region, as well as Eastern and Western Europe, while the opposite conclusion applies to the countries of Southern Europe. [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]

While numerous studies have tried to analyze the impact of intergovernmental transfers in fostering fiscal equalization in India, there need to be more studies in the context of north‐eastern (NE) states. Situating in a geographically isolated and economically backward region, the states of NE India depend heavily on central fiscal transfers to meet expenditures and to promote various economic activities in the region. One of the essential objectives of these transfers is to achieve fiscal equity. Hence, the study attempts to analyze the fiscal equalizing nature of the intergovernmental transfers across NE India during 1991–2019. The coefficient of variation (CV) analysis results indicates that although fiscal transfers reduced the magnitude of disparity in the own‐source revenue across the NE states, a significant amount of disparity still exists in the resource base across these states. The regression analysis findings suggest that the transfers across these states need to be more fiscal equalizing. The per capita gross state domestic product emerges as a positive and significant in predicting per capita transfers, and hence it questions the progressivity of central transfers. When assigning the interstate share of transfers, more weight should be placed on fiscal equalizing factors such as per capita income. The Finance Commission of India should emphasize fiscal equalizing criteria when allocating weights and recommending transfers to the NE States. Additionally, states with low incomes should be recognized in plan schemes. [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]

With a population of over 1.4 billion surpassing China's in 2023, India has now become the world's most populous country. Despite its robust IT and service sectors propelling it to become the fifth‐largest economy, India still grapples with low GDP per capita and significant poverty. The paradoxical nature of India's development necessitates a closer examination of its governance. Over 90% of the Indian population works outside the purview of formal democratic institutions and capital‐intensive economic sectors. Challenges arise from the need to sustain a large poor population with limited resources while catering to the formal sector that generates more than half of its GDP. India's governance exhibits a deep mismatch between its institutional design, politics and developmental needs. This article explores the duality of informal and formal sectors underlying challenges in Indian governance by way of the Berggruen Governance Index. [ABSTRACT FROM AUTHOR]

The existence of fluctuations is part of the narrative, especially when there is a slowdown (or worse, a contraction) in economic activity. The presence of long waves with a period of about 50 years as proposed by Kondratieff is one of the most controversial and fascinating theories about economic cycles. This paper analyses both the original Kondratieff data (from which the hypothesis started) and a dataset that includes GDP per capita for several significant countries. By applying the wavelet analysis (WA), the main objective of the paper is to understand whether it is plausible to support the existence of periodic fluctuations consistent with long cycles theory. The outcomes for Kondratieff's original dataset do not show the presence of a coherent periodicity for most cases. The same conclusion can be drawn for all the GDP per capita series. [ABSTRACT FROM AUTHOR]

This paper surveys the complex relationships between economic growth and Foreign Direct Investment (FDI) in South Asian countries, taking into account the specific conditions and environments that influence foreign investment in each country's economy. The study analyzes annual data from 1991-2020 focuses on India, Pakistan, and Bangladesh and uses cointegration and granger causality tests to determine that every country is at a distinct stage of outreach based on factors such as population, resources, and international trade. Results declare that FDI, economic development, and exports have robust relationship. The study concludes that creating a favorable environment for investors can increase foreign investment, leading to increase per capita GDP growth within the country. [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]

This study has prepared by help of the secondary data with the aim to inspect the relation between countries' efficacy on struggling This study has prepared by help of the secondary data with the aim to inspect the relation between efficacy of countries on combating activities with COVID-19, and national culture. Index of Hofstede's cultural dimensions was used to measure the national culture. COVID-19 Regional Safety Assessment index, which was prepared by Deep Knowledge Group and included 250 countries, was used to measure the countries' efficacy on their struggle on COVID-19. COVID-19 Regional Safety Assessment index was designed to classify, analyse and order the weakness and strength of the countries which faces opportunities and threats due to the outcome of the global health, and economy crisis which triggered by the COVID-19. Data of 93 countries, which have the points belong to each cultural dimensions of Hofstede from 250 countries included in COVID-19 Regional Safety Assessment index, was included in the analysis. In the result of the multiple regression analysis, relation between the dimensions of "power distance" and "long/short term focus" and efficacy of countries on their combating COVID-19 is statistically significant. Also, the controlled variable of GDP [gross domestic product] per capita of the countries made no difference on the results. [ABSTRACT FROM AUTHOR]

Promoting convergence between regions is essential to ensure that both the wealthiest and poorest regions achieve comparable levels of development over time. With this objective in mind, the objectives of the research were to determine the existence of global convergence or convergence clubs among the regions in Peru, as well as to identify the factors influencing such convergence. To identify convergence clubs, the study utilized the load factor methodology introduced by Phillips and Sul (2007) and analyzed panel data from the 2004-2008 period. The results reveal the presence of three convergence clubs based on GDP per capita and labor productivity. Additionally, the composition of the clubs in terms of GDP per capita and labor productivity depend directly on human capital, royalty transfers, and spatial location. These findings suggest that the State should prioritize regions belonging to the poorer convergence clubs. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Ciencias Sociales (13159518) is the property of Revista de Ciencias Sociales de la Universidad del Zulia Venezuela 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.)

The article examines the relationships between the key components of the levels of socioeconomic development of Ukraine and the Republic of Azerbaijan. The aim of the study is to build a model of intercountry regression of per capita economic growth of both Ukraine and the Republic of Azerbaijan and to perform a comparative cross-country analysis of the key component of inclusive growth of the two countries under the strong influence of financial and socioeconomic crisis processes and the ongoing war. The study is aimed at an empirical study of the joint movement of both indicators, the identification of cause-and-effect relationships and cointegration dependence, the determination of a long-term integration relationship, allowing to take the necessary steps and measures for the positive mutual impact of trade and economic relations between the two countries on the national socioeconomic development. As the level of economic development, GDP per capita was used, taking into account purchasing power parity (PPP). The analysis of the dynamic relationship of indicators is carried out on the basis of data from January 1990 to December 2022. The study uses econometric methodology, including the extended Dickey–Fuller test for the presence of a single root, the Granger test for causality, the Engle–Johansen tests for cointegration, the vector model of error correction, and standard diagnostic tests. Tests for stationarity, causality, and cointegration were performed at the 10% significance level in the entire sample. The cointegration of the integrated 1st order of non-stationary initial series is revealed, where the preferred variant is the one with a trend, in which the marginal rate of restoration of equilibrium between GDP per capita at PPP of the two countries in the current year after the shock of the independent variable in the previous year is noted. The result, showing that GDP per capita at the PPP of Ukraine is in a slight positive dependence on GDP per capita at the PPP of Azerbaijan, is obtained. The empirical model explains 95% of the variation in the initial levels, and the equation of the vector error correction system 51% explains the differences. Recommendations are provided to ensure a long-term equilibrium of the joint movement of GDP at the PPP of both countries and to reduce the imbalance. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Social Sciences Research / Sosyal Bilimler Arastirmalari Dergisi is the property of ODU Journal of Social Sciences Research 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.)

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]

Copyright of Trakya University, Economics & Administrative Sciences Faculty E-Journal / Trakya Üniversitesi İktisadi ve İdari Bilimler Fakültesi E-dergi is the property of T.C. Trakya Universitesi 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.)

Copyright of Optimum: Journal of Economics & Management Sciences / Ekonomi ve Yönetim Bilimleri Dergisi is the property of Optimum: Journal of Economics & Management Sciences 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.)

Among the most relevant concerns of human beings nowadays is that of gas emissions, especially carbon dioxide emissions in developed and underdeveloped countries, authors such as Ghazvini, Dehghani Madvar, Ahmadi, Rezaei, El Haj Assad, Nabipour, and Kumar, R. (2020) argue that CO2 emissions related to energy are considered one of the most crucial problems and are rapidly increasing due to increased urbanization. It is important to highlight that different countries have enacted environmental regulations that generate a positive impact on development and ecological sustainability, but these regulations must be applied efficiently, it is of vital importance that political institutions play a leading role in the formulation and management of environmental regulations. Therefore, the following article aims to analyze the relationship of the Gross Domestic Product Per capita with environmental conservation, in Latin America, taking into account that its participation in the world economy according to data from ECLAC (2018) represents 8% of the Global GDP of the world population and we contribute to environmental degradation. For the development of this study, the Kuznets Environmental Curve was used, which allows generating a relationship between GDP per capita and CO2 emissions. The data used corresponds to 27 economies: Argentina, Belize, Bolivia, Brazil, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, Grenada, Guatemala, Guyana, Honduras, Haiti, Jamaica, Saint Lucia, Mexico, Nicaragua, Panama, Peru, Paraguay, El Salvador, Suriname, Saint Vincent and the Grenadines. This allows the generation of hypotheses based on the relationship between monetary amounts and the effect of a set of implications that arise as a result of the use of natural resources (Mosconi, et al. 2020), which may present the low efficiency of the processes. Among the most relevant findings, it can be concluded that the behavior of carbon dioxide emissions is closely related to the GDP per capita, indicating that the general Latin American income is based on environmental exploitation, agriculture and invasive livestock farming. [ABSTRACT FROM AUTHOR]

Since colonial times, substantial regional income disparities have been reported for Indonesia. However, in spite of a wide variety of available data and indicators, so far published data on Indonesian per capita GDP in colonial times are limited to macro-estimates for the entire archipelago or are confined either to Java or to the Outer Islands. In this paper we provide a first attempt to arrive at estimates of diverging income and living standards at a regional level. We implement the Geary and Stark method on a large body of data collected by the colonial government, to estimate GDP for ten macro-regions and five benchmark years between 1870 and 1930. Our findings, corrected for prices, confirm the image arising from the existing literature of major divergences within the Indonesian archipelago in general, and of a higher per capita GDP in most of the Outer Islands (all islands of the Indonesian archipelago except for Java and Madura) compared with Java in particular. This was definitely the case in 1870 and still the case in 1920, but the picture is less clear for 1930, which was the final year before Indonesia's commodity exports started to collapse. [ABSTRACT FROM AUTHOR]

Citizen Science (CS) provides valuable data to assist professional scientists in making informed decisions on macroinvertebrate conservation. However, CS is not developed nor implemented uniformly across the globe, and there are biases and challenges in the extent that it can contribute to global macroinvertebrate conservation. Here, a meta-analysis was performed using 107 Citizen Science Projects (CSPs) to identify underlying biases related to taxon representativity, country wealth, and demographic participation. Macroinvertebrate orders with the highest representativity were Lepidoptera and Hymenoptera, accounting for 53% of represented macroinvertebrate groups. The orders Scorpiones, Parasitiformes, and Spirobolida had proportionately the highest IUCN threat statuses, but significantly lower CSP representation, indicating that these orders require more public attention. Hymenoptera, Odonata, Coleoptera, Hemiptera, Diptera and Clitellata had the highest levels of Data Deficient species, suggesting that the primary objective of CSPs targeted at these orders should be collecting distribution and abundance data to improve Red List assessments. Global distribution of CSPs was uneven and the number of CSPs per country was positively correlated with national Gross Domestic Product (GDP) and GDP per capita, suggesting that countries with relatively low GDP face challenges to successfully establish and maintain CSPs. Establishing new CSPs can assist macroinvertebrate conservation in these countries, where biodiversity levels are often high. To accommodate these biases, CSP development should adopt a bottom-up approach, in which CSPs are designed to address data gaps, and to address local socio-economic limitations and cultural ideologies. Guidelines for such development are presented here, with emphasis on addressing societal variations and inter-disciplinary communication gaps to ensure equitable opportunities for CSP participation. [ABSTRACT FROM AUTHOR]

Copyright of Itobiad: Journal of the Human & Social Science Researches / İnsan ve Toplum Bilimleri Araştırmaları Dergisi is the property of Itobiad: Journal of the Human & Social Science Researches 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.)

The Association of Southeast Asian Nations (ASEAN) region is vulnerable to the effects of climate change. However, urbanization and energy supply are essential to the ASEAN economy. This study examines the effects of CO2 emissions and urban population on GDP per capita in 10 ASEAN countries from 1995 to 2021. Furthermore, ASEAN countries are divided into three income groups. According to the results of this study's panel data analysis, urban population, and CO2 emissions per capita have a positive effect on GDP per capita, respectively. However, both urban population and CO2 emissions per capita reduce GDP per capita. While CO2 emissions per capita and GDP per capita have a negative relationship in low- and high-income countries, the urban population positively impacts GDP per capita across the ASEAN region's income levels. In low- and high-income countries, urban population, and CO2 emissions per capita have a positive impact on GDP per capita. [ABSTRACT FROM AUTHOR]

In this study, the relationship between the net migration rate in Turkey between 2008-2019 and the Real Gross Domestic Product (GDP) per Capita was tested with the Spatial analysis method. Net migration is expressed as the difference between the migration received by a particular settlement and the migration given. The value obtained by dividing the net migration value by the mid-year population and multiplying by one hundred or a thousand is expressed as the net migration rate. The phenomenon of migration that takes place in a certain place is one of the factors affecting per capita income. Spatial Analysis, on the other hand, determines the interaction between variables between units that are geographically close to each other. In the results of working; Provinces with strong and weak spatial relationships between net migration rate and GDP data for the specified years for Turkey were identified. Spatial distribution maps were drawn, Moran I index results, low increasing positive autocorrelation was detected in GDP data for the determined years, while high positive decreasing autocorrelation was detected for net migration rate data. Then, with the LISA clustering maps, the relationship between the provinces was low, high, and unrelated clustered. [ABSTRACT FROM AUTHOR]

What is the significance of GDP per capita to a society? What does it represent conceptually? These questions have been addressed in past decades, engendering extensive explorations of the limitations of the indicator, yet answers have proved problematic or partial. The paper presents the main conclusions so far drawn and builds upon them to present a new reading of the significance of GDP per capita. At the heart of this reading is the view that, while GDP per capita is not indicative of the welfare of individuals, it is indicative of an irreducible 'group well-being.' This view, however, requires one to relinquish the belief that only individuals can be 'well.' It turns out that the allegedly orthodox view, which sees GDP as a human-centered indicator, requires an unorthodox philosophical standpoint, one that accepts an irreducible group well-being. The paper presents this alternative interpretation and addresses its upsides and limitations. [ABSTRACT FROM AUTHOR]

The concept of economic complexity has recently become an important factor in explaining the income and growth differences between countries. Economic complexity is important in terms of indicating the diversity of knowledge and skills that countries have and the level of knowledge and technology of exports. Economic complexity provides a competitive advantage as it indicates the level of sophistication of the products. The aim of the study is to analyze the effects of economic complexity and R&D expenditures on economic growth in countries with high levels of competitiveness. In this study, long-term reciprocal relations were examined with annual data covering the period 1995-2019. In the study, the panel cointegration test were applied. According to the results of panel cointegration tests, it was observed that there is a cointegration relationship between the variables of overal GDP per capita, economic complexity index and R&D expenditures. In long term selected countries, both economic complexity index and R&D expenditures within GDP positively affect GDP per capita. [ABSTRACT FROM AUTHOR]

With climate change and rising sea levels, the residents and assets in low-elevation coastal zones (LECZ) are at increasing risk. The application of high-resolution gridded population datasets in recent years has highlighted the threats faced by people living in LECZ. However, the potential exposure of gross domestic product (GDP) within LECZ remains unknown, due to the absence of refined GDP datasets and corresponding analyzes for coastal regions. The climate-related risks faced by LECZ may still be underestimated. In this study, we estimated the potential exposure of GDP in the LECZ across China by overlying DEM with new gridded GDP datasets generated by random forest models. The results show that 24.02% and 22.7% of China's total GDP were located in the LECZ in 2010 and 2019, respectively, while the area of the LECZ only accounted for 1.91% of China's territory. Significant variability appears in the spatial-temporal pattern and the volume of GDP across sectors, which impedes disaster prevention and mitigation efforts within administrative regions. Interannual comparisons reveal a rapid increase in GDP within the LECZ, but a decline in its share of the country. Policy reasons may have driven the slow shift of China's economy to regions far from the LECZ. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Economic & Social Research is the property of Abant Izzet Baysal University, Faculty of Economics & Administrative Sciences 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.)

The purpose of this study is to analyze the influence of GDP, urbanization, trade openness, financial development, and renewable energy consumption on CO2 emissions in Pakistan using yearly time series data from 1985 to 2018. The study utilized the cointegration technique and Granger causality for empirical estimation. The results of the study indicated that urbanization, financial development, and trade openness upsurge CO2 emission. Whereas using renewable energy resources is favorable for the environment and possesses negative relation with CO2 emission. All variables possess long-run relation with Co2 emission. Granger causality shows unidirectional causality from GDP and renewable energy to CO2 emission. The study contains insight for policymakers in Pakistan with beneficial policy recommendations to work toward a sustainable green environment. [ABSTRACT FROM AUTHOR]