Search Results (9)

This study examines global econo-environmental capability for 118 countries over 1995 to 2024 using a five-lens framework covering productive capacity (PC), developmental momentum (DM), resource efficiency (RE), degradation and depletion ratio (DDR), and remaining development potential (RDP). Using pooled k-means, a stable four archetype typology is identified and shown to persist over time. The analysis assesses how archetypes characterize country–year outcomes (RQ1), whether cross-sectional fairness is changing and relates to frontier slowdown (RQ2), and how archetypes, distance, and regional context shape transition probabilities and club convergence (RQ3). Inequality in five-dimensional capability declines slightly over the period (Gini from 0.109 to 0.092 and Palma from 1.563 to 1.464), implying modest convergence rather than increasing polarization. Average capability also improves, with larger gains for initially distant countries and smaller gains near the frontier, which is consistent with mild club convergence. Regionally, high capability cases are concentrated in Western Europe and North America, while sustained upgrading is observed in parts of Eastern Europe, mixed stability is observed in East and Central Asia, and selective advances are observed in ASEAN. Policy implications should be based on a country’s archetype and its distance to the capability ideal. Lagging countries should prioritize diffusion of proven high efficiency options and basic capability building, while frontier countries should priorities innovation, structural change, and deeper decarbonization. Policy emphasis should be updated as countries move within the capability space over time. Full article

The choice of carbon inequality metrics can significantly influence demand-side mitigation policies and their equity outcomes. We propose integrated carbon inequality metrics, including juxtaposing carbon inequality with economic inequality, disparity ratios across income and age groups, and structural income–urbanization inequality patterns. We then apply these new metrics and use the household expenditure survey data from China Family Panel Studies as a case study to examine household consumption-based carbon emissions in China. We assess the extent to which household consumption patterns, household expenditure, age, and urbanization contribute to the gap in per-capita household carbon footprints (CF) across income groups. We find that in relative terms, the top 20% income group accounts for 38% of total emissions, whereas the bottom 20% emit about 8% in China. Per-capita CFs vary slightly widely in their inequality than expenditure. The CF disparity ratios of all eight consumption categories across provinces concentrate around 4.5. CF disparity ratios of households with elderly members range from 1 to 3 and decrease with increasing household size. Rural CF-Gini exhibit a slightly wider range (0.15 to 0.52) than urban CF-Gini (0.16 to 0.42). Per capita CF of urban inhabitants was substantially larger than that of the rural ones, with 8.83 tCO₂ per capita in urban regions vs. 2.68 tCO₂ in rural regions. This study provides a nuanced understanding of within-country disparities to inform equitable demand-side mitigation solutions. Full article

This study analyzes the dynamics of China’s fruit industry using a range of analytical tools, including the location Gini coefficient, industry concentration ratio, spatial autocorrelation index, specialization index, and the industry gravity model. It explores the industry’s evolving characteristics and trends since the economic reforms, culminating in a trajectory map that highlights shifts in the industry’s gravitational center. This study also offers a qualitative analysis of the factors influencing the agglomeration and relocation of fruit production centers. The findings show a steady increase in both total output and yields per unit area within China’s fruit industry over time. Although the overall degree of agglomeration has decreased, regional agglomeration effects remain significant. Furthermore, the data reveal significant spatial autocorrelation in fruit production, indicating a long-term westward shift in core production areas. Different geographic areas exhibit varying levels of gradational shifts, with marked differences in production concentration patterns across different fruit types. This study provides a comprehensive framework for understanding production agglomeration, integrating interdisciplinary methods from statistics and geography. Full article

The period from January 2020 to December 2022 was marked by a confluence of major events, including the COVID-19 pandemic, the Russia–Ukraine war, the energy crisis, surging inflation, Federal Reserve policy shifts, and banking turmoil, which collectively fueled heightened market volatility, risk management needs, and speculative trading opportunities, leading to volatile swings in trading volume concentration across financial markets, with periods of significant increases followed by rapid declines. This paper examines the variation in the concentration of trading volume across the full spectrum of S&P 500 companies, with a focus on explaining the reasons behind the stochastic changes in trading volume concentration. We analyze different concentration measurement methods, including the power law exponent, the Herfindahl–Hirschman Index, and the Gini-based Trading Concentration Index (TCI). The research employs a novel experimental design, comparing a concentration-driven portfolio, rebalanced daily based on the top 30 stocks by trading volume, against the S&P 500 benchmark. Our findings reveal that the Gini-based TCI fluctuated between 55.98% and 77.35% during the study period, with significant variations coinciding with major market events. The concentration-driven portfolio outperformed the S&P 500, achieving an annualized return of 10.66% compared to 5.89% for the index, with a superior Sharpe ratio of 0.325 versus 0.19. This performance suggests that following trading volume concentration can yield above-average results. However, this study also highlights the importance of understanding and managing the risks associated with concentrated portfolios. This study contributes to the literature on market dynamics and offers practical insights for investors and fund managers on optimizing portfolio strategies in response to evolving concentration patterns in financial markets. Full article

The consequences of the liberalisation of electricity markets have been widely discussed in the literature emphasising the successes or failures of privatisation and deregulation. While most developed power systems have undergone a form of economic transformation, they still require to be monitored and analysed to assess market power. The Polish power system is an example wherein the potential of market power examined fifteen years ago was summarised as significant. Since then, the transformation process and changes in the ownership structure have taken place. This study focuses on the assessment of the potential of market power in the Polish electricity market. For this purpose, statistics on power companies were collected and processed. Then, structural and behavioural measures were applied, including concentration ratios, the entropy coefficient, the Gini coefficient, the Herfindahl–Hirschman Index (HHI), the Residual Supply Index (RSI), and the Lerner Index. The results reveal that, despite a dynamic increase in renewable capacity, market concentration has increased in recent years, achieving an HHI of 2020.9 in 2021. An increase in the Lerner Index of lignite and hard coal-fired units is also observed, indicating high mark-ups by the key market players. Based on quantitative analysis, policy recommendations are outlined to reduce the negative impact of market power on consumers. Full article

We used a mixed design study to analyze the inequalities and inequities in Maternal Mortality (MM) for Chocó (Colombia) between 2010–2018. The quantitative component consisted of an analytical ecological design, where proportions, ratios, measures of central tendency and rates ratios, rate difference, Gini and concentration indices were calculated to measure inequalities. The qualitative component had a phenomenological and interpretive approach. One hundred thirty-one women died in Choco between 2010–2018. The Maternal Mortality Ratio was 224/100.000 live births. The Gini coefficient was 0.35, indicating inequality in the distribution of the number of MM with respect to live births. The health service offers have been concentrated in the private sector in urban areas (77%). The exercise of midwifery has played an important role in maternal and perinatal care processes, especially in territories where the State has been absent. Nevertheless, it occurs in complex circumstances such as the armed conflict, lack of transportation routes, and income deficits, affecting the timelines and care quality for these vulnerable groups. MM in Chocó has been a consequence of deficiencies in the health system and weaknesses in its infrastructure (absence of a high level of maternal-perinatal care). This is in addition to the territory’s geographical characteristics, which increase vulnerability and health risks for women and their newborns. In Colombia, as well as in other countries, many maternal and newborn deaths are preventable because their causes are due to social injustices. Full article

In order to study the spread of an epidemic over a region as a function of time, we introduce an entropy ratio U describing the uniformity of infections over various states and their districts, and an entropy concentration coefficient $C=1-U.$ The latter is a multiplicative version of the Kullback-Leibler distance, with values between 0 and 1. For product measures and self-similar phenomena, it does not depend on the measurement level. Hence, C is an alternative to Gini’s concentration coefficient for measures with variation on different levels. Simple examples concern population density and gross domestic product. Application to time series patterns is indicated with a Markov chain. For the Covid-19 pandemic, entropy ratios indicate a homogeneous distribution of infections and the potential of local action when compared to measures for a whole region. Full article

This research investigates the traffic share evolution of the container throughput in the Mediterranean ports from 2000 to 2015 considering hierarchical clustering and concentration indexes. Compositional Data analysis techniques are used to illustrate periods with similar traffic share composition. Two different regions (East and West) in the Mediterranean Sea (Med) are selected in the function of the long haul services. The standard concentration indexes (i.e., concentration ratio, Gini coefficient, and Normalized Herfindahl-Hirschman) reveal a gentle decreasing of the concentration with relevant fluctuations mainly in the East region. This is due to the investment in port infrastructure in the area resulting from privatization initiatives in many Eastern Mediterranean countries. The periods obtained from the hierarchical clustering show a differentiated pattern in traffic share composition. For these periods, the shift-share results are consistent with traffic fluctuations and in line with the evolution of the concentration indexes. The combination of methods has allowed a good interpretation of the spatial and temporal evolution of the Med ports’ traffic being the methodology applicable elsewhere in the context of port system analysis. Full article

Additive decomposability is an interesting feature of inequality indices which, however, is not always fulfilled; solutions to overcome such an issue have been given by Deutsch and Silber (2007) and by Di Maio and Landoni (2017). In this paper, we apply these methods, based on the “Shapley value” and the “balance of inequality” respectively, to the Bonferroni inequality index. We also discuss a comparison with the Gini concentration index and highlight interesting properties of the Bonferroni index. Full article