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Brazil’s regional inequality is an important topic due to the large and persistent differences in development between states and the high levels of inequality in the country. These variations in development can potentially render survey data inaccurate since the significance of capital income varies across the states. Besides, previous studies incorporating tax and national accounts data globally have mainly focused on measuring the income distribution at the country-level. This approach can limit the understanding of inequality, especially when considering large countries such as Brazil.

The methodology used to construct these estimates follows the guidelines of the Distributional National Accounts, whose core goal is to provide income distribution measures consistent with macroeconomic aggregates and harmonized across countries and time. The procedure has three main steps: first, it corrects the survey’s underrepresentation of top incomes using tax data. Then, it accounts for national income items not included in the survey or tax data, such as imputed rents and undistributed profits. Finally, it ensures that all components match the national income.

Compared to survey-based estimations, the results reveal a new angle on the state-level inequality. This study indicates that Amazonas, Rio de Janeiro and São Paulo have a more concentrated income distribution. The top 1\% of earners in these states receives around 28\% of total pre-tax income, while the top 10\% receive nearly 60\%. On the other end, Amapá (AP), Acre (AC), Rondônia (RO) and Santa Catarina (SC) are the states where the income distribution is less concentrated. There were no significant changes in the income distribution across the states during the period analyzed.

This study combines survey, tax and national accounts data to construct new estimates of Brazil’s state-level income distribution from 2006 to 2019. Previous results only considered income captured in surveys, which usually misses a significant part of capital incomes. This limitation may bias comparisons as capital income has different importance across the states. The new estimates represent the income of top groups more accurately, account for the entire national income and enable to compare regional inequality levels consistently with other countries.

The measurement of regional competitiveness is becoming essential for policymakers to address territorial disparities, while considering the issue of correlations among indicators. Therefore, the purpose of this paper is to measure regional competitiveness using the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) by considering different distance measures and two levels of analysis to provide a comparative and comprehensive measurement of regional competitiveness in Europe.

The authors apply TOPSIS based on three different distance measures (the Manhattan, the Euclidean and the Mahalanobis distance measures) to the regions of the EU Regional Competitiveness Index (RCI) 2019, which is taken as the frame of reference.

The authors replicate the RCI by using TOPSIS with a less preferred choice of distance measure, indicating TOPSIS as a valuable method for policymakers in the analysis of regional competitiveness. The authors argue in favour of the Mahalanobis distance measure as the best of the three, as it considers correlations among macro-economic indicators.

This study aims to make three contributions. Firstly, by replicating the RCI by means of TOPSIS with a less preferred choice of distance measure, the paper provides a benchmark for future research on regional competitiveness. Secondly, by suggesting the use of TOPSIS with the use of the Mahalanobis distance measure, the authors show how to measure regional competitiveness by taking into account correlations among pillars. Thirdly, the authors argue in favour of considering clusters of regions when measuring regional competitiveness.

The purpose of this paper is to report about research how Society 5.0 balances Industry 4.0, responsible economic development and resolution of social problems by advancement of corporate social responsibility (CSR) in organizations.

Drawing from organization, sustainable development and social functionalism theories, the authors designed an integral model of CSR in line with goals of a forward-looking and socially responsible society. This study includes analyzing of present governing principles, multidisciplinary and multifunctional consideration and developing of integral framework for CSR in organizations.

This study’s findings suggest incorporation of technology in models of CSR, a regionally grounded solving of individuals’ social problems and changing of CSR’s environmental, social and economic dimensions according to circumstances of Society 5.0.

This study has created guidance for improvement of CSR practice in organizations through its responsible operating and behavior grounded on the governing environmental and social circumstances in modern society. It also revealed new possibilities for interest-based usage of human-centered society among individuals and organizations.

The reported study proposed an integral model of CSR for solving the main social problems with usage of advanced technologies in responsible economic growth founded on circumstances of Society 5.0, previously not considered in literature.

The purpose of this paper is to provide a measure of competitiveness of the Spanish autonomous communities from a multidimensional and dynamic perspective for the period 2008-2016.

This paper adopts a broad definition of competitiveness based on five key environments (productive capital, human capital, social and institutional capital, infrastructure and knowledge) and comprising 53 indicators. The method used to construct the competitiveness index is based on the P-distance proposed by Pena Trapero (1979), which objectively assigns weights to the indicators. There is an important advantage in the methodological proposal of this study, as it allows analyzing the behavior of partial and aggregated indicators from a dynamic perspective, taking the same value as a reference for the entire period. Therefore, not only a classification obtained for each year but also the variation that occurs in terms of the reference period can be analyzed.

The classification of the autonomous communities is established using common intervals based on the results obtained for the whole period, i.e. 2008-2016. The data point to the unequal situations of the autonomous communities. The results also reveal that the evolution of the regional competitiveness synthetic index is clearly cyclical and the drop recorded in the recessive period is less pronounced than the increase recorded in the growth phase.

The main innovation of the competitiveness index presented here lies in its allowing comparisons over time.

Although ecosystems have been researched extensively over the past decade, we know little about how they should be organised. Focusing on a knowledge ecosystem comprising a university and a regional strategic network (RSN), this paper aims to describe and discuss the mechanisms for knowledge development in knowledge ecosystems.

This paper studies the integration of a university into a Swedish RSN. Data were collected through interviews with representatives of the university, the RSN and all firms comprising the RSN. A qualitative content analysis helped to detect mechanisms for knowledge development.

Two reinforcing mechanisms for knowledge development in the knowledge ecosystem are identified: structure and openness, which relate to insight and outlook, respectively. The findings also indicate a knowledge division, with the university representing the transfer of knowledge capabilities as a linear process, whereas the content-related knowledge is collaborative.

This paper contributes to research on knowledge ecosystems by describing how their organisation is based on a number of contradictions (structure and openness, insight and outlook, linearity and collaboration) to accomplish the development of knowledge capabilities and content-related knowledge.

With the recognition that generating economic growth is not the same as sustaining it, the challenge to catch-up and growth literature is discerning between these processes. Recent research suggests that the decline in the frequency of “shrinking” episodes is more important for long-term development than higher growth rates. By using a framework centred around social capabilities, this study aims to investigate the effects of income inequality and poverty on economic shrinking frequency, as opposed to previous literature that has exclusively had a growth focus. The aim is to investigate how and why some societies might be more resilient to economic shrinking.

The research is a quantitative study, and the authors build a longitudinal data set including 23 developing countries throughout 42 years to test the paper’s purpose. This study uses country and period fixed-effects specifications as well as cross-sectional graphical representations to investigate the relationship between proxies of economic inclusivity and the frequency of shrinking episodes.

The authors demonstrate that while inclusive societies are more resilient to shrinking overall, it is changes in poverty levels, but not changes in income inequality, that appear to be correlated with economic shrinking frequency. Inequality, while still an important element to explain countries’ growth potential as an initial condition, does not seem to make the sample more resilient to shrinking. The authors conclude that the mechanisms in which poverty and inequality are correlated with the catch-up process must run through different channels. Ultimately, processes that explain growth may intersect but not always overlap with the ones that explain resilience to shrinking.

The need for inclusive growth in long-term development has been championed for decades, yet inclusion has seldom been explored from the shrinking perspective. Though poverty reduction is already an important mainstream political objective, this paper differentiates itself by providing an alternate viewpoint of why this is important. Income inequality could have more of an economic growth limiting effect, while poverty reduction could be required to build resilience to economic shrinking. Developing countries will need both growth and resilience to shrinking, to catch-up with higher-income economies, which policymakers might need to balance carefully.

This article aims to evaluate the entry and exit of companies from local productive structures, with a specific focus on the sectoral complexity of these activities and the complexity of these portfolios. The study focuses on empirically demonstrating the thesis that related economic diversification exacerbates the development gap between more and less complex regions.

The article uses indicators formulated by the economic complexity approach. They allow a relevant descriptive analysis of the economic diversification process in Brazilian micro-regions and provide the foundation for the econometric tests conducted. Through three distinct estimation strategies (OLS, logit, probit), the influence of complexity and relatedness on the entry and exit events of firms from local portfolios is tested.

In all estimated models, the stronger relationship between an activity and a portfolio significantly increases its probability of entering the productive structure and, at the same time, acts as a significant factor in preventing its exit. Furthermore, the results reveal that the complexity of a sector reduces the probability of its specialization in less complex regions while increasing it in more complex regions. On the other hand, sectoral complexity significantly increases the probability of a sector leaving less complex local structures but has no significant effect in highly complex regions.

Due to the data used, the indicators are calculated considering only formal job numbers. Additionally, the tests do not detect the influence of spatial issues. These limitations should be addressed by future research.

The article characterizes a prevailing process of uneven development among Brazilian regions and brings relevant implications, primarily for policymakers. Specifically, for less complex regions, policies should focus on creating opportunities to improve their diversification capabilities in complex sectors that are not too distant from their portfolios.

The article makes an original contribution by proposing an evaluation of regional diversification in Brazil with a focus on complexity, introducing a more detailed differentiation of regions based on their complexity levels and examining the impact of sectoral complexity on diversification patterns within each group.

This paper examines the relationship between transport connectivity and regional economic development in China. It develops measurements appropriate for transport connectivity based on a set of evaluation models. This model is used to analyze the logistic connectivity of China’s 31 provinces by focusing on 11 variables, including some new factors (Density of road network, Density of railway network, Number of Internet Users) not used in previous studies, over the 13-year period from 2002 to 2014. Using panel data regression analysis, the empirical results show a statistically significant and positive impact of transport connectivity (factors like Density of road network, Density of railway network and Number of Internet Users) on economic development in China. In particular, the Number of internet users is a key factor reflecting information connectivity in all the variables. Comparative analysis regarding economic development is conducted to benchmark between coastal provinces and interior provinces. Like most previous research, this study yields the same finding of higher impact of transport connectivity on economic development in eastern provinces than in western provinces. This study suggests that decentralized decision-making will be significantly more efficient for analyzing regional infrastructure development. It also shows that the influence of transport connectivity on economic development is dependent on a certain developmental stage. This suggests that an economic region should adopt different development strategies for transport connectivity during different stages of development.

Tourism has grown to be one of the world's largest and fastest-growing economic industries. Tourism development is viewed as a tool to improve income distribution as it allows people at the bottom of the pyramid to get involved in the industry. This study aims to examine the impact of tourism on income inequality in the top income equality countries.

The paper employs fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares techniques to investigate the dynamic impact of tourism on income inequality in the world's most income equality countries, from 2001 to 2016.

The result shows that tourism is one of the major drivers of income equality. Thus, tourism can be used to reduce a country's income disparity.

As a result, policymakers should support the tourism industry to reduce income disparity and enhance income distribution.

Given the conflicting findings in the literature, this study reexamines this link and attempts to backwardly assess if the top equal-income countries in the world are heavily dependent on tourism.

Non-fossil fuels are receiving increasing attention within the context of addressing global climate challenges. Based on a review of non-fossil fuel consumption in major countries worldwide from 1985 to 2015, the purpose of this paper is to analyze trends for global non-fossil fuel consumption, share of fuel consumption and inequality.

The similarities were obtained between the logarithmic mean divisia index and the mean-rate-of-change index decomposition analysis methods, and a method was proposed for complete decomposition of the incremental Gini coefficient.

Empirical analysis showed that: global non-fossil fuel consumption accounts for a small share of the total energy consumption, but presents an increasing trend; the level of global non-fossil fuel consumption inequality is high but has gradually declined, which is mainly attributed to the concentration effect; inequality in global non-fossil fuel consumption is mainly due to the difference between nuclear power and hydropower consumption, but the contributions of nuclear power and hydropower to per capita non-fossil fuel consumption are declining; and population has the greatest influence on global non-fossil fuel consumption during the sampling period.

The main contribution of this study is its analysis of global non-fossil fuel consumption trends, disparities and driving factors. In addition, a general formula for complete index decomposition is proposed and the incremental Gini coefficient is wholly decomposed.