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Narratives play a pivotal role in solving complex problems, as they provide an interpretive framework for facilitating the solution to a given challenge. We presume that if the basis of a narrative applied to a complex problem is incorrect, the interpretation of the problem will also be distorted. Therefore, solutions that are primarily low-efficiency in nature demand new or “rframed” narratives. We examine this premise through the case of the United Kingdom in the light of changes in narratives created to solve regional inequalities, particularly regarding the interpretative framework of the “Levelling Up” policy agenda and narrative, which was introduced by the government of Boris Johnson. Additionally, we conducted a literature review on the Levelling Up policy to provide a supplementary theoretical background beyond the concept of narratives. Conclusions on narratives and Levelling Up are also outlined.

Entropy has been proposed as a significant tool for an analysis of spatial differences. Using Semple and Gauthier’s (1972) transformation of the Shannon entropy statistic into an entropy measure of inequality and their algorithm, an estimation is made of changes in regional inequality in Poland over the years 2005–2012. The inequality is decomposed into total, inter- and intra-regional types, and an analysis is made of relations holding between them.

The main idea of the paper is to offer a method of effectiveness analysis of regional socio-economic system management in Ukraine. This study develops evaluation criteria for the assessment of intraregional differentiation of Ukrainian Black Sea regions. The goal of the research is to reveal the algorithm of the regional socio-economic system evaluation in order to find out the direction of necessary managerial strategy for a region. This was implemented via such methods as comparative analysis, interpretation of statistical indices of regional effectiveness, and structural analysis. The research results reveal that a chosen system of indicators forms a method to evaluate six levels (four zones) of effectiveness of regional socio-economic system management in Ukraine. Considering agriculture, food industry, pharmaceuticals, light industry, and tourism as the basic industries of the regions, the industrial structure of the regional socio-economic system of Ukrainian Black Sea regions in the context of its modernization according to the offered method was developed.

A populist backlash to globalization has ushered in nationalist governments and challenged core features of the Liberal International Order. Although startling in scope and urgency, the populist wave has been developing in declining regions of wealthy countries for some time. Trade, offshoring, and automation have steadily reduced the number of available jobs and the wages of industrial workers since at least the 1970s. The decline in manufacturing employment initiated the deterioration of social and economic conditions in affected communities, exacerbating inequalities between depressed rural areas and small cities and towns, on the one hand, and thriving cities, on the other. The global financial crisis of 2008 catalyzed these divisions, as communities already in decline suffered deeper and longer economic downturns than metropolitan areas, where superstar knowledge, technology, and service-oriented firms agglomerate. We document many of these trends across the United States and Europe, and demonstrate that populist support is strongest in communities that experienced long-term economic and social decline. Institutional differences in labor markets and electoral rules across developed democracies may explain some of the variation in populists’ electoral success. Renewed support for the Liberal International Order may require a rejuvenation of distressed communities and a reduction of stark regional inequalities.

The recent surge in populist movements sweeping many countries has brought into focus the issue of regional inequality. In this article, we develop a panel data set for Canada that includes information on 284 regions observed at 5-year intervals (from 1981 to 2011) and estimate a series of spatial econometric models to study the causes and consequences of regional inequality. Our results draw attention to the fact that the rise in inequality at the national level has been accompanied by greater cross-regional inequality. Differences in the level of economic development, precariousness of labor market conditions, and socioeconomic factors are among the key drivers of these regional patterns of inequality. We also find that the industrial mix of a region plays an important role in shaping its distribution of income: regions with high concentrations of manufacturing activities typically have lower levels of inequality, whereas regions with high concentrations of tertiary services, arts, and entertainment, as well as knowledge-intensive business services tend to have higher levels of inequality. In terms of the consequences of inequality, the growth/equity trade-off across Canadian regions varies significantly over the short- vs. medium-term horizons. In the short run, our results suggest that inequality is positively related to regional economic growth. This response changes as we move to a medium-term horizon, which suggests that as inequality persists over longer periods of time, it has a negative and significant impact on regional growth trajectories. Panel vector autoregressive models are also used to further explore the direction of causality of the growth-inequality relationship.

An important channel through which less developed European countries have grown over the past twenty years is through the industrial transformation of their economies from low to higher value-added activities. The aim of the paper is to address the role of industrial transformation on regional imbalances, by analysing the different components of industrial productivity dynamics, namely the industrial composition, competition and reallocation effects. Based on both a shift-share analysis and a simulation analysis, the paper shows that the reallocation towards higher value-added sectors in Central and Eastern European (CEE) countries could in fact lead to higher regional inequalities. Our empirical results lead us to claim that short-term normative interventions should go in the direction of supporting “modern and technologically advanced traditional sectors” rather than necessarily pushing CEE countries towards a high value-added industry specialization.

This study introduces an innovative tool to analyse how various inequality factors, including geography, race, and gender, contribute to overall inequality. Traditional approaches typically partition populations into groups based on a single factor and assess inequality by additively decomposing an inequality measure into within- and between-group components. After discussing the theoretical impossibility of additively decomposing the Gini index into within- and between-group components, in fact, we propose a Gini decomposition into two highly informative within- and between-components, with substantial improvement upon the usual assessment of horizontal inequality. This method represents a significant advancement over the traditional horizontal inequality assessment, which only compares group means and overlooks the complexities of differences between groups. Our approach accurately captures the nuances of group disparities, offering a robust measure of horizontal inequality. Through rigorous simulations and empirical analysis of the OECD Income Distribution Database, we validate the effectiveness of our method in evaluating and understanding inequality. This work enriches the toolkit available to researchers in the field by offering a framework for selecting the most suitable measure of horizontal inequality, along with the code for implementing the proposed decomposition.

Regional economic inequality is a persistent problem for all nations. Meanwhile, satellite-derived night-time light (NTL) data have been extensively used as an efficient proxy measure for economic activity. This study firstly proposes a new method for correction of the NTL data derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite and then applies the corrected NTL data to estimate gross domestic product (GDP) at a multi-scale level in China from 2014 to 2017. Secondly, incorporating the two-stage nested Theil decomposition method, multi-scale level regional inequalities are investigated. Finally, by using scatter plots, this paper identifies the relationship between the regional inequality and the level of economic development. The results indicate that: (1) after correction, the NPP-VIIRS NTL data show a statistically positive correlation with GDP, which proves that our correction method is scientifically effective; (2) from 2014 to 2017, overall inequality, within-province inequality, and between-region inequality all declined, However, between-province inequality increased slightly. As for the contributions to overall regional inequality, the within-province inequality was the highest, while the between-province inequality was the lowest; (3) further analysis of within-province inequality reveals that economic inequalities in coastal provinces in China are smaller than in inland provinces; (4) China’s economic development plays an important role in affecting regional inequality, and the extent of influence of economic development on regional inequality is varied across provinces.

Economic theory, including endogenous growth, the role of institutions, and, most importantly, the New Economic Geography (NEG), have made significant progress in explaining the emergence of core-periphery patterns behind this divergence. They point to the critical role of agglomeration, which confers benefits to metropolitan cores that have the advantages of large markets, deep labor pools, links to international markets, and clusters of diverse suppliers and institutions. Regions relatively near the metropolitan core are likely to benefit from spillovers and congestion-related dispersion. Regions further outside the core however, are not only less able to take advantage of spillovers, but also more likely to be far removed from key infrastructural, institutional, and interpersonal links to regional and international markets. As a result, they face significant challenges to becoming competitive locations to host economic activity. Thus the geographical pattern of core and peripheral regions is increasingly manifest in an economic pattern of 'leading' and 'lagging' regions

Introduction: Rural and remote areas have a higher burden of disease, leading to inequalities in health between regional and urban areas. This article compares trends in health status and social determinants of health (SDH) in capital cities and the remaining areas of (rest of) states and territories in Australia, and examines the distribution of health and social determinants between metropolitan, inner regional, outer regional, rural and remote areas. Methods: We conducted an ecological analysis of Public Health Information Development Unit data for Australian capital cities, the rest of states and territories, and local government areas (LGAs). Trends in inequalities in capital cities and the rest of states and territories (regional, rural and remote) from 1986 to 2018 were assessed using the slope index of inequality. Data for 538 LGAs were classified into remoteness categories and scatterplots produced to assess differences in health and SDH both between and within remoteness categories. Results: Our analysis of trends found that premature and avoidable mortality and infant mortality decreased in all socioeconomic quintiles outside of capital cities. However, inequality in socioeconomic area disadvantage increased for premature and avoidable mortality. There were mixed trends in terms of SDH: higher increases in full-time participation in secondary education and internet access in the most disadvantaged quintiles led to decreases in inequality in urban and non urban areas. Inequality increased outside capital cities for income indicators, rental stress and labour force participation due to higher proportional gains for areas within the least disadvantaged quintile of area disadvantage. Inequality was higher in capital cities compared to the rest of states and territories in 2016 for rental and mortgage stress, welfare-dependent families and participation in tertiary education. It was higher in the rest of states and territories compared to capital cities for premature and avoidable mortality, labour force participation and internet access. We found that while rural and remote areas had worse health and SDH on average, there was heterogeneity in premature and avoidable mortality and SDH for outer regional, remote and very remote LGAs. Conclusion: Increasing inequality in health and SDH in outer regional, rural and remote areas underscores the ways in which health inequalities strongly correlate with inequalities in SDH. Variation in health and SDH within non-metropolitan areas suggests it May not be appropriate to clump regions and towns together when conducting analysis in Australia. Policies to improve rural and remote health need to enhance existing provisions of social and health infrastructure, with context-specific measures to reduce these health inequalities.