Spatial Consumption Inequality in Mozambique

In this paper we explore the temporal dynamics of spatial inequality in housing prices for Madrid, the capital city of Spain. Spatial inequalities are a concerning feature of urban areas across the globe. It has been suggested that within cities housing prices are becoming more geographically unequal over time, particularly since the 2008 housing market crash. However, more evidence is needed at the intra-urban level to understand neighbourhood house price differences in large urban areas. Changes are analysed during a key period of the housing market bust (2010–2015) and boom (2016–2019), using data from a major housing listing portal. Fine grain space-time analysis of the distribution of housing prices supports an increase in spatial inequality and polarisation at the neighbourhood level. Two spatially differentiated housing sub-markets of high- and low-priced housing are identified. The persistence and growth of spatial house price inequality has important societal implications for the wealth gap and segregation of rich and poor in cities.

Black Women Less Likely to Breastfeed: Narrowing Gap Could Shrink Infant Mortality Rate

Urban suburbia: Gentrification and spatial inequality in workers' communities in Tokyo

Emerging world countries have experienced over the last two decades a significant change in their trade patterns. Bold trade reforms have been followed by rapid rises in international trade levels. However, despite these radical changes, we know remarkably little about how changes in trade patterns are affecting the evolution of regional inequality in the developing world. This paper addresses the link between trade openness and spatial inequality across 22 emerging countries over the period between 1990 and 2006. Our findings show that changes in international trade bring about a significant rise in within-country inequality across the developing world and that this impact is greatest in the poorest countries. This result is robust to the inclusion of a number of control variables, and to changes in the specification of the sample and in the measure used to quantify the level of regional disparities. Consequently, the increase in trade exposure across the emerging world, while possibly benefiting the countries involved in the process in aggregate terms, is generating winning and losing regions.

In North-eastern Nigeria, the Gongola region has been one of the least developed since independence. The series of geopolitical reorganizations since 1967 which lead to the gradual and consistent decentralization of the processes of social, economic and political transformation and the reduction of spatial inequalities in development within the country appeared to have little impact on urban development in the region. The concern of this paper is to determine the pattern of urban development achieved in the region as a single administrative entity, to explore the specific and theoretical factors that were responsible for the existing pattern of urban development, and make suggestions on how to guide future planning to influence pattern of urbanization in the region, in the desired manner. To achieve these objectives, data were collected on eleven indicators of development in all the local government areas of the region and subjected to principal factor analysis, to most important form or spatial structure of regional development. The result generated five dimensions of regional development. The most important dimension identified i.e., urban infrastructure development, was subjected to spatial autocorrelation analysis (using the join-count statistics), in order to determine the likelihood of existence of any spatial association in the observed pattern. The result indicates that the pattern of urban infrastructure development appear to be associated with some deliberate and systematic process of public policy making that promoted urban development at the early stages of the region's political development. The result also shows that the general pattern of economic development in the region has tended to favour locations surrounding the more urbanized areas thereby introducing spatial inequalities and neglect of the more rural places. The paper suggests strengthening of a system of geopolitical growth centers in the more rural areas and the adoption of a grass root approach to Development Planning in the region as a panacea for redressing spatial inequalities in the regional development process. Keywords: Region, Development, Planning, Urban, Gongola. (Global Journal of Social Sciences: 2003 2 (1): 65-78)

This study analyzes the patterns and dynamics of income inequality across districts and municipalities in Aceh Province during the 2022–2024 period using data from the National Socio-Economic Survey (Susenas) published by Statistics Indonesia (BPS). A descriptive-comparative approach was employed with the Gini Ratio as the main indicator to examine spatial variations and inequality trends between urban and rural areas. The results show that Aceh’s Gini Ratio declined from 0.296 in 2022 to 0.294 in 2024, indicating a modest improvement in income distribution. The reduction in inequality mainly occurred in rural areas, while urban regions experienced a slight increase due to the concentration of economic activities among higher-income groups. Banda Aceh and Lhokseumawe recorded the highest inequality levels, whereas Aceh Tengah and Bireuen demonstrated relatively strong income equality. Overall, Aceh remains one of the provinces with low-income inequality in Indonesia but still faces challenges of structural disparities across regions. The findings highlight the need to shift policy orientation from redistributive equality toward productivity-based equality through regional economic integration, empowerment of micro and small enterprises, and the development of inclusive economic sectors to achieve equitable and sustainable growth..

This study explores how geographical factors shape El Salvador’s banking sector, particularly focusing on regional disparities, urbanization, and vulnerability to natural disasters affecting access to financial services. By employing a mixed-methods approach that combines quantitative data and qualitative interviews, the research analyzes how these geographical challenges impact financial inclusion and banking development. Data from the Central Reserve Bank of El Salvador and financial institutions is examined alongside Geographic Information Systems (GISs) to illustrate the spatial distribution of banking services. Interviews with stakeholders, including bank representatives and clients from urban and rural areas, reveal a significant urban–rural divide, with approximately 75% of bank branches and 80% of ATMs situated in urban centers, particularly in San Salvador. Rural areas face limited access to formal banking due to challenging topography and inadequate infrastructure, leading to increased financial exclusion and reliance on informal systems. Natural disasters further disrupt banking infrastructure and heighten the need for emergency loans. While urbanization has spurred financial growth, it has also resulted in informal settlements with restricted access to formal services. As its main contribution, this study provides one of the first in-depth, geographically grounded analyses of financial exclusion in El Salvador, offering original insights into how spatial inequalities and disaster vulnerability intersect to shape banking access and economic participation. The study calls for a more inclusive banking sector, recommending mobile and digital banking expansion, agent banking in underserved areas, and improved disaster risk management to enhance economic participation across all regions.

Spatial inequality of inclusive wealth in China and Japan

A substantial empirical literature documents the rise in wage inequality in the American economy. It is silent on whether the increase in inequality is due to components of earnings that are predictable by agents or whether it is due to greater uncertainty facing them. These two sources of variability have different consequences for both aggregate and individual welfare. Using data on two cohorts of American males we find that a large component of the rise in inequality for less skilled workers is due to uncertainty. For skilled workers, the rise is less pronounced.

We investigate whether sub‐Saharan African countries are affected by an “urban mortality penalty” repeating the history of industrialized countries during the nineteenth century. We analyze Demographic and Health Surveys from several sub‐Saharan African countries for differences in child and adult mortality between rural and urban areas. For the first decade of the 2000s, our findings indicate that child mortality is higher in rural than in urban areas for all countries. On average, child mortality rates are 13.6 percent in rural areas and 10.8 percent in urban areas. In contrast, average urban adult mortality rates (14.1 percent) have exceeded rural adult mortality rates (12.4 percent). Child mortality rates are on average 65 percent higher in urban slums than in formal settlements. Child mortality rates in slum areas are, however, still lower than or equal to those in rural areas for most countries in our sample.

With rapid urbanisation and concomitant rise in urban poverty, a better understanding of urban poverty and urban income dynamics has become an urgent priority. One in five poor households now live in urban Bangladesh and many more urban households are aspiring to be middle class yet vulnerable to falling back into poverty. Progress in reducing poverty has slowed in urban areas, particularly in larger cities. As a result, there are now more people living in extreme poverty in urban Bangladesh (3.7 million) than in 2010 (3 million). At current rates of urbanisation and poverty reduction, more than half of poor households will live in urban areas by 2030. This paper examines what can be learned about trends and drivers in urban poverty from recent nationally representative surveys. It also analyses additional data sources on the capital city, Dhaka, to shed light on spatial inequality within the city. The paper highlights the need for increased data collection and evidence on urban poverty to inform public policy to address this emerging challenge.

This chapter shows how to model the relationships between phenomena that differ in spatial density. It is a selective overview of econometric and machine learning methods that can capture the spatial density information of geo-located points and use it in estimation. The goal of those models is to explain the density with other factors. It works also in an opposite way: to check if density matters for other phenomena; that is, for understanding the situation—to know how density is created and how it impacts the surrounding; for monitoring—to understand if and how phenomena change under density changes; and for predicting the spatial trends of density, agglomeration, congestion, spatial inequalities, and cohesion when density changes. The chapter shows how to transform raw data in order to use the information from the neighbourhood of different densities, in circles or in grids. It presents two approaches, using AIC and Voronoi polygons, to dealing with the neighbourhood with spatial weight matrix in the case of point data. It also shows how Geographically Weighted Regression (GWR) works with data of different density and heterogeneity, using spatial drift, measuring spatio-temporal stability, and estimating GWR with Random Forest. It also presents the advanced models: bootstrapped spatial econometric models, which are a solution for large data estimation and out-of-sample prediction; models on gridded data, which are applied to spatial econometric and machine learning models; and the local elasticity models where density is the main input and output information.

ObjectiveThis study aimed at using survey data to predict skilled attendance at birth (SBA) across Ghana from healthcare quality and health facility accessibility.MethodsThrough a cross-sectional, observational study, we used a random intercept mixed effects multilevel logistic modelling approach to estimate the odds of having SBA and then applied model estimates to spatial layers to assess the probability of SBA at high-spatial resolution across Ghana. We combined data from the Demographic and Health Survey (DHS), routine birth registers, a service provision assessment of emergency obstetric care services, gridded population estimates and modelled travel time to health facilities.ResultsWithin an hour’s travel, 97.1% of women sampled in the DHS could access any health facility, 96.6% could reach a facility providing birthing services, and 86.2% could reach a secondary hospital. After controlling for characteristics of individual women, living in an urban area and close proximity to a health facility with high-quality services were significant positive determinants of SBA uptake. The estimated variance suggests significant effects of cluster and region on SBA as 7.1% of the residual variation in the propensity to use SBA is attributed to unobserved regional characteristics and 16.5% between clusters within regions.ConclusionGiven the expansion of primary care facilities in Ghana, this study suggests that higher quality healthcare services, as opposed to closer proximity of facilities to women, is needed to widen SBA uptake and improve maternal health.

Revisiting the Pigouvian tax in urban roads: Housing supply restrictions, leaking profits and spatial inequality

Local government reform, urban crisis and development in South Africa