Poverty In Cities Research Articles

Analysis of the Influence of Open Unemployment Rate, Road Infrastructure Development, Inflation, and Economic Growth on Poverty Levels in Mataram City (2010-2023)

Although economic growth had started to improve at the time due to the World Superbike (WSBK) event being held in Mandalika, the rising poverty rate in Mataram has continued to fluctuate. For example, in 2021, the city's poverty rate increased. Economic growth, inflation, and the construction of transportation infrastructure all partially and concurrently contribute to Mataram City's poverty rate. Descriptive and associative quantitative methods are used in this study. Using multiple linear regression analysis methodologies, secondary and time series data from According to the study's findings, just one factor—inflation—had a substantial impact on the poverty rate in Mataram, whereas the open unemployment rate, road length, and economic growth had no discernible effects. The poverty rate in the city of Mataram is significantly impacted by the open unemployment rate, road length, inflation, and economic growth all at the same time. The development of MSMEs based on the creative economy, the creation of an appropriate city road network that will be more beneficial to the community's economy, targeted fiscal policies to lower the rate of inflation, and other suggestions are some ways the Mataram city government can try to alleviate poverty, and designing the right strategy to optimize foreign trade.

Kunz and post-communist geographies of urban poverty in Romania

This article examines the spatial, social, economic, and civic dimensions of poverty in a post-communist Romanian city, focusing on the Kunz, an informal neighborhood in Timișoara. In Romanian, areas marked by concentrated poverty are pejoratively referred to as mahala, and internationally as, akin to the pejorative word, ‘slums’. This study sheds light on spatially concentrated poverty in post-communist cities through the lens of urban planning, citizenship, and environmental justice. Drawing on multiple research methods, the research reveals how environmental injustice is perpetuated by the lack of inclusive urban planning strategies, exacerbating existing poverty due to a continuous influx of impoverished populations from various regions. Exploiting legal uncertainties, these newcomers built homes without property deeds, subdividing older land plots. The strong socio-economic cohesion, basic urban infrastructure arrangements, temporary identity cards, and strong family ties within the community mitigate the fear of eviction from substandard housing. Economic crises generate a certain sense of security in the face of eviction as residents in these impoverished areas interpret crises as opportunities for safety. This sentiment prevails as substantial public investments are often delayed, reducing the likelihood of demolition and mass evictions, leaving the population nowhere else to turn.

Examining the indirect effects of acculturation stress on insomnia through rumination and alcohol use among Latinx women and men.

Acculturation stress, a type of sociocultural stress, is positively associated with insomnia among Latinxs; however, the mechanisms of this association remain elusive. We tested the indirect effects of acculturation stress on insomnia through rumination and alcohol use, two coping strategies associated with insomnia, and explored these effects in gender-stratified models among Latinxs. We analyzed cross-sectional data from 187 Latinxs participating in the Latino Sleep and Health study in New York City in 2016-2019. We conducted bias-corrected boot-strap tests of mediation with case resampling (1,000 replications) in aggregate and gender-stratified models. Acculturation stress and insomnia were measured continuously using the Hispanic Stress Inventory and Insomnia Severity Index (ISI). Rumination was measured using a subscale of the Ruminative Response Scale. The Quantity-Frequency Index was used to measure alcohol use. Covariates included age, New York City poverty threshold, and perceived stress. Participants were Mage 37.43 (SD = 13.67). Most participants were women (64.17%). The average ISI was 6.65 (SD = 5.51). The indirect effect of acculturation stress on insomnia through rumination was statistically significant (b = 0.02, 95% BCa CI [0.01, 0.03]). Among women, this indirect effect had slightly larger coefficients than among men (b = 0.02, 95% BCa CI [0.01, 0.04]; b = 0.01, 95% BCa CI [0.004, 0.04]). Alcohol use was not a statistically significant mediator (b = -0.001, 95% BCa CI [-0.004, 0.0002]). These findings suggest that psychological interventions focused on reducing rumination in response to acculturation stress may promote healthy sleep among Latinxs, particularly among Latina women. Future studies should use longitudinal study designs to determine the causal relationships among these variables. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Os efeitos do aquecimento global na ampliação das áreas desertificadas: um estudo acerca da geografia econômica dos municípios do sertão da Bahia e possíveis mitigações da teoria da tríplice hélice

Global warming, caused by the burning of fossil fuels and deforestation, is triggering significant changes in the Earth's environment. Phenomena like El Niño and La Niña, analyzed through modeling techniques, reveal complex patterns affecting various time scales. In regions with fragile soils, the trend is rapid progression towards scenarios of desertification and abandonment in the coming years. The migration of rural populations from these areas to urban centers, abandoning subsistence economies, may increase poverty in cities, a movement comparable to the Industrial Revolution's exodus, already visible in economic and social data. This article theoretically reviews topics related to desertification resulting from climate change, aiming to identify the social and economic consequences of this phenomenon in the region. Additionally, it explores possible actions to mitigate problems caused by global warming. In conclusion, a solution based on the Triple Helix Theory, which promotes interaction between government, universities, and businesses, will be presented. This approach could be crucial in mitigating the impacts of desertification, fostering sustainable development and innovation in the affected region.

Urban Agriculture’s ‘Invisible’ Short Food Value Chain: How Small-scale Farming Contributes to Johannesburg Food Security

AbstractUrbanisation into poverty in cities of the global South gives impetus to urban agriculture (UA) as a strategy to improve food security for low-income residents. This study disputes that UA is a trivial sector by arguing through the invisible short food value chain lens that it contributes to food security in local communities. The study adopted the extended case method that immersed researchers for more than a year to understand the practices of 11 farming entities and 20 of their customers in Johannesburg. Open-ended interview guides were administered to key informants from the city, provincial government, and non-governmental organisations. Findings show that UA increases food availability in local communities through the short food value chain. However, the local economy is undocumented and invisible to city stakeholders, negatively affecting their land use planning decisions for the sector. Though stakeholder consensus on UA is still lacking, the City of Johannesburg recognised UA’s potential and allocated both temporary and permanent land access arrangements for farming. Small-scale farmers lack the capacity to supply formal institutions, which can be overcome by intermediaries, such as civil society facilitation. The limitations of UA manifest in its inability to attract labour and keep records which inhibits its potential and support at the city level.

Ethnicity, social connectedness, and the rural-urban food continuum: Food security among urban informal settlement dwellers in Kenya

Rapid urbanization in developing countries is increasingly becoming an important development issue due to its negative effects on poverty and food insecurity in cities. This study investigated the determinants of the food insecurity gap among urban households living in informal settlements in Nairobi, Kenya, and the role of social connectedness and the rural-urban food continuum. Using panel data collected from 385 households using a two-stage cluster sample design, the study applied panel data regression and decomposition models to understand the factors affecting food insecurity access scores and weekly household food consumption expenditure. Descriptive results showed a score of 8.00 for the pooled sample on the household food access scale, with households from other regions having a lower score (7.94) than those from the Western region (8.32). 43 % of households from Western Kenya engaged in farming in rural areas (43 %) and had higher social connectedness (45 %) than households from other regions. The results indicate that dependency ratio, income, savings, social connectedness, rural visits, and dietary knowledge are significant factors impacting food security. Decomposition of levels and change in food insecurity revealed that endowments from the random effects model contributed to reducing the food insecurity gap between households originating from the Western region and those from other regions. The study highlights the importance of considering regional factors and promoting social connectedness and rural-urban linkages in addressing food insecurity in informal urban settlements.

Measurement and determinants of multidimensional poverty: the case of Hong Kong

ABSTRACT Multidimensional poverty in urban cities has received growing attention. In this study, the Alkire-Foster method was applied to examine multidimensional poverty in Hong Kong using a random sample of 1,476 Hong Kong adults in a cross-sectional population study undertaken in 2016–2017. Multidimensional poverty was measured on seven dimensions: education, health, mental health, housing, employment, social network, and subjective poverty. The adjusted headcount ratio gradually decreased, and the poverty intensity climbed while the cut-off value of multidimensional poverty increased. Education, employment and subjective poverty made the greatest contribution to multidimensional poverty. Logistic regressions were used to investigate the groups at risk of multidimensional poverty with different deprivation thresholds. Study results show that being female, single, older, a low income and deprived of necessities were risk factors of multidimensional poverty with various poverty cut-offs. Low income and deprivation of necessities correlated but did not overlap with multidimensional poverty. Our findings imply that poverty measurement should be multidimensional, and anti-poverty policy should be more targeted and diversified according to different groups’ risks of multidimensional poverty. The implications of these results and limitations are discussed.

Impact of the Human Development Index, Economic Growth, Investment, and Government Expenditure on the poverty of districts and cities in Bengkulu Province

The purpose of this research is to observe the influence of the human development index, economic growth, investment, and government spending on the poverty rate in districts and cities in Bengkulu Province. Data used as panel data for the period 2014–2020 The method of analysis used is panel data regression. Research results show that the human development index has a significant impact on poverty levels. Economic growth significantly affects the poverty level. Investment significantly influences the level of poverty. As well, government spending affects poverty rates in the Bengkulu City district.

Analysis of the Poverty Level Model for West Sumatra Province Using Geographically Weighted Binary Logistic Regression

Poverty is a widespread social problem that affects many developing countries, including Indonesia. The province of West Sumatra has a relatively low poverty rate of around 5.92 percent, making it the third lowest on the island of Sumatra. However, there are several districts and cities in this province that still have many people living in poverty. Various factors such as income levels, social conditions, and access to education, can contribute to the poverty gap in various regions. Geographically Weighted Binary Logistic Regression (GWBLR) is used to examine the relationship between poverty and geographic factors. GWBLR is a statistical analysis technique that takes geographic variables into account when the response variable is categorical or dichotomous. This approach incorporates a bandwidth-dependent weighting function. By conducting a fit test using R software, it is known that the Fcount value is greater than the Ftable value, indicating a significant difference between the logistic regression model and GWBLR. The results show that the GWBLR model with Fixed Gaussian Kernel weights is the most effective in analyzing poverty in the province. This model shows the lowest Akaike Information Criterion (AIC) value. Furthermore, this study identifies the Life Expectancy Variable as a significant factor affecting poverty in certain districts and cities in West Sumatra Province in 2022.
 

EFEKTIVITAS PROGRAM PENGEMBANGAN PEMBERDAYAAN MASYARAKAT PADA DINAS SOSIAL KABUPATEN PIDIE JAYA

All over the world, the increase in population in developing and developed countries is accompanied by the same problem, namely a decrease in the level of public services for the community. The phenomenon of poverty in Indonesian cities like Papua is one example. Papua owns 26.80% West Papua 21.43% East Nusaa Tenggara 20.23% Malukui 16.23% Gorontalo 15.51% Aceh 14.75% and other cities One way to improve people's welfare is through community empowerment. This study found that the Pidie Jaya District Office of Social Affairs played an important role in empowering the community by changing the way people think. The Pidie Jaya District Office of Social Affairs itself has attempted to empower the community by offering assistance to economically disadvantaged communities. This type of descriptive research, a qualitative approach, is used in this study. The results of the study show that the community empowerment program used by the Pidie Jaya District Office is still ineffective. How big or small the program depends on the wishes and resources of the community. Therefore, to carry out the Community Empowerment Development Program, the government and the community must work well together. Lack of agreement among the community, ignorance about how to look after, lack of knowledge about how to use rocks, and a very low budget are some of the obstacles that have prevented this program from being implemented. The advice that can be given in this study is that the Social Service Office of Pidie Jaya Regency The effectiveness of the Community Empowerment Development Program in Pidie Jaya Regency needs to be continued, by using a dynamic empowerment process or adapting to the typology of community empowerment and after each completion of a series of activities the community empowerment development program needs to be evaluated towards the development of community empowerment.Keywords : Effectiveness, Program, Community Empowerment Development

Comparison of Queen Contiguity and Customized Weighting Matrices on Spatial Regression to Identify Factors Impacting Poverty in East Java

Poverty is crucial problem that negative impact on all sectors, including economic, social, and cultural development in East Java Province. Poverty can also increase unemployment, crime, trigger social disasters and hinder progress East Java province. One efforts overcome problem of poverty in East Java province is detect factors that influence. This effort can be done through statistical modeling to determine factors that influence poverty in East Java province. statistical model that can identify factors that influence poverty and explain relationship between region and surrounding area is spatial regression analysis. In spatial regression analysis, spatial weighting matrix is needed to determine spatial influences between regions where one region influences neighboring regions. spatial weighting matrices that is often used is queen contiguity, and according to Anselin (1988:20), this spatial weighting also considers initial information, purpose of case studied, and theory underlying the research. This weighting uses social and economic variables case under study, namely customized weighting matrix. Based on results of this study, shows that best spatial regression and spatial weighting models are General Spatial Model (GSM) with customized weighting because customized weighting produces better estimation results than SAR, SEM and GSM models with queen contiguity weighting in district and city poverty modeling in East Java province with Akaike Infomation Criterion (AIC) value of 188.77 and detemination coefficient (R2) of 84.95%. School's Expected Time, Life Expectancy Score, and Employment Participation Rate are factors that will have substantial impact on percentage of population living in poverty East Java's districts and cities in 2021.

Level of Poverty in Cities and Regencies

This study analyzes the poverty rate of regencies/cities on the island of Sumatra using quantitative methodology. Panel data regression analysis techniques with Pooled least Square (PLS), Fixed Effect Model (FEM), and Random Effect Model (REM). The panel data in the study is a combination of time series data for 2010-2019 with cross-section data from 153 regencies/cities on the island of Sumatra. The purpose of the study was to find the best panel data regression model and determine the variables that affect the poverty rate of regencies/cities on the island of Sumatra. The results of the research analysis found a fixed effect model (FEM) as the best model for analyzing the poverty rate (P0) of regencies/cities on the island of Sumatra. Access to electricity, access to adequate drinking water, acquisition of GRDP and government capital expenditure are variables that have a significant impact on the poverty rate (P0). Access to sanitation and population are not variables that affect the level of poverty (P0). The managerial implications of the government prioritize increasing district/city GRDP to reduce poverty.

Patterns and determinants of multidimensional poverty in secondary cities: Implications for urban sustainability in African cities

Urban poverty research on African cities has focused mainly on megacities and large metropolitan areas. Despite their critical role in Africa's urbanization and development, secondary cities have received limited scholarly attention. Studies on secondary cities are unidimensional and rely mostly on secondary information from national census data. Using Wa, a secondary city in Ghana, this study assesses spatial patterns and determinants of multidimensional poverty, measured by two metrics: multidimensional poverty index (MPI) and multidimensional energy poverty index (MEPI). Spatially explicit primary data were collected from 775 households differentiated into core and fringe neighbourhoods. Mean MPI was significantly lower in core neighbourhoods than in fringe neighbourhoods. However, we found no statistically significant difference in MEPI between core and fringe neighbourhoods. The distribution of MPI is variably influenced by location and space but not MEPI. Although MPI was generally low, most areas with low MPI still had high MEPI, suggesting that energy access may be major problem even in secondary cities with low poverty. MPI was largely influenced negatively by household size and education. There was a significant negative relationship between MEPI and the food consumption score, suggesting a strong inverse relationship between food security and energy poverty. Together, the findings imply that scaling up the adoption of clean cooking energy in secondary cities can play a key role in addressing multidimensional urban poverty and advancing urban sustainability.

Measuring Urban Poverty Spatial by Remote Sensing and Social Sensing Data: A Fine-Scale Empirical Study from Zhengzhou

Urban poverty is a major obstacle to the healthy development of urbanization. Identifying and mapping urban poverty is of great significance to sustainable urban development. Traditional data and methods cannot measure urban poverty at a fine scale. Besides, existing studies often ignore the impact of the built environment and fail to consider the equal importance of poverty indicators. The emerging multi-source big data provide new opportunities for accurately measuring and monitoring urban poverty. This study aims to map urban poverty spatial at a fine scale by using multi-source big data, including social sensing and remote sensing data. The urban core of Zhengzhou is selected as the study area. The characteristics of the community’s living environment are quantified by accessibility, block vitality, per unit rent, public service infrastructure, and socio-economic factors. The urban poverty spatial index (SI) model is constructed by using the multiplier index of the factors. The SOM clustering method is employed to identify urban poverty space based on the developed SI. The performance of the proposed SI model is evaluated at the neighborhood scale. The results show that the urban poverty spatial measurement method based on multi-source big data can capture spatial patterns of typical urban poverty with relatively high accuracy. Compared with the urban poverty space measured based on remote sensing data, it considers the built environment and socio-economic factors in the identification of the inner city poverty space, and avoids being affected by the texture information of the physical surface of the residential area and the external structure of the buildings. Overall, this study can provide a comprehensive, cost-effective, and efficient method for the refined management of urban poverty space and the improvement of built environment quality.

How do energy forms impact energy poverty? An analysis of European degrees of urbanisation

The access that households have to various forms of energy depends on their level of urbanisation, which leads to distinct preferences in the forms of energy they consume. Consequently, different forms of residential energy consumption should have different impacts on energy poverty, when analysed for each degree of urbanisation. Verifying this was the underlying motivation for this study. Thus, it investigates how forms of residential energy consumption (oil, wood/biomass, natural gas, and electricity) impact energy poverty in (a) cities; (b) towns and suburbs; and (c) rural areas. To do so, data from 2005 until 2018 for twelve European countries was analysed using three-panel data sets, one for each urbanisation degree. The results, estimated using Feasible Generalised Least Squares, indicated that, in sparsely populated areas (towns, suburbs, and rural areas), primary energy sources, such as wood/biomass and natural gas alleviate energy poverty. Conversely, in cities, residential electricity consumption has been the key form for decreasing both poverty and energy poverty. The results of this research highlight that energy forms have differing impacts on energy poverty in areas with different levels of urbanisation. Therefore, energy policies should be planned at a disaggregated regional level within countries, and not at a national or European level.

Spatial identification of poverty in mountainous cities based on the mountain poverty spatial index: A case study of Ganzhou city in 2018 in China

Spatial identification of poverty in mountainous cities based on the mountain poverty spatial index: A case study of Ganzhou city in 2018 in China

PENGARUH IPM, RLS, TPT, DAN PENGELUARAN PERKAPITA TERHADAP KEMISKINAN DI PROVINSI JAWA BARAT

This study seeks to determine the influence of Human Development Index (HDI), Average Length of Schooling, Open Unemployment Rate, and Per capita Expenditures have on poverty in Cities in West Java Province during 2010 – 2020. This study uses a random effect model which is selected from three panel data processing methods through testing. The results showed that the HDI variables, the average length of schooling, the open unemployment rate and per capita expenditure together had an effect on the variation in the rise/fall of poverty. Simultaneously, the HDI variables, the average length of schooling, the open unemployment rate and per capita expenditure have a significant effect on poverty. Partially, the HDI variable and the average length of schooling have a significant effect on poverty. Meanwhile, the variables of the open unemployment rate and per capita expenditure have no significant effect on poverty.

The dynamics of socio-economic segregation: What role do private schools play?

Although residential sorting along socio-economic lines has increased in many cities across Europe, few studies have examined what drives changes in segregation over time. This study looks at the role of school choice expansion in shaping patterns of spatial inequality. We adopt a longitudinal perspective and investigate how the increasing availability of private primary schools is related to the dynamics of socio-economic segregation in German cities. Drawing on a uniquely compiled data set for the years 2005 to 2014 that includes 74 large and medium-sized cities with over 3500 districts, we estimate linear panel regression models with city fixed effects. The analyses show that an increase in the share of private primary schools is associated with a decrease in the segregation of poverty in West German cities but not in East German ones. The association in West Germany is particularly pronounced in local contexts characterised by growing rates of poor residents and growing proportions of young children. Results imply that school choice availability may promote residential integration and at the same time reinforce school segregation.

The Main Factors and Trends of Urbanization in Kazakhstan: Analysis and Recommendations

With the development of industry, the industrialization of agriculture, the strengthening of Industry 4.0 trends in all countries of the world, the trends of migration of rural residents to cities, and the pace of urbanization are increasing. The purpose of the article was to study the main factors determining the trends, intensity, and specificity of urbanization processes in Kazakhstan. The methods of retrospective analysis, analogies, logical analysis, generalizations, demographic and economic statistics, index, graphic, comparative analysis, absolute and relative indicators of demography and migration, methods of the theory of differentiated urbanization are used. Specific methods were applied to calculate the coefficients of urbanization intensity. To achieve the goal, a comparative analysis of theoretical views on trends and factors of urbanization was carried out. Based on statistical data, a comparative analysis of the birth rate, the level, and quality of life, the level of poverty in cities and villages of Kazakhstan was carried out. The dynamics, orientation, and territorial distribution of urbanization processes are revealed. To determine the hierarchies of cities depending on the population, Zipf curves were calculated, ranking of cities was carried out. It is concluded that the processes of urbanization in the country are uneven, as well as that the factors of urbanization are fully manifested in Kazakhstan’s conditions and determine its trends and intensity. Based on the identified trends and problems of urbanization, recommendations on the choice of the main directions and mechanisms for regulating the processes of urbanization in Kazakhstan are substantiated.

Poverty during Covid-19 Pandemic in Indonesia: A Case Study in Java-Bali Region

Indonesia has greatly affected by COVID-19 outbreak. This study shows that health crisis during COVID-19 pandemic has caused the rise of new poor seen from the increase of poverty rates, both at the national, regional, and local levels. The increase in poverty occurred in all provinces which is associated with the magnitude of pandemic. In this study, we highlight poverty in the provinces of Java-Bali region as the most affected areas of the outbreak. Among the 128 regencies/cities, the six top highest increase in poverty are regencies/cities that located in small islands and coastal regions. The highest increase was experienced by Kepulauan Seribu by 2,78% of increase. This follows by increase in Sampang Regency (2,07%), North Jakarta (1,74%), Bangkalan Regency (1,66%), and Indramayu Regency (1,59%) respectively. This study shows that the uncertainty in the time of COVID-19 has made precarity among productive working groups. Migrant workers especially in urban areas are more vulnerable due to ‘lockdown’ policies. In addition, we also found that poverty in small islands and coastal cities are severely affected. Further research needs to be done to elaborate this finding to anticipate poverty in Indonesia in the future when the uncertainty of COVID-19 continues to this day.