Impact of urban microfinance on the livelihood strategies of borrower slum dwellers in the Dhaka city, Bangladesh

Hossain, Basharat; Wadood, Syed Naimul

doi:10.1016/j.jum.2019.12.003

Cited by 14 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The data shows that the population is dominated by married, which is 54.98% (non-migrant) and 33.5 % (migrant). Most residents of the slum areas were married [25,26]. It is different from other studies, stating that the population is dominated by those living a domestic partnership, followed by unmarried, married, and divorced categories [9,27].…”

Section: Marital Status and Origincontrasting

confidence: 65%

Population characteristics and distribution patterns of slum areas in Palembang City: Getis ord gi* analysis

2020

View full text Add to dashboard Cite

The paper aims to describe the population characteristics and the distribution patterns of slums in Palembang City. The research employs a quantitative method with 382 respondents. The data are analyzed using cross-tabulation of IBM SPSS 23 to know the population characteristics. Meanwhile, the distribution patterns of slums are analyzed by observing the sample distribution through the proportional random sampling technique. It is carried out by calculating the number of buildings of each area and noting the coordinates of each sample using GPS essentials application. The data are recorded and inserted into the sample spots on the map, which were then analyzed using the High-Low Clustering Report of Getis Ord General Gi*, to see the distribution pattern, especially the cold spot and hot spot, through ArcMap 103 program. The research found that non-migrant married Moslems dominate the population of Palembang city, with the average occupation is labor or manual worker. The slum distribution forms a low cluster pattern, meaning that it has a low value. The value is due to the government’s effort to manage the city and the development of the market sector, limiting the slum distribution. Getis Ord Gi* analysis revealed that the slum area in the city center and within a dense population is a cold spot (low cluster), while those far from the city center yet are still crowded are hot spots (high cluster).

show abstract

Section: Marital Status and Origincontrasting

confidence: 65%

Population characteristics and distribution patterns of slum areas in Palembang City: Getis ord gi* analysis

2020

View full text Add to dashboard Cite

show abstract

“…Weekly and regular payments. These microfinance companies serve poor people without bank accounts [10].…”

Section: Literature Reviewmentioning

confidence: 99%

Shared Responsibility System Fails: Group Loans Have Higher Credit Risk in Microfinance Institutions

Syari’udin¹,

Astuti²,

Ambarwati³

et al. 2023

Advances in Social Science, Education and Humanities Research

View full text Add to dashboard Cite

This study aimed to examine the credit risk in microfinance institutions in Gunungkidul Regency, considering both internal and external factors that may affect the repayment ability of borrowers. The study used the Ordered Logit Model analysis to investigate the relationship between credit risk and loan types, gender, and education level of borrowers. The results indicated that group loans had a higher level of credit risk compared to individual loans, indicating that the shared responsibility system, which should encourage group members to repay loans on time, has become less effective. Moreover, male borrowers were found to be more at risk of default than female borrowers, and higher education levels were associated with lower credit risk. These findings have important implications for microfinance institutions to improve their credit risk management strategies and develop more effective loan products to minimize the credit risk of borrowers.

show abstract

“…Geophysical shocks compound the increase in urban poverty in Asian countries like Bangladesh and Indonesia (Table 1). (Hossain and Wadood 2020).…”

Section: Acknowledgmentsmentioning

confidence: 99%

“…Additionally, there are improvements in "housing, utility usages, water and sanitation" all having the potential to increase resilience (Hossain and Wadood 2020). MFIs in Bangladesh and Indonesia by and large focus their lending in urban areas.…”

Section: Acknowledgmentsmentioning

confidence: 99%

Building Resilience of the Urban Poor: The Potential for Disaster Risk Financing Solutions Used by Microfinance InstitutionsBuilding Resilience of the Urban Poor The Potential for Disaster Risk Financing Solutions Used by Microfinance Institutions

2022

View full text Add to dashboard Cite

This report shows how innovative finance solutions can bolster climate resilience in the fast-urbanizing Asia and the Pacific by helping microfinance institutions (MFIs) funnel emergency support to small and medium-sized businesses. Explaining why MFIs struggle to support vulnerable SMEs when climate or geophysical shocks hit, it explores how disaster risk financing (DRF) solutions can harness global financial and insurance markets to transfer risk and provide capital. It recommends ADB spearheads a regional facility to manage risk transfer and ensure MFIs receive the contingent capital and credit they need to help SME owners rebuild their businesses and livelihoods.

show abstract

Impact of urban microfinance on the livelihood strategies of borrower slum dwellers in the Dhaka city, Bangladesh

Cited by 14 publications

References 10 publications

Population characteristics and distribution patterns of slum areas in Palembang City: Getis ord gi* analysis

Population characteristics and distribution patterns of slum areas in Palembang City: Getis ord gi* analysis

Shared Responsibility System Fails: Group Loans Have Higher Credit Risk in Microfinance Institutions

Building Resilience of the Urban Poor: The Potential for Disaster Risk Financing Solutions Used by Microfinance InstitutionsBuilding Resilience of the Urban Poor The Potential for Disaster Risk Financing Solutions Used by Microfinance Institutions

Contact Info

Product

Resources

About