Search Results Heading

MBRLSearchResults

mbrl.module.common.modules.added.book.to.shelf
Title added to your shelf!
View what I already have on My Shelf.
Oops! Something went wrong.
Oops! Something went wrong.
While trying to add the title to your shelf something went wrong :( Kindly try again later!
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
    Done
    Filters
    Reset
  • Discipline
      Discipline
      Clear All
      Discipline
  • Is Peer Reviewed
      Is Peer Reviewed
      Clear All
      Is Peer Reviewed
  • Series Title
      Series Title
      Clear All
      Series Title
  • Reading Level
      Reading Level
      Clear All
      Reading Level
  • Year
      Year
      Clear All
      From:
      -
      To:
  • More Filters
      More Filters
      Clear All
      More Filters
      Content Type
    • Item Type
    • Is Full-Text Available
    • Subject
    • Publisher
    • Source
    • Donor
    • Language
    • Place of Publication
    • Contributors
    • Location
702 result(s) for "microcredit"
Sort by:
The Microfinance Business Model
Recent evidence suggests only modest social and economic impacts of microfinance. Favorable cost-benefit ratios then depend on low costs. This paper calculates the costs of microcredit and other elements of the microcredit business model using proprietary data on 1,335 microfinance institutions between 2005 and 2009, jointly serving 80.1 million borrowers. The costs of making small loans to poorer clients are high, and when revenues fall short of costs, subsidies are necessary to deliver services to those clients on a sustainable basis. Using a method that accounts for the opportunity costs of all forms of subsidy, the analysis finds that the median institution receives five cents of subsidy per dollar lent and $51 of subsidy per borrower (in PPP-adjusted terms). Relatively low levels of median subsidy suggest that even modest benefits of microcredit could yield impressive cost-benefit ratios. The distribution of subsidies is highly skewed, however: the average subsidy per dollar lent is 13 cents, and the average subsidy per borrower is $248. The data show that subsidies per borrower are substantially higher for commercial microfinance banks and some non-bank financial institutions that make relatively large loans. MFIs organized as non-governmental organizations (NGOs), in contrast, generally rely less on subsidy.
The Miracle of Microfinance? Evidence from a Randomized Evaluation
This paper reports results from the randomized evaluation of a group-lending microcredit program in Hyderabad, India. A lender worked in 52 randomly selected neighborhoods, leading to an 8.4 percentage point increase in takeup of microcredit. Small business investment and profits of preexisting businesses increased, but consumption did not significantly increase. Durable goods expenditure increased, while \"temptation goods'' expenditure declined. We found no significant changes in health, education, or women's empowerment. Two years later, after control areas had gained access to microcredit but households in treatment area had borrowed for longer and in larger amounts, very few significant differences persist.
Six Randomized Evaluations of Microcredit: Introduction and Further Steps
Causal evidence on microcredit impacts informs theory, practice, and debates about its effectiveness as a development tool. The six randomized evaluations in this volume use a variety of sampling, data collection, experimental design, and econometric strategies to identify causal effects of expanded access to microcredit on borrowers and/or communities. These methods are deployed across an impressive range of locations—six countries on four continents, urban and rural areas—borrower characteristics, loan characteristics, and lender characteristics. Summarizing and interpreting results across studies, we note a consistent pattern of modestly positive, but not transformative, effects. We also discuss directions for future research.
Microcredit in Theory and Practice: Using Randomized Credit Scoring for Impact Evaluation
Microcredit institutions spend billions of dollars fighting poverty by making small loans primarily to female entrepreneurs. Proponents argue that microcredit mitigates market failures, spurs micro-enterprise growth, and boosts borrowers' well-being. We tested these hypotheses with the use of an innovative, replicable experimental design that randomly assigned individual liability microloans (of $225 on average) to 1601 individuals in the Philippines through credit scoring. After 11 to 22 months, we found evidence consistent with unmet demand at the current price (a roughly 60% annualized interest rate): Net borrowing increased in the treatment group relative to controls. However, the number of business activities and employees in the treatment group decreased relative to controls, and subjective well-being declined slightly. We also found little evidence that treatment effects were more pronounced for women. However, we did find that microloans increase ability to cope with risk, strengthen community ties, and increase access to informal credit. Thus, microcredit here may work, but through channels different from those often hypothesized by its proponents.
From Exclusion to Empowerment: Assessing Microcredit Impact on Women's Economic Life Improvement
This research investigates the economic lives of women, in Bahawalpur, the southern Punjab region of Pakistan, with a particular emphasis on personal empowerment. It examines the key features of microcredit, including loan duration, loan size, loan-related training, loan purpose, and loan type. Data is obtained through a survey and analyzed using multinomial logit and probit models. Worsen, same, and improved were the three categories of economic status used in the study. The findings suggest that the likelihood of a deterioration in the economic circumstances of women decreases as the loan duration increases. Indeed, the impact of loan purpose and loan size is not entirely evident; in certain instances, their impact has been determined to be somewhat weak or ambiguous. The findings indicate that the success of microcredit is contingent upon the loan’s structure, as well as the attendant support and availability of funds.
Estimating the Impact of Microcredit on Those Who Take It Up: Evidence from a Randomized Experiment in Morocco
We report results from a randomized evaluation of a microcredit program introduced in rural areas of Morocco in 2006. Thirteen percent of the households in treatment villages took a loan, and none in control villages did. Among households identified as more likely to borrow, microcredit access led to a significant rise in investment in assets used for self-employment activities, and an increase in profit, but also to a reduction in income from casual labor. Overall there was no gain in income or consumption. We find suggestive evidence that these results are mainly driven by effects on borrowers, rather than by externalities.
Microcredit Impacts: Evidence from a Randomized Microcredit Program Placement Experiment by Compartamos Banco
We use a clustered randomized trial and over 16,000 household surveys, to estimate impacts at the community level from a group lending expansion at 110 percent APR by the largest microlender in Mexico. We find no evidence of transformative impacts on 37 outcomes (although some estimates have large confidence intervals), measured at a mean of 27 months post-expansion, across 6 domains: microentrepreneurship, income, labor supply, expenditures, social status, and subjective well-being. We also examine distributional impacts using quantile regressions, given theory and evidence regarding negative impacts from borrowing at high interest rates, but do not find strong evidence for heterogeneity.
Factors Influencing Sustainable Poverty Reduction: A Systematic Review of the Literature with a Microfinance Perspective
This research examined factors that help microfinance achieve sustained poverty reduction based on a systematic literature review (SLR). A search was conducted on the SCOPUS database up to December 2023. After analyzing hundreds of documents, a subset of 30 articles was subject to in-depth analysis, exploring factors and corresponding measurement indicators for sustainable poverty reduction in microfinance contexts. This article emphasizes that sustained poverty reduction is a gradual process requiring ongoing efforts from both Microfinance Institutions (MFIs) and governments. Two key success factors are empowering borrowers and ensuring the microfinance programs themselves are profitable. When implemented in an integrated and coordinated manner, these factors can empower individuals to escape poverty by fostering self-employment and income generation, ultimately reducing dependence on external support. Additionally, the study highlights the role of personality traits in influencing long-term entrepreneurial success. The findings provide valuable tools for MFIs and policymakers. MFIs gain a practical framework to guide their interventions towards sustained poverty reduction. Policymakers can leverage the identified factors and indicators when designing and implementing microfinance policies with a long-term focus on poverty alleviation. This study breaks new ground by presenting an operational framework that categorizes and integrates two critical factor groups: empowerment and beneficiary profitability. Furthermore, it links these factors to corresponding measurement indicators within a unified framework, enabling a more holistic assessment of poverty reduction efforts.
What does your Facebook profile reveal about your creditworthiness? Using alternative data for microfinance
Microfinance has known a large increase in popularity, yet the scoring of such credit still remains a difficult challenge. Credit scoring traditionally uses socio-demographic and credit data, which we complement in an innovative manner with data from Facebook. A distinction is made between the relationships that the available data imply: (1) LALs are persons who resemble one another in some manner, (2) friends have a clearly articulated friendship relationship on Facebook, and (3) BFFs are friends that interact with one another. Our analyses show two interesting conclusions for this emerging application: the BFFs have a higher predictive value then the person's friends and secondly, the interest-based data that define LALs, yield better results than the social network data. Moreover, the model built on interest data is not significantly worse than the model that uses all available data, hence demonstrating the potential of Facebook data in a microfinance setting.