Showing 1 – 7 of 7 results.
Self-published
Restricted
Indian Chit Fund (ROSCA) Ledger Data: Monthly Bidders and Winners (ICPSR 251425)
Released/updated on: 2026-07-28
Time period: 2020-05-31--2026-01-24
This dataset contains transcribed monthly auction records from 13 complete chit fund cycles operated by a nationally registered chit fund provider bank in Bangalore, India, between 2020 and 2026. A chit fund is a rotating savings and credit association (ROSCA) in which a fixed group of subscribers contributes a fixed monthly installment for a fixed number of months; each month the pooled sum is awarded to one subscriber through a competitive auction, in which subscribers bid a discount they are willing to forgo in exchange for receiving the pot early. The discount, net of the fund organizer's (foreman's) commission, is redistributed as a dividend to all subscribers, reducing their subsequent installments. The data were transcribed by hand from the provider's original paper auction ledgers and record, for every subscriber present at every auction in each cycle, whether and how much they bid, whether they won that auction, and the resulting financial breakdown of the pot (prize, commission, dividend, and net payment). The 13 cycles were randomly selected to span 7 distinct chit series/plan types offered by the provider, ranging in chit value from ₹50,000 to ₹900,000 and in duration from 20 to 30 months. The dataset is intended to support research on informal/semi-formal credit markets, auction behavior, and household saving and borrowing strategies in urban India. All subscriber, foreman, and provider identities have been anonymized; no attempt should be made to re-identify any individual or entity represented in the data.
Self-published
Locking crops to unlock investment: Experimental evidence on warrantage in Burkina Faso (ICPSR 251101)
Released/updated on: 2026-07-08
Geographic coverage: Burkina Faso
Time period: 2013-09-01--2015-09-30
Warrantage is an innovative model of rural finance with the potential to overcome credit, crop storage, and behavioral constraints through a localized inventory credit system. Using a randomized controlled trial varying household level access to warrantage, we measure its impacts among households interested in participating. Among treated households, take-up of storage is high, while credit take-up is moderate. Treated households primarily store grains sell their production over an extended period, at a time when prices are higher resulting in higher sales revenue. Increased incomes are spent on long-term investments, including education, livestock, and agricultural inputs for the subsequent year.
Self-published
Reducing Emission of CO2 from Africa’s Tropical Forests: A Randomized Controlled Trial (ICPSR 221102)
Released/updated on: 2025-02-28
Geographic coverage: Tanzania
This paper evaluates the impact of distributing high-cost LPG stoves to urban households through subsidy and on credit in a randomized controlled trial set up on charcoal consumption, CO2 emission, and cooking time. The paper finds that the treatment group (credit and subsidy combined) reduced charcoal consumption by 28.7 percent 15 months after the intervention, corresponding to an average aversion of 3.78 MT of CO2/household/year. The two treatments are not statistically significantly different. However, a social cost-benefit analysis suggests that the benefit of the stoves is 30-fold larger than their cost under credit and 19-fold larger under subsidy, which indicates that credit is the most socially effective instrument for supporting LPG interventions. The paper also documents that LPG stoves reduced cooking time by 68.5 percent 15 months after the interventions. The findings suggest that access to micro-finance is a promising venue for promoting energy transition and addressing the adverse effects of biomass fuel use in developing countries.
Self-published
Data and Code for "Does team competition increase pro-social lending? Evidence from online microfinance" (ICPSR 135641)
Released/updated on: 2021-04-03
Time period: 2006-02-01--2012-10-31
This project contains the data collected and analysis used for the paper "Does team competition increase pro-social lending? Evidence from online microfinance," published in Games and Economic Behavior.
The paper investigates how team competition affects pro-social lending on the microfinance website kiva.org. First, field data is used to show that lenders who join a team make 1.2 more loans to entrepreneurs in developing countries through Kiva than those who do not join a team. Second, a large-scale randomized field experiment is run through team forums to show that lenders make more loans when exposed to a message that combines goal-setting and coordination, and that goal-setting alone can increase lending of previously inactive teams.
Materials included are:
1) 4 Stata .dta files containing the data
2) 1 Stata .do file containing the analysis code
Self-published
“I Loan Because...": Understanding Motivations for Pro-Social Lending (ICPSR 101940)
Released/updated on: 2018-03-17
Geographic coverage: Earth
As a new paradigm of online communities, microfinance sites such as Kiva.org have attracted much public attention. To understand lender motivations on Kiva, we classify the lenders’ self-stated motivations into ten categories with human coders and machine learning based classifiers. We employ text classifiers using lexical features, along with social features based on lender activity information on Kiva, to predict the categories of lender motivation statements. Although the task appears to be much more challenging than traditional topic-based categorization, our classifiers can achieve high precision in most categories. Using the results of this classification along with Kiva teams information, we predict lending activity from lender motivation and team affiliations. Finally, we make design recommendations regarding Kiva practices which might increase pro-social lending.
Self-published
Recommending teams promotes prosocial lending in online microfinance (ICPSR 100358)
Released/updated on: 2016-12-11
This paper reports the results of a large-scale field experiment designed to test the hypothesis that group membership can increase participation and pro-social lending for an online crowdlending community, Kiva. The experiment uses variations on a simple email manipulation to encourage Kiva members to join a lending team, testing which types of team recommendation emails are most likely to get members to join teams as well as the subsequent impact on lending. We find that emails do increase the likelihood that a lender joins a team, and that joining a team increases lending in a short window (one week) following our intervention. The impact on lending is large relative to median lender lifetime loans. We also find that lenders are more likely to join teams recommended based on location similarity rather than team status. Our results suggest team recommendation can be an effective behavioral mechanism to increase pro-social lending.
Curated
Simple Crosstabs
Poverty Assessment and a Comparative Study of Rural Microfinance Institutions and Government Programmes in Ghana (ICPSR 35296)
Released/updated on: 2014-08-07
Geographic coverage: Ghana
Time period: 2004-02-01--2004-06-30
This data collection assessed the delivery strategies of microfinance institutions (MFIs) in Ghana with the aim of identifying best practices to guide operations of the industry. The specific objectives of the study were to assess the socio-economic profiles of clients of selected MFIs and non-client households, assess the poverty levels of MFIs' client households in relation to the non-client sample, and to make recommendations for policy and planning with a view to strengthening the delivery of MFIs poverty-related programmes. Demographic information collected includes sex, age, education and health status of all household members, marital status, religion and occupation of adult household members aged 15 and above and ethnic group of household head. Other components of the study instrument were: footwear and clothing expenditure, food-related indicators, dwelling-related indicators, other asset-based indicators, and other living standards indicators.