Korean Trust Fund for ICT4D Technological Innovations in Rural Malawi: A Field Experimental Approach

Transcription

1 GRANT APPLICATION Korean Trust Fund for ICT4D Technological Innovations in Rural Malawi: A Field Experimental Approach Submitted By Xavier Gine (xgine@worldbank.org) Last Edited May 23, Printed June 13, Basic Facts Country/Region Project Sector Malawi / Africa Finance OUI Amount Requested US$ 224,220 Primary Area Originating Dept/Division TTL Access DECRG Xavier Gine Narrative 1. Objective Provide brief overall project objective, including intended impact. (Max. 500 words) The incomes of smallholder farmers in developing countries are severely constrained by the inability to finance crucial inputs such as fertilizer and improved seeds, particularly for export crops. Credit supply in rural areas is limited by the absence of ready means to sanction unreliable borrowers and, conversely, to reward good borrowers with expanded credit. A central problem in many developing countries is the absence of a national identification system that would allow borrowers to be uniquely identified. Arrangements with commodities traders to forward loan balances to lenders when farmers sell their crop are a common strategy to try to reduce default, but lenders cite many cases in which borrowers apply for a loan under one name and sell their production of tobacco or paprika under another. This deception, possible in the absence of positive identification, makes it impossible for the lender to deduct the loan repayment from the proceeds of the crop sales. In addition, defaulters can largely avoid future sanctions by simply applying for new loans under yet another different name. As a result, credit for agricultural purposes in Malawi is limited. This creates a situation in which farmers are frequently credit constrained and profitable investments must be foregone. This pilot project, aims to demonstrate how biometric technology can help improve the functioning of rural credit markets in Malawi by providing a way to uniquely identify borrowers. In particular, the project asks whether fingerprinting of borrowers coupled with the use of fingerprint-based credit history databases can help lenders withhold credit from past defaulters, and expand credit to borrowers who have proven reliable, as well as increase borrowers incentives to repay their loans. In essence, the project assesses whether biometric technology improves the enforcement of loan contracts by making the threat of future credit denial more credible, thereby improving repayment. By imposing discipline in the credit market, biometric technology could reduce the risks in lending and lower

2 the costs of making loans to poor farmers. The longer term objective of the program is to demonstrate the desirability and feasibility of establishing a credit bureau in Malawi based on biometric identification. The project also explores a series of interlinked questions. How does biometric identification affect the farmer s decision to take out a loan? And what impact does biometric identification have on farming practices, such as input utilization, use of family labor, and use of hired labor? 2. Rationale Indicate the innovative features of the project and how it plays a catalytic role in Bank Group operations. In what way does it have an impact on core Bank business? (Max. 250 words) 3. Program Description Describe project design including approach, components, resources stakeholder roles, etc. (Max words) This project complements and extends the existing portfolio of Bank projects on agricultural development in Malawi and is also consistent with the Bank s Malawi Country Assistance Strategy, which emphasizes the importance of strengthening rural financial markets to improve the livelihoods of rural households. For these reasons, the project has received the strong support of the Malawi CMU. The impact of biometric technology is measured using the statistical gold standard in social sciences, which is to perform an experiment with randomized treatment and control groups. Each participating farmer club (group of farmers in a village that grow a particular crop) is be randomly assigned to either the treatment or the control group. Random assignment allows us to identify the causal effect of the intervention, as opposed to differences between clubs that are due to other factors. We started working with MRFC, a public microfinance institution that operates in rural areas, in May By that time, we knew that MRFC was updating the credit MIS to a system that would allow using biometric technology and were assured that it would be up and running before the main agricultural season that would start in September/October. As it turns out, by mid summer it became clear that they would not be ready updating their systems so using funds from a World Bank grant, we decided to purchase a few laptops and scanners, as well as a simple software that would allow the recording of the fingerprints of prospective borrowers. In August 2007, fifty percent of farmer clubs in the study were selected by lottery to have their fingerprints recorded at the time of loan disbursement. Fingerprinted farmers were administered an educational module that explained how their fingerprint could uniquely identify them for credit reporting to all major Malawian rural lenders. The training emphasized that defaulters faced exclusion from future borrowing. The control group was not fingerprinted, but did receive an analogous training emphasizing the importance of one s credit history and how it influences one s future credit access. The process was a bit ad-hoc, although we made sure that MRFC credit officers were always present when we collected the data so that farmers would associate the recording of data to MRFC. Now MRFC has fully upgraded the systems and is looking to integrate the use of biometric information into their main protocols. Our dataset of fingerprints is compatible with MRFCs MIS so the data collected can be uploaded into their systems. We are seeking funds to purchase a few point-of-sales devices that can be used as they screen and disburse loans this upcoming September. In this context, as is the case in most sub-saharan Africa, credit supply has been limited due to difficulties in enforcing sanctions against defaulters. Fingerprinting raises the effective cost of default for borrowers because it makes it easier for financial institutions to withhold new loans from past defaulters, and to reward responsible past borrowers with new and expanded credit. In this new environment, individuals with a low likelihood of repaying should intentionally refrain from borrowing since they will lose the opportunity to borrow in the future in the event of default. Borrowers should also have greater incentives to ensure that production is successful, either by exerting more effort or choosing less risky projects, and when production is sufficient to cover the loan repayment should be less likely to default intentionally or opportunistically. Therefore, the key questions and hypotheses that the project will address are the following: 1) How does biometric identification affect the decision to take out a loan? If farmers believe that biometric identification raises the cost of default, it should deter some farmers from borrowing in the first place (specifically, those with private information that their likelihood of default is high). 2) What impact does biometric identification have on farming practices, such as input utilization, use of family labor, and use of hired labor? When the consequences of default are higher, farmers may use more inputs and exert more effort to reduce the probability of having to default on the loan.

3 3) What impact does biometric identification have on repayment? This is the most obvious area of impact farmers should be more likely to repay if the consequences of default are higher. A credible experimental estimate of this effect can be used in cost-benefit analyses of investments in biometric technology by rural lenders. It is important that biometric technology be integrated into MRFCs systems because farmers that were fingerprinted have been told that they will not be able to get another loan from MRFC if they default in the current one because they will be identified as they try to access a new loan. If the technology is not ready by next September, the threat of future credit denial that we have created could turn into a bluff. The study includes a sufficient number of units so that the treatment group is statistically distinguished from the control group. In this context, the unit of analysis is the farmer club because it would be problematic for within-club group dynamics to administer a treatment to some farmers and not others within the same club. Our power calculations indicates that to understand the impact of the biometric technology we require 250 farmer clubs of 15 members on average, for a total of 5,250 farmers. MRFC and Cheetah Paprika, the buyer of the produce from participating farmers, are carrying out the project among paprika farmers in four districts of central Malawi: Kasungu, Dowa, Mchinji and Dedza. Each of these areas has a well-functioning branch of MRFC as well as sufficient numbers of paprika farmers to be enrolled in the study. The project will conduct surveys of borrowers to measure the impact of the various interventions. These data will complement internal administrative data of the partner institutions. A follow-up survey (in 2009) will continue to track savings, input use, and agricultural decision-making more generally. The survey will also include modules typically included in full socioeconomic household surveys modeled after the World Bank Living Standards Measurement Surveys (LSMS). Key outcomes will include broader measures of well-being in households, such as income, nutrition, health, and child schooling. 4. Program Duration Indicate the expected duration of the project. 5. Fit with Strategies Describe how project fits with or supports sector, regional and country strategies. Highlight any relationship to an existing Bank operation or program. (Max. 500 words) 15 months The evidence that the project brings to light has the potential to have an important influence on the Bank and government policy in Malawi. First of all, by measuring the positive impact of biometrics on loan repayment rates, the project could help catalyze the establishment of national credit reporting agencies that use fingerprints as the unique identifier. In addition, improved access to credit has the potential to dramatically improve the ability of smallholder farmers to raise crop yields and to expand their participation in commercial agricultural markets. By showing how expanded financial services in rural areas can help farmers afford fertilizer and other inputs on their own (thereby raising their own incomes), the project can identify alternative government policies that would raise food security and the well-being of poorer farmers. The evidence generated by the project could help build support for scaling down or eliminating distortionary fertilizer subsidies (such as Malawi s) and replacing them with more market-based solutions to rural poverty. Target Countries 6. Target Countries Asia: Africa: Latin America: Middle East & North Africa: Europe & Central Asia: Categorization

4 7. ICT Program Areas Select all applicable program areas and categorization. Access: Connectivity for Rural and Underserved Areas Technology Convergence Low-Cost ICT User Devices or Services Innovative ICT Services and Applications ICT Infrastructure Development Mainstreaming: Agriculture and Rural Development Social inclusion and development Innovation and Entrepreneurship: Regional Scope: AFR 8. Deliverable Type Pilots and Demonstration Projects 9. Activity Executed By World Bank Key Stakeholders 10. Key Stakeholders and Other Interested Parties Please list key stakeholders and other interested parties, both recipients and beneficiaries, in the government, private sector, and elsewhere. Government Private Sector (Large) Private Sector (SME) Other Recipients Malawi Rural Finance Company (MRFC) Opportunity International Bank of Malawi (OIBM) Cheetah Paprika Ltd. Beneficiaries Timeline & Milestones 10. Estimated Timeline & Activity Milestones Please include titles and completion dates for each deliverable. Estimated Start Date Deliverables Biometric information is uploaded onto MRFC banking MIS. Purchase of POS devices. Training of MRFC staff on the use of POS devices and biometric technology Loan applications are collected. Farmers are identified using biometric technology. Credit decisions are made. Follow-up survey to determine impact of treatments on input use and other farm decisions. Full household socioeconomic survey to determine impact of treatments on farm profits and other household outcomes. Analysis of data and write-up of report Estimated End Date Date 1 Jul, 31 Jul, 30 Aug, 15 Oct, 31 Mar, Oct, Mar, Mar, 2010

5 Risks 11. Risks Affecting Project Implementation Identify and explain briefly major risks (including political, environmental, security, governance, and implementation) to project implementation, and measures to address these risks. Type of Risk Brief Description Measure to Mitigate Risk Training of MRFC staff conducted too late season If MRFC is not properly trained in the use of the new technology, the project could be undermined. Ensure that POS are purchased on time and that training takes place in advance of loan application process. Program Team 12. Program Team Please provide names of all principal team members. Core Team Members Transaction leader/ contact person Other team members (including back-ups) Xavier Gine Name(s) Dean Yang (U. Michigan), Santhosh Srinivasan (consultant, WB) Management Team Managing unit manager Director Xavier Gine Martin Ravallion Name(s) Financing Plan 14. Budget/Financing Plan Please enter the column totals from the spreadsheet template here. Column Total Amount (US$) KTF Request 224,220 Co-financing 111,000 World Bank Group 22,500 Total Cost 357,720 Monitoring & Evaluation 15. Outputs Please fill in the key measurable performance indicators for each component. These M&E milestones need to include base line data, expected value and intermediate achievements (collected during supervision). Measurable Indicators Baseline Value Intermediate Value Expected Final Value Increased Access to credit $5 M $6M $7M Repayment rate improves Creation of Credit bureau No Yes

6 16. Outcomes By project component please enter the tasks to be performed, their outcomes and their expected long term impact. Project Activities The project being a pilot is designed to achieve the stated outputs. Expected Outcomes Expected Impacts