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Repayment Flexibility: Contract Choice and Investment Decisions among Indian Microfinance Borrowers
Last registered on September 16, 2019

Pre-Trial

Trial Information
General Information
Title
Repayment Flexibility: Contract Choice and Investment Decisions among Indian Microfinance Borrowers
RCT ID
AEARCTR-0002259
Initial registration date
June 08, 2017
Last updated
September 16, 2019 4:41 AM EDT
Location(s)

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Primary Investigator
Affiliation
Institute of Financial Management and Research (IFMR), Lead
Other Primary Investigator(s)
PI Affiliation
Institute of Financial Management and Research (IFMR), Lead
PI Affiliation
Assistant Professor, Warwick Business School, University of Warwick
Additional Trial Information
Status
On going
Start date
2016-04-01
End date
2019-12-31
Secondary IDs
Abstract
Repayment rigidity has been shown to be particularly unfavorable for microfinance borrowers, especially in terms of investment potential. This study proposes an innovative way for Microfinance Institutions (MFIs) to offer repayment flexibility in microfinance contracts, which uses contract price as a screening mechanism. The underlying intuition is that offering repayment flexibility as a more expensive contract option than the standard rigid contract can work as a screening instrument for lenders, with borrowers selecting into the contract that best suits their characteristics. This, in turn, can mitigate default rates. We design and set up a Randomized Controlled Trial (RCT) in Uttar Pradesh, India, to test this hypothesis: in treated branches, the lender offers a flexible repayment option along with the standard rigid contract, the former being more expensive than the latter. In control branches, only the standard, rigid contract is available.
Our experimental design allows us to study two things:
- By focusing on treatment branch only, we can look at borrowers’ selection into flexible vis-à-vis rigid contract by linking borrowers’ characteristics with contract choice
- By comparing treatment (contract choice) with control (only standard contract offered), we can study the impact of offering a flexibility option on business outcomes and repayment rates.
Our work specifically focuses on the design of microfinance contracts, and in particular on the introduction of flexible repayment schedules that can be profitable for both borrowers and the lenders. Second, it studies how borrowers select into different repayment schedules, based on their sensitivity to price and behavioral characteristics (time preferences, risk aversion, financial discipline), as well as on the value they give to continuing their relationship with the lender. In order to study borrowers’ selection, our experimental design does not “exogenously” assign borrowers to a flexible contract (as, for instance, in Field et al., 2013), but allows them to choose between a rigid and a flexible schedule, which are provided simultaneously by the lender.

External Link(s)
Registration Citation
Citation
Agarwal, Parul, Giorgia Barboni and Khushboo Gupta. 2019. "Repayment Flexibility: Contract Choice and Investment Decisions among Indian Microfinance Borrowers ." AEA RCT Registry. September 16. https://doi.org/10.1257/rct.2259-3.0.
Former Citation
Agarwal, Parul, Giorgia Barboni and Khushboo Gupta. 2019. "Repayment Flexibility: Contract Choice and Investment Decisions among Indian Microfinance Borrowers ." AEA RCT Registry. September 16. https://www.socialscienceregistry.org/trials/2259/history/53369.
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Experimental Details
Interventions
Intervention(s)
Once clients are ascertained to be eligible for the individual, standard “rigid” loan, customers in treated branches are offered the opportunity to choose between the product they are expecting to receive (i.e. the rigid contract) at 24% interest and a flexible contract offered at an interest rate of 26%.
This flexible loan gives the customers the opportunity to benefit from a three-month repayment holiday, to be exerted any time after the third month of the loan maturity. The first three instalments of the flexible contract require a monthly repayment. During the three-month repayment holiday, borrowers still needed to repay a small fee. Borrowers in control branches were only offered the standard rigid contract at 24%. This contract has been designed with our partner Microfinance Institution for the purpose of the study.
Intervention Start Date
2016-04-15
Intervention End Date
2017-06-15
Primary Outcomes
Primary Outcomes (end points)
In line with Barboni (2017), our primary outcomes of interest are repayment rates, business outcomes including sales, profits, investments (business assets), consumption (expenditures) as well as savings and borrowing. We also intend to study how preferences for repayment flexibility relate to customers’ characteristics, including risk aversion, time preferences, and personality traits.
Primary Outcomes (explanation)
We will construct a few outcome variables relating to customers’ behavioral traits. The main ones are time consistency and risk aversion. In the baseline and endline surveys, we play two sets of “lab-in-the-field games” to elicit respondent’s preferences.

Borrowers’ attitude towards risk is measured with a standard Multiple Price List (MPL). The MPL protocol consists of presenting the subjects with two different lotteries, Lottery A and Lottery B, entailing six decisions. Payouts are constant but the probabilities of success change from one decision to the other, with Lottery B being riskier than lottery A. Until round three, lottery A gives a higher expected value than lottery B. Starting from round four, Lottery B yields a higher expected value. Therefore, subjects who stay with Lottery A longer than three rounds display increasing levels of risk aversion. Conversely, subjects switching to Lottery B in the earlier rounds would display increasing levels of risk-loving behavior

In addition, customers’ intertemporal preferences are assessed using standard list choices. This protocol consists of two lotteries. In the first one, the respondent has to choose between a Rs. 200 sum to be paid the day after the interview and an equal or larger sum (Rs. 200, 240, 260, 280, and 300) to be paid one month later. The second lottery “shifted” the time horizon of the first lottery by three months. Combining the two lotteries not only allows one to estimate subjects’ discount rate, but also to detect any time inconsistency. If a subject preferred Rs. 260 one month later to Rs. 200 paid tomorrow, she should have also preferred Rs. 260 paid four months in the future to Rs. 200 paid three months in the future. This behavior is defined as “time consistent”. Still, preference “reversals” may emerge. For example, when a subject prefers Rs. 260 one month later to Rs. 200 paid tomorrow, but the choice is reverted for the later rewards, the subject is said to display hyperbolic discounting. Conversely, when a subject prefers Rs. 260 one month later to Rs. 200 paid tomorrow, but this choice is reverted for the earlier rewards, the subject is showing anti-hyperbolic discounting.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We randomize 28 branches of the partner institution in the state of Uttar Pradesh, India between control and treatment. Randomization of treatment and control branches was done at two stages – first for the 4 city branches and then the 24 non-city branches. The least squared distance method of randomization was adopted to assign branches to treatment and control. Additionally, the sampling distribution at each of the treatment and control branches was fixed in proportion to the average monthly number of loans disbursed at each of the branches. The randomization method adopted pairs branches together based on the minimum distance between two branches and randomly assigns them to treatment and control. Data is collected on a total of 800 households – 400 of whom have received the treatment intervention.
Baseline household survey is administered to the treatment and control clients once their loan is disbursed. Regular follow-ups are conducted via telephonic surveys to capture customers’ delinquencies/defaults. This is further cross checked with the administrative data from the partner institution. A midline survey is conducted half-way through the loan period (12 months post loan disbursal), and an endline survey will be conducted at the end of the 24 month loan period.
Experimental Design Details
Not available
Randomization Method
The least squared distance method of randomization was adopted to assign branches to treatment and control. The randomization method adopted pairs branches together based on the minimum distance between two branches and randomly assigns them to treatment and control.
Randomization Unit
Randomization of treatment and control branches was done at two stages – first for the 4 city branches and then the 24 non-city branches. The least squared distance method of randomization was adopted to assign branches to treatment and control. Additionally, the sampling distribution at each of the treatment and control branches was fixed in proportion to the average monthly number of loans disbursed at each of the branches.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
28
Sample size: planned number of observations
800 suggested, final sample size is 799.
Sample size (or number of clusters) by treatment arms
400 treatment clients across 14 treatment branches
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We believe the sample size of 790 clients in 28 branches, out of which 14 are in treatment, is high enough to attain a minimum detectable effect size of 0.41 or less for a significance level of 0.05 and a power of 0.90. Assumptions Case 1 Case 2 Case 3 Alpha Level (α) 0.05 0.05 0.05 Two-tailed or One-tailed Test? 2 2 2 Power (1-β) 0.9 0.9 0.9 Rho (ICC) 0.1 0.1 0.1 P 0.5 0.5 0.5 R12 0.4 0.3 0.25 R22 0.3 0.2 0.2 g* 4 4 4 n (Average Cluster Size) 29 29 29 J (Sample Siz [# of Clusters]) 28 28 28 MDES 0.38 0.41 0.41
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
School of Social Science and Philosophy ,Trinity college ,Dublin
IRB Approval Date
2014-08-27
IRB Approval Number
NA
Analysis Plan

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