Designing microcredit loans for agricultural farmers

Last registered on January 22, 2023


Trial Information

General Information

Designing microcredit loans for agricultural farmers
Initial registration date
January 06, 2023

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
January 22, 2023, 10:42 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.



Primary Investigator

Graduate School of Economics, Kyoto University

Other Primary Investigator(s)

PI Affiliation
Florida International University
PI Affiliation

Additional Trial Information

Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Despite the expansion of microcredit access, its outreach is still limited among farmers. Standard microcredit causes a timing mismatch between cash flow and credit flow for farmers. They have little income until harvest while standard microcredit requires weekly installment. This mismatch will cause underinvestment and borrowing for repayment, resulting in lower uptake rates. Further, agricultural investment is sequential while credit is disbursed in a lump-sum, inducing present-biased (PB) farmers to fail in setting aside a sufficient amount of the fund for later investment. We randomly offered three microcredit programs that differ in repayment and disbursement timing to tenant farmers: (1) standard microcredit, (2) crop credit that disburses credit in a lump-sum and requires a one-time repayment after harvest, or (3) sequential credit that disburses credit sequentially and requires a one-time repayment after harvest.
External Link(s)

Registration Citation

Kono, Hisaki, Abu Shonchoy and Kazushi Takahashi. 2023. "Designing microcredit loans for agricultural farmers." AEA RCT Registry. January 22.
Experimental Details


Traditional credit (T1): This is the standard microcredit product in which the full loan amount was disbursed at the beginning of the crop season, and borrowers were liable to repay the loan in regular weekly installments of equal amount, beginning from the first month after loan disbursement. The loan matured after the harvest, when farmers were supposed to pay the last installment.

Crop credit (T2): This product removes the weekly installment from Traditional credit (T1). The borrowers were required to repay the full amount at the end of the harvesting period, which corresponded to the due date of the last installment in T1.

Sequential credit (T3): This product modifies T2 by changing the schedule of loan disbursement. To match the sequence of agricultural investment, the disbursement was divided into three phases. Based on the bookkeeping exercise in the pilot survey, we set the limit of the first disbursement at 60% of the maximum loan size so that the remaining 40% was still available for late-stage investment. At the time of the second disbursement (one month after the first disbursement), borrowers could receive up to 20% of the loanable amount in addition to the unused loanable amount at the first disbursement. The third and final disbursement was made one month after the second disbursement. At each disbursement, borrowers could decide the amount they would like to receive as long as it was within the specified limit.

Sequential in-kind credit (T4): This product intends to strengthen the commitment function of T3 by disbursing the credit in kind such as seed and fertilizer (valued within the loanable amount).
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Uptake, credit size, investment
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
profit, other borrowings, default
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
After collecting the baseline data, we randomly assigned 200 members (4 members per group) to each of the four credit products (T1-T4). The remaining 200 members served as the control group. We stratified the individuals based on the score of economic status that would be correlated with the latent productivity. Specifically, we computed the score by factor analysis, where we include indicators for owning agricultural lands, owning livestock, owning productive assets, borrowing money in the last three years, having electricity connection, having latrine toilet, and housing conditions (if the house is made of mud), the area of agricultural land, and the years of education. We constructed a strata of five households with similar scores, and randomly divided the five households into five different treatment statuses.
Experimental Design Details
Randomization Method
Randomization done in office by a computer
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
1000 farmers
Sample size: planned number of observations
1000 farmers
Sample size (or number of clusters) by treatment arms
200 farmers T1, 200 farmers T2, 200 farmers T3, 200 farmers T4, and 200 farmers control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
0.28 standard deviation

Institutional Review Boards (IRBs)

IRB Name
Kyoto University, Graduate School of Global Sustainablity
IRB Approval Date
IRB Approval Number


Post Trial Information

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials