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Impact Evaluation of Agricultural Microcredit Product in Myanmar
Last registered on May 13, 2020

Pre-Trial

Trial Information
General Information
Title
Impact Evaluation of Agricultural Microcredit Product in Myanmar
RCT ID
AEARCTR-0005452
Initial registration date
May 11, 2020
Last updated
May 13, 2020 3:45 PM EDT
Location(s)

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Primary Investigator
Affiliation
University of Sydney
Other Primary Investigator(s)
PI Affiliation
Myanmar Economic Association
PI Affiliation
Yangon University of Economics
Additional Trial Information
Status
On going
Start date
2019-12-13
End date
2020-12-31
Secondary IDs
Abstract
We study the impacts of an agricultural microcredit product for smallholder farmers on farm investment, farm performance, broader measures of economic performance, and household welfare.
External Link(s)
Registration Citation
Citation
Oo, Khin Pwint, Russell Toth and Tin Tin Wai. 2020. "Impact Evaluation of Agricultural Microcredit Product in Myanmar." AEA RCT Registry. May 13. https://doi.org/10.1257/rct.5452-1.0.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
The intervention is the provision of a seasonal agricultural microcredit loan.
Intervention Start Date
2019-12-13
Intervention End Date
2020-06-15
Primary Outcomes
Primary Outcomes (end points)
Our theory of change is that seasonal agricultural microcredit loans should primarily be invested in agricultural activity. Since the loans are provided very close to planting season, they should lead to a genuine increase in access to finance for the winter agricultural season, rather than providing a slightly lower-cost source of financing. Hence loan recipients should have greater capital to invest in agriculture, rather than substituting for other loans.

Given their timing and purpose, we expect loans to be used on variable inputs such as seeds, fertilizer, and labor inputs. Hence we should see impacts on these agricultural investments, both in the monetary value invested in inputs, and the likelihood of accessing key types of inputs. It is also possible that access to loans would lead to a change in cropping patterns, e.g., devoting more land or investment to a more input intensive crop. So we will study the crop mix, but we don't have strong priors here.

In principle, increases in agricultural investment should lead to increases in agricultural productivity and outcomes, in particular, total yield, which can be measured in quantity terms (e.g., kilograms or volume-based measures of yield). Increases in yields should lead to increases in agricultural revenue. While loan recipients might also increase expenditure through use of loan proceeds, on net they should have higher profits than non-recipients.
Primary Outcomes (explanation)
Total agricultural revenue will be measured by adding up the revenue from individual crops. We will look also look at the revenue from the "main" (largest revenue) crop.

Total agricultural expenditure will be measured by adding up the expenditure from individual crops. We will look also look at the expenditure on the "main" (largest revenue) crop.

To calculate agricultural profit, we will subtract agricultural expenditure from agricultural revenue.

In some cases, the endline survey will be conducted before all farmers have harvested their winter season crop. In that case we will calculate their yield as the sum of what they have harvested so far, with what they still expect to harvest. Similarly, we will calculate their revenue as the sum of what they have sold so far, and what they still plan to sell.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary outcomes concern off-farm outcomes: non-farm business and earnings activity, household labour market outcomes, and broader outcomes for the household.

With respect to other economic activity, we will focus on investments and returns from non-farm businesses, and labour earnings.

With respect to other household outcomes, we will construct the Probability of Poverty Index (based on the Myanmar PPI), and calculate other monetary measures of household outcomes including expenditure on health and education, transfer receipts, and food security. In particular, we will look at a measure of 4-weeks' consumption, and likelihood of household needing to ration meals.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Access to agricultural microcredit is provided to a randomly-selected treatment group and not to a control group, within a set of farmers who showed interest in the agricultural microcredit product.
Experimental Design Details
Not available
Randomization Method
Randomization is done based on the last digit of farmers' National Registration Card (NRC) number, which is effectively random. Treatment-control was divided based on even-odd last NRC digits.
Randomization Unit
Individual borrower (representing an agricultural household).
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
21 villages.
Sample size: planned number of observations
453 borrowers (representing agricultural households).
Sample size (or number of clusters) by treatment arms
There are 356 treatment and 97 control. The distribution of treatment-control varies by cluster (village) as randomization was done at individual rather than cluster level.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Human Research Ethics Committee, University of Sydney
IRB Approval Date
2019-12-13
IRB Approval Number
2019/873