Impact of Microcredit in the Philippines

Last registered on May 24, 2017


Trial Information

General Information

Impact of Microcredit in the Philippines
Initial registration date
March 13, 2014

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
March 13, 2014, 5:49 AM EDT

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

Last updated
May 24, 2017, 11:47 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.



Primary Investigator

Northwestern University

Other Primary Investigator(s)

PI Affiliation
University of Illinois at Urbana Champaign
PI Affiliation
Dartmouth College

Additional Trial Information

Start date
End date
Secondary IDs
This study is a long-term evaluation of the impact of microcredit in the Philippines. In partnership with two microcredit lenders, we introduced a credit scoring system that evaluates the credit worthiness of credit applicants. First-time borrowers who are marginally credit worthy are subject to a random credit decision where most receive an offer of credit but some are randomly rejected. By comparing those who were randomly approved for credit against those who were randomly denied, we will be able to measure the impact of access to microcredit.

This study is a follow-up to Karlan and Zinman (2010).
External Link(s)

Registration Citation

Karlan, Dean, Adam Osman and Jonathan Zinman. 2017. "Impact of Microcredit in the Philippines." AEA RCT Registry. May 24.
Former Citation
Karlan, Dean, Adam Osman and Jonathan Zinman. 2017. "Impact of Microcredit in the Philippines." AEA RCT Registry. May 24.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Consumption, business investment, household income, response to shocks, use of formal insurance
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We used credit scoring software designed in consultation with two microlenders in the Philippines to identify marginally creditworthy loan applicants. Some applicants receive a randomized offer of access to credit while others do not and we will compare these two groups to obtain an unbiased measure of the impact of access to microcredit. More details on the experimental design can be found in Karlan, Osman and Zinman (2013), "Follow the Money: Methods for Identifying Consumption and Investment Responses to a Liquidity Shock."
Experimental Design Details
Randomization Method
Randomization done by computer at time of loan application
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
4,032 loan applicants
Sample size: planned number of observations
4,032 loan applicants
Sample size (or number of clusters) by treatment arms
417 applicants in control group, 3,615 in treatment group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Yale University FAS Human Subjects Committee
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Intervention Completion Date
December 31, 2012, 12:00 +00:00
Data Collection Complete
Data Collection Completion Date
December 31, 2012, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
1,601 applicants
Final Sample Size (or Number of Clusters) by Treatment Arms
1,272 accepted applicants served as the treatment and 329 rejected applicants served as the comparison
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Measuring the impacts of liquidity shocks on spending is difficult methodologically but important for theory, practice, and policy. We compare three approaches for tackling this question: directly asking borrowers how they spend proceeds from a loan (direct elicitation); asking borrowers using a list randomization technique (indirect elicitation) that allows them to answer discretely in cases where loan uses are at odds with lender policies or social norms; and, a counterfactual analysis in which we compare household and enterprise cash outflows for those in a treatment group, randomly assigned to receive credit, to a control group. The counterfactual analysis yields an estimate that about 100% of loan-financed spending is on business inventory. For the direct and indirect elicitations, we find evidence of both strategic misreporting and “following the cash”: borrowers likely report what they physically did with cash proceeds, rather than counterfactual spending.
Karlan, Dean, Adam Osman, and Jonathan Zinman. 2016. "Follow the money not the cash: Comparing methods for identifying consumption and investment responses to a liquidity shock." Journal of Development Economics 121: 11-23.

Reports & Other Materials