The effects of information sharing on moral hazard in credit markets - Evidence from a randomized evaluation in the Philippines

Last registered on December 20, 2022
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Pre-Trial

Trial Information

General Information

Title
The effects of information sharing on moral hazard in credit markets - Evidence from a randomized evaluation in the Philippines
RCT ID
AEARCTR-0002346
Initial registration date
July 24, 2017

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
July 24, 2017, 7:38 PM EDT

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

Last updated
December 20, 2022, 2:38 AM EST

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

Locations

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Primary Investigator

Name
Kristina Czura
Affiliation
University of Groningen
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Other Primary Investigator(s)

PI Name
Matthias Fahn
PI Affiliation
Johannes Kepler University Linz
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PI Name
Lisa Spantig
PI Affiliation
University of Essex
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Additional Trial Information

Status
On going
Start date
2016-03-09
End date
2024-12-31
Keywords
Finance & Microfinance
Additional Keywords
Information sharing, loan repayment, microfinance
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The increasing popularity of microfinance resulted in fierce competition in credit markets in many developing counties. Despite the favorable notion of competition in general, increased competition has led to new challenges. Recent studies find that higher levels of competition among microfinance institutions (MFIs) are related to over-indebtedness of borrowers and weakened loan repayment incentives. This might partly be driven by the absence of information sharing between lenders and the increase in competition which in turn results in greater information asymmetries in the markets. Information sharing via credit registries can thus be an important measure to improve the performance of microcredit markets and better access to credit for the poor. In this project we seek to answer the question how information sharing affects moral hazard in the credit market. We design and implement an information campaign regarding a private credit registry used by several microfinance institutions to increase knowledge on the existence of the credit registry among borrowers.
External Link(s)

Registration Citation

Citation
Czura, Kristina, Matthias Fahn and Lisa Spantig. 2022. "The effects of information sharing on moral hazard in credit markets - Evidence from a randomized evaluation in the Philippines." AEA RCT Registry. December 20. https://doi.org/10.1257/rct.2346-7.0
Former Citation
Czura, Kristina, Matthias Fahn and Lisa Spantig. 2022. "The effects of information sharing on moral hazard in credit markets - Evidence from a randomized evaluation in the Philippines." AEA RCT Registry. December 20. https://www.socialscienceregistry.org/trials/2346/history/166053
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
We design an information campaign to increase knowledge about a private credit registry that shares information on borrowers among microfinance institutions in the Philippines. The information campaign is conducted in lending centers of a partner microfinance institution that offers group loans in lending centers of 5 to 40 borrowers. The intervention is randomly assigned at the center level.
Intervention Start Date
2016-08-01
Intervention End Date
2016-08-31

Primary Outcomes

Primary Outcomes (end points)
Effort provision (in work/ household business),
Repayment,
Monitoring,
Peer pressure,
Usage of alternative credit sources,
Investments
Primary Outcomes (explanation)
The following variables will be constructed: effort, use of alternative credit sources, monitoring, and peer pressure.

For each variable, we have a set of questions from household surveys that adress different aspects.
In our analysis, we will use the individual questions as well as an index combining different questions to get a singular measure for 1) effort, 2) use of alternative credit sources, 3) monitoring, and 4) peer pressure.
For the index calculation, we use the ordinal alpha since we have 3-point Likert Scales (the commonly used Cronbach's Alpha is not applicable for Likert Scales with fewer than 5 points).
We also construct an index for competition as an explanatory variable.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We first elicit baseline values of variables of interest in a random subset of our study population via an individual survey. We then administer the above described intervention (i.e. information campaigns) in randomly selected centers. Shortly after the intervention, we re-survey the same individuals in the midline and approximately one year after the intervention, we administer the endline survey.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Borrowing centers consisting of 1-8 borrowing groups with 5 borrowers each
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
Number of borrowing centers included in study: 303
o Treatment 1: Standard campaign: 72
o Treatment 2: Detailed campaign: 75
o Treatment 3: Control campaign: 31
o Control: 125
Sample size: planned number of observations
We have two data sources: 1) Household phone survey with randomly selected clients from the participating centers. The planned number of borrowers being interviewed is 2000. Actual number of surveyed borrowers: in Baseline: 1941 in Midline: 1898 in Endline: currently ongoing 2) Administrative data on all clients in 303 participating centers from 2012 to 2017
Sample size (or number of clusters) by treatment arms
Treatment randomly assigned to borrowing centers with the following number of centers in each treatment
o Treatment 1: Standard campaign: 72
o Treatment 2: Detailed campaign: 75
o Treatment 3: Control campaign: 31
o Control: 125
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Commission, Department of Economics, University of Munich
IRB Approval Date
2016-02-03
IRB Approval Number
Project 2016-05 „The Effect of a Credit Registry on Moral Hazard”
Analysis Plan

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