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DELIVERING CONDITIONAL CASH TRANSFERS VIA SAVINGS ACCOUNTS: DEFAULT AND MENTAL ACCOUNTING MECHANISMS
Last registered on May 06, 2014

Pre-Trial

Trial Information
General Information
Title
DELIVERING CONDITIONAL CASH TRANSFERS VIA SAVINGS ACCOUNTS: DEFAULT AND MENTAL ACCOUNTING MECHANISMS
RCT ID
AEARCTR-0000368
Initial registration date
May 06, 2014
Last updated
May 06, 2014 12:39 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
Case Western Reserve University
Other Primary Investigator(s)
PI Affiliation
El Colegio de México
Additional Trial Information
Status
In development
Start date
2014-04-28
End date
2015-08-15
Secondary IDs
Abstract
Our study aims to test whether and how mental accounting and default mechanisms improve the ability of poor households to save in the formal financial system, cope with negative shocks, and invest in health and education. We are also interested in testing whether making the financial lives of the poor easier has an effect on their cognitive system, and if this, in turn, affects their welfare. Designing savings tools that help the poor to save is a global challenge that could benefit many. The Mexican antipoverty program Oportunidades delivers conditional cash transfers (CCTs) to its beneficiaries via direct deposits into savings accounts. We plan to exploit this key feature of the program to evaluate the potential of default and mental accounting mechanisms for a vulnerable population. Part of the sample will keep receiving their CCTs as usual, another part will be offered an account labeled for emergencies, and another part will be offered the account labeled for emergencies with the possibility of getting automatic deposits into their account.


External Link(s)
Registration Citation
Citation
Chiapa, Carlos and Silvia Prina. 2014. "DELIVERING CONDITIONAL CASH TRANSFERS VIA SAVINGS ACCOUNTS: DEFAULT AND MENTAL ACCOUNTING MECHANISMS." AEA RCT Registry. May 06. https://doi.org/10.1257/rct.368-1.0.
Former Citation
Chiapa, Carlos and Silvia Prina. 2014. "DELIVERING CONDITIONAL CASH TRANSFERS VIA SAVINGS ACCOUNTS: DEFAULT AND MENTAL ACCOUNTING MECHANISMS." AEA RCT Registry. May 06. https://www.socialscienceregistry.org/trials/368/history/1673.
Experimental Details
Interventions
Intervention(s)
We will randomize access to a savings aaccount labeled for emergencies and access to a savings account labeled for emergencies with the possibility of making automatic deposits.
Intervention Start Date
2014-06-02
Intervention End Date
2015-05-29
Primary Outcomes
Primary Outcomes (end points)
Usage of the emergency savings account, total savings in the emergency savings account and overall household savings, households’ ability to cope with shocks, and investments in health and education. We are also interested on the treatment effects on individuals cognitive resources, mental health, and stress levels.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We will conduct a field experiment in collaboration with Oportunidades and BANSEFI, the bank that processes the CCTs and offers and manages the savings accounts. We will randomly assign sample localities to a treatment arm. Beneficiary households in some selected localities will be offered a savings account labeled for emergencies and beneficiary households in other selected localities will be offered a savings account labeled emergencies with the possibility of getting automatic deposits into their account.
Experimental Design Details
Randomization Method
By a computer
Randomization Unit
Locality
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
59 localities
Sample size: planned number of observations
5,407
Sample size (or number of clusters) by treatment arms
15 control localties, 22 localities in each treatment group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We made the following assumptions: a power of 0.8 and a significance level of 0.05; an intra-cluster correlation of 0.006;* and an average take-up rate of the savings account denominated for emergencies and savings by default of 25% (based on take-up rates of other savings accounts in developing countries**). We consider as outcome variable self-reported savings in BANSEFI by Oportunidades beneficiaries who were given a debit card to manage their transfers. The data comes from INSP (2012). On average, beneficiaries report having MX$12.48 (standard deviation MX$271.67) saved in their accounts. We assume this to be the level of savings for the control group. Under the assumptions above, in order to detect a statistically significant difference of 0.2 standard deviations, considering 59 clusters (15 for the control group and 22 for each treatment group), we would need at least 20 complying households in each cluster.*** Considering the control group and assuming a 15% non-response rate at baseline, the number of households to be surveyed in each control locality is 24 (20/0.85). In addition, assuming a 15% attrition rate between baseline and endline, the number of households to be surveyed in each control locality is 29 (24/0.85 = 28.24 ≈ 29). Now, turning to the treatment groups, following the same reasoning and assuming a take-up rate of 25%, the number of households to be surveyed in each treatment locality is 113 (28.24/0.25 = 112.96 ≈ 113). Thus, we will interview 435 beneficiaries in the control group (29*15) and 4,972 in the two treatment groups (113*22*2). Hence, our total sample will be of 5,407 beneficiaries. Footnotes: * This value was obtained using the loneway command in STATA. The data used are self-reported savings kept in BANSEFI by Oportunidades beneficiaries who were given a debit card to manage their funds. The data comes from INSP (2012). ** Ashraf, Karlan and Yin (2006) find that for the Philippines, 28% of current bank’s clients opened an additional (commitment) account when offered one. Other studies offering a savings account to individuals that had no previous access find higher take up rates (e.g. Dupas and Robinson (2013a) find a 53% take-up rate in Kenya, Prina (2013) fins ad 78% take-up rate in Nepal). *** The number of 59 localities in the study was determined considering the maximum number of localities with a BANSEFI branch within 10 km and with a distance from other localities of at least 3 kilometers.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Comité de Etica e Investigación (CEI), Instituto Nacional de Salud Pública, México
IRB Approval Date
2014-01-13
IRB Approval Number
CI: 1204, No. 1470
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers