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Maternal Cash Transfers and Child Health: Evidence from India

Last registered on November 20, 2020

Pre-Trial

Trial Information

General Information

Title
Maternal Cash Transfers and Child Health: Evidence from India
RCT ID
AEARCTR-0002899
Initial registration date
April 14, 2018

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
April 17, 2018, 2:57 PM EDT

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

Last updated
November 20, 2020, 1:59 AM EST

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

Locations

Region

Primary Investigator

Affiliation
University of Southern California

Other Primary Investigator(s)

PI Affiliation
University of California, San Diego
PI Affiliation
University of California, San Diego
PI Affiliation
University of Virginia

Additional Trial Information

Status
On going
Start date
2017-09-15
End date
2021-04-30
Secondary IDs
Abstract
This study will evaluate whether framed, unconditional cash transfers (UCT) to pregnant women and lactating mothers are effective in improving the health of their children, as measured by incidence of stunting and wasting. This will be the first randomized evaluation in India of unconditional cash transfers for maternal and child health, and will be implemented by the Government of Jharkhand (GoJH) in eight districts. We will study the impact of a 24-month long UCT to pregnant and lactating mothers, testing how variation in the timing of transfers affects child health.
External Link(s)

Registration Citation

Citation
Muralidharan, Karthik et al. 2020. "Maternal Cash Transfers and Child Health: Evidence from India." AEA RCT Registry. November 20. https://doi.org/10.1257/rct.2899-3.2
Former Citation
Muralidharan, Karthik et al. 2020. "Maternal Cash Transfers and Child Health: Evidence from India." AEA RCT Registry. November 20. https://www.socialscienceregistry.org/trials/2899/history/80012
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Experimental Details

Interventions

Intervention(s)
n/a
Intervention Start Date
2018-03-01
Intervention End Date
2020-11-15

Primary Outcomes

Primary Outcomes (end points)
Child height and weight for age at age 2
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
na
Experimental Design Details
After registration was complete, women were randomized into four groups, with transfers going out immediately. Figure 1 summarizes the experimental design. The entire sample of the study comprises of 960 AWCs randomly selected across 8 districts, from which we will choose the AWCs for the three treatment arms:

• Treatment Group 1: Pregnant women from 240 AWCs will receive a monthly Rs. 500 cash transfer for two years, starting immediately after the registration window closes (approximately from ages -6 months to 18 months for the child)
• Treatment Group 2: Pregnant women from 240 AWCs will receive a monthly Rs. 500 cash transfer for one year, starting immediately after the registration window closes (approximately from ages -6 months to 6 months for the child)
• Treatment Group 3: Pregnant women from 240 AWCs will receive a monthly Rs. 500 cash transfer for one year, starting one year after the registration window closes (approximately from ages 6 months to 18 months for the child)
• Control group: 240 AWCs will serve as the control group for the three treatments

In the treatment arms, the cash transfers will be framed as to be used for maternal and child nutrition. This message will be reinforced by regular interactive voice response phone calls to beneficiaries. Control households will receive similar phone calls, but with a generic message encouraging spending on nutrition, to keep the role of messaging constant between the groups. Since households will be randomly assigned to these groups, we can compare between them to determine the relative effectiveness of getting transfers at different ages for child nutrition. The results will speak to broader questions around targeting cash transfers to mothers of young children, and the rate of return to expanding the fiscal envelope to increase spending on early childhood nutrition.
Randomization Method
randomization done in office by a computer
Randomization Unit
Anganwadi center (a community health center for a population of roughly 1000 individuals)
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
960 anganwadi centers
Sample size: planned number of observations
4800 pregnant women
Sample size (or number of clusters) by treatment arms
1200 pregnant women in each treatment arm and in the control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We surveyed the literature on cash transfers to gauge the range of plausible effect sizes that we want to be powered to detect. Transfers are around 15% of household income, similar in magnitude to those studied in Schady and Rosero (2008) and Paxson and Schady (2010) in Ecuador, Amarante et al (2011) in Uruguay, and Macours et al (2012) in Nicaragua. The most comparable is the Ecuadorian program, in which there was an improvement in development of 0.18 standard deviations among the poorest quartile of children in their sample; given the higher income levels in Ecuador, that group should be roughly comparable to our sample in Jharkhand. We wish to detect effects of that size for each of the questions of interest. To be slightly conservative, our calculations focus on minimum detectable effect sizes of 0.15 standard deviations. Intracluster Correlation Calculations Since our randomization is clustered at the AWC level, we must account for intracluster correlation in our power calculations. We use the 2006 wave of the Indian National Family Health Survey and calculate the intra-village correlation in child height and weight for age within villages in Jharkhand and neighboring states (Bihar, Madhya Pradesh, Orissa). For these variables, the intracluster correlation is relatively high, at 0.06 and 0.09. To be conservative, we use 0.09 in our calculations. Number of Participants Per Cluster The average number of women per AWC is estimated to be 5, but in the first round of registrations, we observed substantial heterogeneity across AWCs. In some clusters, there were as many as 17 women registered, while in others, none registered. We calculate the coefficient of variation in number of registrations across AWCs (0.665), and take this into account in the power calculations. When we randomize, we will also stratify by number of registrations in an AWC to maximize power. One way of increasing power is to collect baseline data on variables that will be correlated with the outcome at endline (such as the outcome at baseline). We have elected not to do a baseline survey. There are two reasons that we will not be able to do this. First, it is not possible to identify beneficiaries until after they have registered, and the transfers must go out as soon as possible after registration. This does not afford time for a baseline survey. Second, the primary outcomes of interest, such as child weight and height are not possible to measure at baseline, since the child is still in utero. In the power calculations, we thus do not assume any power boost from a baseline survey. The power calculations are different for each of the questions of interest. For example, to calculate the effect of a single year of cash transfers, we can combine the two treatment groups that receive a year of transfers and compare them to the control group. However, to determine the effect of receiving two years of transfers, we can only compare that single treatment group to the control group. For all of the questions of interest, we seek to detect an effect of 0.15 standard deviations with 80% power. We thus determine our sample size for the questions on which the sample sizes will be smallest, and then calculate our power for the other questions of interest under this sample size. Based on this, a sample size of 240 AWCs per treatment arm allows us to detect an effect size of 0.15 standard deviations with 95% confidence at 80% power. Based on this sample size, the below table shows the level of power for different effect sizes. Question of Interest Effect size of 0.1 SD Effect size of 0.12 SD Effect size of 0.15 SD Comparison of 1 treatment arm to 1 treatment arm (e.g. effect of 1 year of transfers in utero vs. after child is born) 0.48 0.63 0.82 Comparison of 1 treatment arm to 2 treatment arms (e.g. effect of 1 year of transfers vs. 2 years of transfers) 0.66 0.82 0.95
IRB

Institutional Review Boards (IRBs)

IRB Name
University of California, San Diego
IRB Approval Date
2017-11-02
IRB Approval Number
171746S
Analysis Plan

Analysis Plan Documents

JH+ICDS+PaP+-+year+2+-+final+-+revised.pdf

MD5: 7db95532afef279269e68fde3e389d54

SHA1: 3b49bb08ee6fa0a82eaf7c9acbf62b8bacd298ae

Uploaded At: November 20, 2020

JH ICDS PaP - year 2 - final.pdf

MD5: 9aad6e56d3138c3359f2e38bce295081

SHA1: f61d56a1b278b4beb98bb2cfc7da25b264ea2b06

Uploaded At: March 05, 2020

JH+ICDS+PaP+-+year+1+-+final.pdf

MD5: 68977d69e3a98002fcfe3d0fc0a6d523

SHA1: 0fe6b390a301c647eec41d3464cf2ffaf5fa3ac0

Uploaded At: March 07, 2019

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials