Mobile-Based Information Provision on Covid Support in Uttar Pradesh

Last registered on October 07, 2021

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Pre-Trial

Trial Information

General Information

Title

Mobile-Based Information Provision on Covid Support in Uttar Pradesh

RCT ID

AEARCTR-0007297

Initial registration date

April 08, 2021

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 09, 2021, 2:28 PM EDT

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

Last updated

October 07, 2021, 5:30 AM EDT

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

Locations

Country

India

Region

Uttar Pradesh

Primary Investigator

Name

Debayan Pakrashi

Affiliation

Department of Economic Sciences, Indian Institute of Technology Kanpur

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Irma Clots-Figueras

PI Affiliation

University of Kent

Contact Investigator

PI Name

Zaki Wahhaj

PI Affiliation

University of Kent

Contact Investigator

PI Name

Bansi Malde

PI Affiliation

University of Kent

Contact Investigator

PI Name

Anirban Mitra

PI Affiliation

University of Kent

Contact Investigator

PI Name

Amrit Amirapu

PI Affiliation

University of Kent

Contact Investigator

Additional Trial Information

Status

On going

Start date

2020-04-01

End date

2023-12-31

Keywords

Gender, Governance, Other, Welfare

Additional Keywords

awareness, access, relief programmes, political attitudes, trust

JEL code(s)

D83, H12, H41, I38

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

COVID-19 and policies to control it have resulted in widespread poverty and food insecurity as the pandemic has adversely affected employment opportunities, incomes and livelihoods of millions of households. In order to protect poor households from income-loss and inaccessibility to food supplies, the central and state governments have introduced several benefits as part of its existing welfare schemes. However, there often exists a gap between introduction and access to these publicly funded government programmes. We conduct a field experiment in the state of Uttar Pradesh, India with just over 1000 households during the COVID-19 pandemic to examine whether raising awareness about government benefits via information provision over the phone leads to improved knowledge, increased access, and greater utilization of these available benefits. We will also assess whether such interventions will be more effective if the male members are targeted vis-à-vis the female members of the households. We believe that this analysis will be of particular interest as understanding what works best in this situation will be essential to improving the design of policies to combat this and similar crises in the future.

External Link(s)

Registration Citation

Citation

Amirapu, Amrit et al. 2021. "Mobile-Based Information Provision on Covid Support in Uttar Pradesh ." AEA RCT Registry. October 07. https://doi.org/10.1257/rct.7297-1.1

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Experimental Details

Interventions

Intervention(s)

We will conduct an informational intervention where we will provide subjects living in slums in Uttar Pradesh with information about the main government Covid-19 relief programmes they could have access to. We will have two treatment groups and a control group, that will not receive any information.

Intervention Start Date

2020-09-01

Intervention End Date

2021-02-28

Primary Outcomes

Primary Outcomes (end points)

Awareness, access and utilization of the benefits being provided by the governments via different relief programmes.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Perception of corruption and how governments handled the crisis, voting intentions, information sharing within household and community, food security and wellbeing indicators such as life satisfaction and mental health.

Secondary Outcomes (explanation)

Experimental Design

1006 households from 60 different slums in the city of Kanpur, Uttar Pradesh were assigned to one of two treatment groups or a control group. The treatment is randomised at the slum-level (such that 20 slums are allotted to each group) in a randomised saturation design to capture any information spillovers to other households within the same slum.

Experimental Design Details

In one of the treatments we will provide information to the woman who answered the baseline questionnaire (referred to as Treatment Female), and in the other to her husband, or the household head (Treatment Male). Our study will analyse how our informational interventions affect awareness of the different programmes, but also the extent to which these households benefit from the programmes.

The comparison between the two treatment groups will give us an understanding of information transmission within the household. For example, differential effects across the two treatment groups would suggest that information provided to female and male household members are being communicated/processed differently by the household. Due to the way our intervention is designed, we will be able to have estimates of the degree of information transmission of the different programmes after the intervention.

Randomization Method

Randomization into the different treatment or control groups or treated versus untreated status was assigned by the computer.

Randomization Unit

Randomization was done at the slum level. Within treated slums, we randomly selected 75% of sample households to receive the information. The remaining 25% are 'spillover control' households

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

60 slums.

Sample size: planned number of observations

1006 households from these 60 slums.

Sample size (or number of clusters) by treatment arms

340 households were assigned to the control group (from 20 slums), 334 to the Treatment Female group (from 20 slums) and 332 to the Treatment Male group (from 20 slums), giving us a total of 1006 households from 60 slums.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Assuming there are 17 households per cluster on average, the minimum detectable effect sizes are as follows: For an intracluster correlation of 0, the MDE for continuous outcomes such as knowledge of entitlements and access and utilisation of benefits: 1) Treatment 1 vs control: 0.232 std deviations 2) Treatment 2 vs control: 0.232 std deviations 3) Treatment 1 vs Treatment 2: 0.246 std deviations 4) Pooling Treatment 1 + 2 vs control: 0.197 std deviations 5) Spillover households - Treatment 1 + 2 vs control: 0.263 std deviations For an intracluster correlation of 0.05, the MDE for continuous outcomes such as knowledge of entitlements and access and utilisation of benefits: 1) Treatment 1 vs control: 0.302 std deviations 2) Treatment 2 vs control: 0.302 std deviations 3) Treatment 1 vs Treatment 2: 0.311 std deviations 4) Pooling Treatment 1 + 2 vs control: 0.258 std deviations 5) Spillover households - Treatment 1 + 2 vs control: 0.311 std deviations

Supporting Documents and Materials

IRB