Conventions, Information Asymmetry, and Flow of Information in Households: Theory and Experiment in Liberia

Last registered on August 19, 2021

Pre-Trial

Trial Information

General Information

Title
Conventions, Information Asymmetry, and Flow of Information in Households: Theory and Experiment in Liberia
RCT ID
AEARCTR-0007841
Initial registration date
June 22, 2021
Last updated
August 19, 2021, 12:18 AM EDT

Locations

Primary Investigator

Affiliation
Northwestern University

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2021-06-21
End date
2022-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
It remains a puzzle how collective decisions upon private information are made in households and communities in developing countries. Recent evidence points to the interplay of social roles and individual incentives to transmit information. In the spirit of Akerlof (1970), this paper proposes a framework to understand three essential aspects of information aggregation, when there are information asymmetries about changes in attributes of individuals under social conventions: (1) acquisition of attributes (e.g. skills); (2) efforts in interactions (e.g. communication); and (3) resulting flow of new information. The framework suggests tradeoffs for communities in achieving societal and micro-level objectives, and highlights tradeoffs in different approaches to informational interventions considering the possibilities of miscoordination among agents. Within the context of a school-based agricultural education program in Liberia that aims to empower students as agents of knowledge diffusion, I design a household-level experiment to study intergenerational information flow. The experiment (1) tests the existence of information asymmetries in crucial decisions; and (2) contrasts different approaches that induce information transmission in students' households and communities.

This experiment is embedded in the context of a general randomized evaluation of the program (AEARCTR-0006671).
External Link(s)

Registration Citation

Citation
Lee, Jimmy. 2021. "Conventions, Information Asymmetry, and Flow of Information in Households: Theory and Experiment in Liberia." AEA RCT Registry. August 19. https://doi.org/10.1257/rct.7841-2.3000000000000003
Experimental Details

Interventions

Intervention(s)
I design a 2 x 2 randomized experiment among 1000 households with students in 50 schools that join the school-based agricultural program (4-H Liberia) in 2021. Our household-level interventions encourage students and their elders to imagine, at the beginning of the program (and of the first rainy season), the consequences of students' active participation in the program.

The first randomization aims to encourage elders (in students' households) to learn about and support their students' potential growth in farming skills, attitudes, and commitments. Half of the households receive an invitation to treatment video sessions; the other half receive an invitation to placebo video sessions. For every household, the representative elder who attends the session must be a farmer growing crops in the promoted categories (root crops or vegetables). Each video session has 5 elders and lasts around 1.5 hours: baseline questions; video display on a laptop under palava huts; and follow-up questions. Treatment video sessions display a 14-minute video that (i) provides an overview of the program and (ii) summarizes program impact on students’ farming skills, attitudes, and livelihoods from past participants (in communities that are not included in the sample). Placebo video sessions display a 4-minute video that ONLY provides an overview of the program. Both videos are taken from footage shot during late 2020 - early 2021 by a third-party media production company in Liberia. The treatment video is a long version that encompasses everything in the placebo video. We also independently randomize who in the households attend the video sessions (both treatment and placebo): for half of the households, a male is invited to the sessions; for the other half of the households, a female is invited.

The second randomization aims to overcome potential coordination difficulties between students and their elders by encouraging students to reach out to their elders (to introduce the program, what they have learnt, suggest new farming ideas, and propose to manage farms, etc).
During the video sessions, we collect (before showing videos) elders' beliefs about students' current farming skills, attitudes, and commitments; and (after showing video) elders' forward-looking expectations about the same attributes of students in 1 year. We ask if elders would give their consent for IPA to reveal their positive expectations to students. We then manipulate students' information about their elders' expectations in a follow-up survey. In half of the households, we deliver (i) revelation messages that reveal expectations from elders to students and (ii) encouragement messages that ask students to take on the role as an agent of diffusion of new practices. In the other half of the households, we deliver ONLY encouragement messages.
Intervention Start Date
2021-06-21
Intervention End Date
2021-07-31

Primary Outcomes

Primary Outcomes (end points)
Our primary outcomes are in 7 categories: (i) students' participation in the program; (ii) students' major rainy season farming activities outside schools; (iii) students' minor rainy season farming activities outside schools; (iv) students' knowledge, skills, and aspirations; (v) students' usage of new agricultural practices outside schools; (vi) elders' knowledge and skills; (vii) elders' usage of new agricultural practices outside schools. Multiple inference corrections will be implemented across outcomes within the same category.

(i) In the category of students' participation in the program, we have the following outcomes:
(1) a binary indicator of whether students work in the school garden (self-reported in the post-rainy-season survey);
(2) a binary indicator of whether students enroll in 4-H Clubs (self-reported in the post-rainy-season survey and monitored by program);
(3) a binary indicator of whether students have started home entrepreneurship projects (self-reported in the post-rainy-season survey and monitored by program);
(4) a binary indicator of whether students are in the leadership of development clubs (including presidents, vice-presidents, secretaries, treasuries, and chaplains; self-reported in the post-rainy-season survey and monitored by program);
(5) a binary indicator of whether students have participated in national networking events (including 4-H leadership camps and 4-H agriculture fairs; self-reported in the post-rainy-season survey and monitored by program).

(ii) In the category of students' major rainy season farming activities outside schools, we have the following outcomes:
(1) a binary indicator of whether students managed at least one independent farm plot during the major rainy season (self-reported, verified by reports of elders and enumerators in the post-rainy-season survey);
(2) binary indicators of whether students chose planting method in at least one farm plot during the major rainy season (aggregated into an index of multiple planting methods promoted by the program; self-reported and verified by reports of elders in the post-rainy-season survey);
(3) a binary indicator of whether students chose which crops to plant in at least one farm plot during the major rainy season (self-reported and verified by reports of elders in the post-rainy-season survey);
(4) a binary indicator of whether students chose whether to sell their crops in at least one farm plot during the major rainy season (self-reported and verified by reports of elders in the post-rainy-season survey);
(5) total area of students' farm plots during the major rainy season (self-reported, verified by enumerators in the post-rainy-season survey);
(6) binary indicators of whether students use hired labor / family labor / communal (kuu) labor during the major rainy season (aggregated into an index; self-reported, verified by reports of elders and enumerators in the post-rainy-season survey);
(7) binary indicators of whether students used fertilizer / irrigation / pesticide during the major rainy season (aggregated into an index; self-reported, verified by reports of elders and enumerators in the post-rainy-season survey).

(iii) In the category of students' minor rainy season farming activities outside schools, we have the following outcomes:
(1) a binary indicator of whether students managed at least one independent farm plot during the minor rainy season (self-reported, verified by reports of elders and enumerators in the post-rainy-season survey);
(2) binary indicators of whether students chose planting method in at least one farm plot during the minor rainy season (aggregated into an index of multiple planting methods promoted by the program; self-reported and verified by reports of elders in the post-rainy-season survey);
(3) a binary indicator of whether students chose which crops to plant in at least one farm plot during the minor rainy season (self-reported and verified by reports of elders in the post-rainy-season survey);
(4) a binary indicator of whether students chose whether to sell their crops in at least one farm plot during the minor rainy season (self-reported and verified by reports of elders in the post-rainy-season survey);
(5) total area of students' farm plots during the minor rainy season (self-reported, verified by enumerators in the post-rainy-season survey);
(6) binary indicators of whether students use hired labor / family labor / communal (kuu) labor during the minor rainy season (aggregated into an index; self-reported, verified by reports of elders and enumerators in the post-rainy-season survey);
(7) binary indicators of whether students used fertilizer / irrigation / pesticide during the minor rainy season (aggregated into an index; self-reported, verified by reports of elders and enumerators in the post-rainy-season survey).

(iv) In the category of students' knowledge, skills, and aspirations, we have the following outcomes:
(1) a standardized measure of students' knowledge of promoted farm management practices and agricultural innovations (measured in a 20-question test during the post-rainy-season survey);
(2) a standardized measure of students' knowledge of promoted entrepreneurial skills and financial literacy (measured in a 20-question test during endline survey in 2022);
(3) binary indicators of whether students can correctly use specific promoted practices (aggregated into an index; tested by enumerators during the post-rainy-season survey);
(4) binary indicator of whether students want to be a farmer, a scientist, or an agriculturalist after finishing school (self-reported without giving choices during the post-rainy-season survey).

(v) In the category of students' usage of new agricultural practices outside schools, we have the following outcomes:
(1) binary indicators of whether students have applied promoted practices outside schools in their farms (aggregated into an index; self-reported and verified by enumerators during the post-rainy-season survey);
(2) fraction of farms where at least one farming practice has been applied (verified by enumerators during the post-rainy-season survey).

(vi) In the category of elders' knowledge and skills, we have the following outcomes:
(1) a standardized measure of elders' knowledge of promoted farm management practices and agricultural innovations (measured in a 20-question test during the post-rainy-season survey);
(2) a standardized measure of elders' knowledge of promoted entrepreneurial skills and financial literacy (measured in a 20-question test during endline survey in 2022);
(3) binary indicators of whether elders can correctly use specific promoted practices (aggregated into an index; tested by enumerators during the post-rainy-season survey).

(vii) In the category of elders' usage of new agricultural practices outside schools, we have the following outcomes:
(1) binary indicators of whether elders have applied promoted practices outside schools in their farms (aggregated into an index; self-reported and verified by enumerators during the post-rainy-season survey);
(2) fraction of farms where at least one farming practice has been applied (verified by enumerators during the post-rainy-season survey).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
There are two classes of secondary outcomes:
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
I test the significance of my hypothesized mechanism - information asymmetry in changes of students' farming skills, attitudes, and commitments - in a 2 x 2 experiment among 1000 households with students in 50 schools that join the school-based agricultural program (4-H Liberia) in 2021.

We identify our effects as follows. I test the first hypothesis - that there is room to encourage elders in students' households to learn about the positive impacts of the program (on students' farming attributes) - using the first randomization. Households that are invited to treatment video sessions will be compared to households that are invited to placebo video sessions.

I test the second hypothesis - that even when elders in students' households have positive expectations about students' growth in farming attributes, there are difficulties for elders to reveal these expectations to students (e.g. because farming ideas and knowledge about the program belong to students) - using the second randomization. Households that receive the "revelation + encouragement" treatment will be compared to households that receive the "encouragement" treatment.

The selection of our household sample is done in schools. Students are randomly drawn from Grades 4, 5, 7, and 8 (stratified by school and gender). Informed by pilot survey data, we implement a series of screening criteria in selecting 20 students per school who are likely to participate in the program. Selected students must be aged 12-20; must have at least one elder in the household who is planting root crops or vegetables; and must be from separate households. We prioritize students who had farming experience or joined cooperative labor groups (kuu) before 2021. We also prioritize students who have both male and female elders in the household who are planting root crops or vegetables.

All baseline surveys and household-level interventions (same or next day after baseline surveys) will be conducted in June - August 2021. A follow-up survey after the major rainy season (typically April - October) will take place in November 2021 - January 2022. Two further follow-up surveys might take place in April - June 2022 and September - November 2022 to track long-run outcomes. Students' participation in program activities will be monitored by our partners 4-H Liberia and AgriCorps; these data will be linked to our baseline surveys.
Experimental Design Details
Not available
Randomization Method
Randomization done in IPA office by a computer, using student ID (which is sorted according to schools, grades, and gender of students). Randomization was done before students are recruited into the sample, and was stratified based on schools and gender of students.
Randomization Unit
For video treatment: household
For revelation treatment: household
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1000 households in total.
Sample size: planned number of observations
1000 students (500 male, 500 female) and 1000 elder farmers (500 male, 500 female).
Sample size (or number of clusters) by treatment arms
250 households receiving treatment video and "revelation + encouragement" treatment;
250 households receiving placebo video and "revelation + encouragement" treatment;
250 households receiving treatment video and "encouragement" treatment;
250 households receiving placebo video and "encouragement" treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

Documents

Document Name
Class-level screening survey of students
Document Type
survey_instrument
Document Description
This is the class-level screening survey for sampling students at each school.
File
Class-level screening survey of students

MD5: 2d72cfed78f3f0200c5d657eb54b3bea

SHA1: 43ac7e47c2b917f06a19bfb7f95ae56906f31c03

Uploaded At: August 08, 2021

Document Name
Baseline test for students in treatment schools
Document Type
survey_instrument
Document Description
This is the baseline test for sampled students in 50 treatment schools (without HH-level interventions).
File
Baseline test for students in treatment schools

MD5: 57e3947195406f300e274080b8ca235f

SHA1: d6dd8b981c919289c1387239c666c3bd841bb630

Uploaded At: August 08, 2021

Document Name
Baseline test for students in control schools
Document Type
survey_instrument
Document Description
This is the baseline test for sampled students in 97 control schools.
File
Baseline test for students in control schools

MD5: 7aab7d78ea91a95070a02875be9ed3b4

SHA1: d06a00b78767389c651d4d3fde3570e5ef471752

Uploaded At: August 08, 2021

Document Name
Baseline survey for students in treatment schools with HH-level interventions
Document Type
survey_instrument
Document Description
This is the baseline survey for sampled students in 50 treatment schools (with HH-level interventions).
File
Baseline survey for students in treatment schools with HH-level interventions

MD5: 9c5fb7f5201ae5838d71082fb1b28b59

SHA1: 974585a9553bf548a4bc9bbef7dcab6181535558

Uploaded At: August 08, 2021

Document Name
Baseline survey of elders
Document Type
survey_instrument
Document Description
This is the baseline survey for sampled elders in 50 treatment schools (with HH-level interventions).
File
Baseline survey of elders

MD5: 287eab6fe5f687ee11d03db56cd5e383

SHA1: 89a9cdafe2478edeedf12efc96d8129238279980

Uploaded At: August 08, 2021

Document Name
Follow-up survey of elders
Document Type
survey_instrument
Document Description
This is the follow-up survey for sampled elders in 50 treatment schools (with HH-level interventions). This takes place immediately after the presentation of treatment/placebo video to elders.
File
Follow-up survey of elders

MD5: 31dad4b3d0ce8fd6eea6b3bfb6fe7c3d

SHA1: 82d5bc09629d412d8cec9adf9045adf7296892c3

Uploaded At: August 08, 2021

Document Name
AgriCorps Theory of Change
Document Type
other
Document Description
This is the theory of change presented to me by my partner AgriCorps when we first met in 2019.
File
AgriCorps Theory of Change

MD5: 69c4c13c288b4be898227a1f390f2f0f

SHA1: 0d4440d54388f494d5e3057f7751e598aae7adf7

Uploaded At: August 08, 2021

Document Name
Follow-up survey of students
Document Type
survey_instrument
Document Description
This is the follow-up survey for sampled students in 50 treatment schools (with HH-level interventions). This survey includes the treatment/placebo revelation messages.
File
Follow-up survey of students

MD5: 31dad4b3d0ce8fd6eea6b3bfb6fe7c3d

SHA1: 82d5bc09629d412d8cec9adf9045adf7296892c3

Uploaded At: August 08, 2021

IRB

Institutional Review Boards (IRBs)

IRB Name
Northwestern University IRB
IRB Approval Date
2019-12-20
IRB Approval Number
STU00211435
IRB Name
Innovations for Poverty Action IRB
IRB Approval Date
2019-12-03
IRB Approval Number
15307
IRB Name
University of Liberia IRB
IRB Approval Date
2021-02-05
IRB Approval Number
18-11-185
Analysis Plan

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