Digital Green Methodology Evaluation
Last registered on August 27, 2018

Pre-Trial

Trial Information
General Information
Title
Digital Green Methodology Evaluation
RCT ID
AEARCTR-0000313
Initial registration date
March 18, 2014
Last updated
August 27, 2018 6:46 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
Columbia University
Other Primary Investigator(s)
PI Affiliation
New York University, Abu Dhabi
PI Affiliation
Yale University
PI Affiliation
Cal Poly
PI Affiliation
University of California, Berkely
Additional Trial Information
Status
Completed
Start date
2014-05-20
End date
2014-12-31
Secondary IDs
Abstract
This is an impact evaluation for DG. The study seeks to evaluate DG’s effectiveness as an extension methodology and to understand the impact of labor-cost information embedded in extension messaging.
We will focus on System of Rice Intensification (SRI) in the Indian state of Bihar. SRI is an agronomic technique that increase gross yield, typically with less inputs. The main trial will be timed to coincide with the main rice planting season in 2014 which begins in late June and will go through December.
External Link(s)
Registration Citation
Citation
Baul, Tushi et al. 2018. "Digital Green Methodology Evaluation." AEA RCT Registry. August 27. https://www.socialscienceregistry.org/trials/313/history/33513
Experimental Details
Interventions
Intervention(s)
Digital Green is a non-profit headquartered in Delhi, which specializes in a specific video-based extension technique. The DG methodology involves (a) the local production of videos for agricultural technologies and techniques; and (b) group-based instruction that uses the videos as a base for mediated instruction, where a mediator provokes the audience into discussions about the video content. A small-scale controlled trial of DG suggested that it is 10 times more cost-effective than classical €œtraining and visit style agriculture extension. DG partners with and trains other organizations that disseminate agriculture technologies and techniques to smallholder farmers in developing countries.

The study seeks to evaluate DG's€™ effectiveness as an extension methodology and to understand the impact of labor-cost information and messages around self-efficacy embedded in extension messaging.
Intervention Start Date
2014-06-20
Intervention End Date
2014-10-20
Primary Outcomes
Primary Outcomes (end points)
1. Rice yields.
2. Measures of self-efficacy
3. SRI adoption
4. Labor, seed, water usage.
5. Income and consumption.
6.Income transfers
Primary Outcomes (explanation)
Self efficacy will be measured by a survey evaluating farmers' beliefs in their own abilities to carry out learned practices from the videos.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We will conduct the trial over 420 total villages (in 4 districts on Bihar) with 6 participants per village. There will be 140 control and 280 treatment villages. Treatment status will be assigned randomly and randomization is stratified based on Jeevika's SRI presence in the previous year 2013.

Out of the 280 treatment villages in 93 randomly assigned villages there will be self efficacy information showed using Digital Green Methodology. In another 93 randomly assigned villages. In the remaining 94 randomly assigned villages both cost and self efficacy information will be shown using Digital Green Methodology.

The trial will proceed as straightforward treatment and control groups to test the effect of Digital Green, Digital Green with focused messaging around labor costs, and Digital Green with focused messaging on self efficacy. The control group will receive training via Jeevika, the implementer of the baseline farmer training in India-- National Livelihood Rural Mission.


T0: NRLM
T1: Digital Green
T1a: Regular DG videos
T1b: DG videos + labor-cost information
T1c: DG videos + self-efficacy information
Experimental Design Details
Randomization Method
Randomization done in office by a computer. Some re-randomization in the filed may be necessary based on attrition.
Randomization Unit
Villages
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
420 Villages
Sample size: planned number of observations
2520 households
Sample size (or number of clusters) by treatment arms
280 Treatment villages. 140 control villages
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Minimum detectable effect size for: Adoption rate of SRI: a 8% increase (from 40 to 48 percent) Yields: A 10% increase in yields
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Columbia University
IRB Approval Date
2014-03-07
IRB Approval Number
AAAN2254
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