The American Economic Association's registry for randomized controlled trials
Low Carbon Farming in Karnataka
Last registered on June 30, 2015
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Low Carbon Farming in Karnataka
Initial registration date
June 30, 2015
June 30, 2015 5:55 AM EDT
WZB Berlin Social Science Center
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Other Primary Investigator(s)
Additional Trial Information
Environment & Energy
This is a pilot to investigate the effects of a low carbon farming programme developed by an international network of NGOs. The target population are small and marginal farmers growing ragi (finger millet). Randomisation is carried out within village in two selected villages, with one additional village as control.
BC, Saikumar, Amma Serwaah-Panin and Ferdinand Vieider. 2015. "Low Carbon Farming in Karnataka." AEA RCT Registry. June 30.
BC, Saikumar et al. 2015. "Low Carbon Farming in Karnataka." AEA RCT Registry. June 30.
Sponsors & Partners
Information programme on sustainable farming practices.
Intervention Start Date
Intervention End Date
Primary Outcomes (end points)
Treatment check: differences in farming behaviour between treatment and control farmers; conformity to recommendations by treatment farmers. Outcomes to be measured in farmer diaries.
Aggregate outcomes: over yield differences between treatment and control; differences in revenue and profits (revenues minus costs). Differences in soil quality and emissions (conditional on measuring instruments being in place).
Individual level: influence of farming practices at individual level for both treatment and control farmers; correlation with socio-demographic background characteristics; correlations with experimentally measured risk and time preferences; correlations with cognitive ability measures. Interaction effects of individual characteristics with the treatment.
Primary Outcomes (explanation)
Farmer diaries will be maintained to register farmer practices in both the treatment and control groups in detail. Village level volunteers will assist farmers in filling in said diaries in order to guarantee consistency and control quality of information.
Risk and time preferences will be measured using a so-called budget-line task. See Choi, Syngjoo, Raymond Fisman, Douglas Gale, & Shachar Kariv (2007). Consistency and Heterogeneity of Individual Behavior under Uncertainty. American Economic Review 97(5), 1921-1938, for an illustration for the method for risk; the method for time preferences follows a similar setup.
Cognitive ability tests: Raven matrices and the Stroop numerical task.
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
We use within-village randomisation at the individual level of eligible farmers. The treatment is offered to half the eligible farmers in both villages. The farmers are randomly selected (pure randomisation). An additional village is monitored as a control village.
Experimental Design Details
Randomisation done in office by a computer.
Farmers growing ragi in 2014. Randomisation at the individual farmer level.
Was the treatment clustered?
Sample size: planned number of clusters
144 excluding control village
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
72 in treatment
35 in control village (randomly selected from ragi growers in control village)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
pilot study only
Supporting Documents and Materials
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Approval Date
IRB Approval Number
Post Trial Information
Is the intervention completed?
Is data collection complete?
Is public data available?
Reports, Papers & Other Materials
REPORTS & OTHER MATERIALS