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Biochar, Soil Carbon, Social Learning, and Technology Adoption
Last registered on January 17, 2014


Trial Information
General Information
Biochar, Soil Carbon, Social Learning, and Technology Adoption
Initial registration date
Not yet registered
Last updated
January 17, 2014 5:22 AM EST
Primary Investigator
UC Berkeley
Other Primary Investigator(s)
Additional Trial Information
On going
Start date
End date
Secondary IDs
This research focuses on the problem of soil degradation and agricultural development in sub-Saharan Africa, and the dissemination of technologies by which farmers can improve soil fertility, and thereby increase their yields and improve their livelihoods. In particular, we propose to study the dissemination of biochar (a soil amendment made from thermally altered biomass, including crop residues).

A growing body of work has shown that biochar can improve crop yields and sequester carbon for long periods, particularly in highly weathered soils, such as those typical of much of sub-Saharan Africa. However, numerous new agricultural technologies in sub-Saharan Africa have been introduced only to face lack of adoption by intended end-users. This is particularly true among the subset of agricultural technologies that offer both local and global environmental benefits, that external actors may have an incentive to support through, for example, carbon finance.

Therefore, our aims are threefold: First, we seek to estimate the impact of biochar adoption on farm-level crop yields and profitability. Second, we seek to test various inducement programs to see which is most effective in stimulating adoption of our new technology per dollar of external support. In particular, we will compare the efficacy of a program to stimulate social learning through pre-existing social networks, a simple price support, and the provision of a limited liability credit offer. Finally, we will exploit the randomization of inducements to test mechanisms by which social learning operates in the context of adoption of new technologies.
External Link(s)
Registration Citation
Crane-Droesch, Andrew. 2014. "Biochar, Soil Carbon, Social Learning, and Technology Adoption." AEA RCT Registry. January 17. https://doi.org/10.1257/rct.221-1.0.
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Experimental Details
75 of 1000 farmers in our sample were randomly selected to recieve biochar demonstration plots in the runup to the 2013 "short rains" agricultural season. These demonstration plots applied biochar to one half of a 1/8-acre plot, and not to the other. Farmers were instructed to manage both plots equally otherwise. Beginning January 2014 (after the harvest of the demonstration plots) farmers in our sample are being offered biochar for sale, at randomly varying prices, and with a chance to recieve a free trail offer (in which farmers recieve a small amount of biochar on credit, and can choose not to pay if they are not satisfied with the results).
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Adoption, yields, complimentary input expenditure, complimentary input efficacy, agricultural profits
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Demonstration plots were randomly allocated within social networks. Therefore, the proportion of a farmer's network having a biochar demonstration plot is not correlated with characteristics of farmers that may influence outcomes of interest. In addition, prices and free trials were allocated randomly on top of this. Adoption propensity will be assessed as a function of these three variables. Furthermore, the random variation in adoption propensity attributable to these inducements will later be harnessed to assess biochar's impact of other outcomes of interest.
Experimental Design Details
Randomization Method
Computer randomization for selection into demonstration plot group. Prices and free trial offers were randomized by having farmers choose from among many blank envelopes containing different offers.
Randomization Unit
Individual/socail network
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
1000 people in 4 geographic areas.
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
75 demonstration plots
70% of farmers got some subsidy, with the degree of the subsidy varying over a wide range.
25% will receive the free trial offer
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
UC Berkeley Committee for the Protection of Human Subjects
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)