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Energy Efficiency in Agriculture: Experimental Evidence from Bangladesh
Initial registration date
January 12, 2021
January 13, 2021 9:22 AM EST
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Other Primary Investigator(s)
Additional Trial Information
Residential electricity consumption in developing countries has risen, and is predicted to increase steadily in the near future. At the same time, groundwater extraction for agriculture is often fueled by electricity, and will likely rise over time as pumps become more affordable for small-scale farmers. For instance, agricultural electricity connections in Bangladesh have risen from 5,549 in 1981 to 54,592 in 2015. Much of the energy-efficiency literature has focused on residential or commercial users of electricity. Is there room to increase energy efficiency among agricultural users? We consider this by testing different mechanisms to encourage adoption of electricity-saving irrigation technology in Bangladesh. To our knowledge, there are very few studies that look at energy efficiency in agriculture, specifically on strategies that encourage farmers to adopt technology that uses electricity more efficiently. The experiment will estimate the energy savings from Alternate Wetting and Drying --- a technique where farmers use a plastic PVC pipe to monitor soil moisture and plan irrigations. We will compare the savings from two different targeting strategies. First, we will offer the technology to water sellers, who stand to gain from saving electricity since they charge farmers for water on a seasonal basis and pay for the marginal cost of pumping on their own. Second, we will offer the technology directly to farmers.
Chakravorty, Ujjayant and Kyle Emerick. 2021. "Energy Efficiency in Agriculture: Experimental Evidence from Bangladesh." AEA RCT Registry. January 13.
Intervention Start Date
Intervention End Date
Primary Outcomes (end points)
Daily Electricity Usage in Agriculture
Primary Outcomes (explanation)
Measured by taking the difference between electricity meter readings at two points in time: once around the start of the season and once around harvesting. It is converted to daily usage by dividing by the number of days in between the two readings.
Secondary Outcomes (end points)
Uptake of the AWD technology, Seasonal Water Charges, Farm Yields
Secondary Outcomes (explanation)
The villages will be randomly divided into 4 groups. In the first group of 105 villages we will promote AWD to individual farmers as a “business-as-usual” benchmark. The most common approach to agricultural extension relies on visits to individual farmers by extension agents. Thus, our first treatment seeks to replicate this type of targeting to individual cultivators. We will therefore arrange for a sales person to approach each farmer in the command area and give him or her the opportunity to purchase AWD at a pre-determined price. The farmer will make their purchasing decision on the spot and the field sales person will provide the AWD pipe to the farmer right away, if they choose to buy. The 105 villages in this arm will receive one of two random village-level prices.
The second arm seeks to test whether targeting water sellers – instead of individual buyers – increases AWD uptake, usage, and ultimately saves more electricity. We will again introduce the option to purchase AWD pipes, but do so directly to the tube well owner (water seller) in the village. The sales person will approach the owner and explain the AWD technology in the same way they did to individual farmers in the first arm. This time the sales offer will be proposed to the tube well owner, rather than to the individual farmers. The tube well owner can then either purchase the pipes himself, or arrange for purchases by the farmers in his command area. Again, we operate under the hypothesis that this treatment can increase uptake off the observation that owners are influential and themselves incentivized to reduce electricity usage from irrigation due to the existing contract structure. The cross randomization of high and low prices will also exist in this arm. This arm will have 105 villages. The third group of 105 villages will be randomized to receive a “coordination treatment” where we seek to increase adoption by inducing group decision-making to solve coordination failures. If irrigation-timing decisions are made jointly, then it seems natural that AWD adoption decisions should also be made jointly. We will have the field partner organize a meeting of all farmers in the command area and make sales offers to the entire group. Finally, we will have a pure control group of 45 villages.
Experimental Design Details
randomization done in office by a computer
Was the treatment clustered?
Sample size: planned number of clusters
Sample size: planned number of observations
8 farmers per village for farm-level observations. 360 villages for village-level observations (electricity usage)
Sample size (or number of clusters) by treatment arms
45 villages control, 105 villages door-to-door targeting, 105 villages village meeting, 105 villages owner targeting
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
INSTITUTIONAL REVIEW BOARDS (IRBs)
Tufts University Social, Behavioral and Educational Research IRB
IRB Approval Date
IRB Approval Number