Leveraging Natural Enemies to Reduce Pesticide Overuse in Agriculture

Last registered on January 17, 2025

Pre-Trial

Trial Information

General Information

Title
Leveraging Natural Enemies to Reduce Pesticide Overuse in Agriculture
RCT ID
AEARCTR-0015204
Initial registration date
January 14, 2025

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
January 17, 2025, 6:58 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Affiliation
University of Chicago

Other Primary Investigator(s)

PI Affiliation
CUHK-Shenzhen
PI Affiliation
Duke University

Additional Trial Information

Status
In development
Start date
2025-03-10
End date
2026-07-10
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In this project, we propose a randomized field experiment to investigate and overcome the potential barriers to the adoption of pesticide-replacing agricultural technologies in a developing economy. To do so, we will partner with two influential companies operating in Western China. The first one is a major agricultural technology company that specializes in producing the natural enemies of agricultural pests, such as predatory mites, which can be applied to the fields to replace traditional chemical pesticides. Working with the agricultural technology company, we will randomly provide selected farmers with monetary subsidies for the natural enemy products. The second one is the largest supermarket chain in a Western Chinese province, which is committed to procuring agricultural products with low pesticide residue, for which their urban customers are willing to pay a substantial premium. Working with the supermarket chain, we cross-randomize a certification treatment. The supermarket chain has formally committed to a higher procurement price for products that are certified to test below a cutoff for pesticide residue. We will enroll the treated farmers (both those that receive free natural enemy products and those that do not) into such a certification program.
External Link(s)

Registration Citation

Citation
Lin, Wei, Shaoda Wang and Daniel Xu. 2025. "Leveraging Natural Enemies to Reduce Pesticide Overuse in Agriculture." AEA RCT Registry. January 17. https://doi.org/10.1257/rct.15204-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
• Supply Treatment: This group will receive supply-side technical support. In partnership with the agricultural technology company, we will offer free installation of predatory mites and comprehensive training to all participating farmers.
• Demand Treatment: This group will receive demand-side economic incentives. Simultaneously, a large-chain supermarket company will commit to purchasing the farmers' uncontaminated and certified agricultural products at a premium above the standard market rate. This pricing strategy provides a direct financial incentive for farmers to adopt this environmentally friendly pest control technology.
• Supply + Demand Treatment: This group will receive both supply-side technical support and demand-side economic incentives. In partnership with the agricultural technology company, we will offer free installation of predatory mites and comprehensive training to all participating farmers. Simultaneously, a large-chain supermarket company will commit to purchasing the farmers' uncontaminated and certified agricultural products at a premium above the standard market rate. This pricing strategy provides a direct financial incentive for farmers to adopt this environmentally friendly pest control technology.
• Control Group: This group will not receive any interventions and will serve as the baseline for comparison to assess the impact of the various interventions on the adoption of green pest control technologies. Control farmers will be selected from both villages with and without any treatment farmers, which will allow us to identify information spillovers.
Intervention Start Date
2025-03-10
Intervention End Date
2026-07-10

Primary Outcomes

Primary Outcomes (end points)
Our outcome variables will include several key metrics: 1) Adoption Rate: We will measure the percentage of farmers who successfully integrate and maintain the use of the provided green pest control technologies within their farming practices. 2) Pesticide Residue Testing: We will conduct tests to determine the levels of pesticide residues in agricultural products, and whether they meet food safety standards. 3) Farmer Beliefs and Learning: We will assess how farmers' perception and knowledge about green pest control technologies evolve over time. 4) Health Benefits: We will survey farmers about their health outcomes, to measure the non-pecuniary benefits of reducing pesticide use.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In collaboration with the provincial government, a major agricultural technology company, and a large chain retailer with more than 200 branches in the province, we propose a novel randomized field experiment targeting farms of mandarin orange --- the most important cash crop in the region. Our approach includes subsidizing the installation of natural enemy products (i.e., predatory mites) for farmers, as well as implementing a cross-randomization of low-pesticide-residue certification, which will help farmers secure higher procurement prices from the retailer.
With the help of the provincial government, we have obtained administrative dataset that includes a comprehensive list of mandarin orange producers across approximately 400 villages. This dataset provides detailed information on each farmer, including the owner's background and contact information, the location of the farm plot, the area of each plot, and the type of orange orchards. The dataset covers a total of 16,869 orange farmers who manage 117,595 mu of land, with an average of 7 mu per farmer dedicated to orchard cultivation.
To determine the origin of pesticide overuse, we will conduct a baseline survey to document basic facts about the beliefs of farmers regarding pesticide, risk preference, time preference, and the self-predicted optimal levels of pesticide use. We will also collect information on the market sources of pesticides, different pesticide varieties, and the prices and stock data of local pesticide traders.
Building on this foundation, we will randomly select 3,800 farmers. These selected farmers will be evenly divided into three treatment groups and one control group. We break down the design down below.
• Supply Treatment: This group will receive supply-side technical support. In partnership with the agricultural technology company, we will offer free installation of predatory mites and comprehensive training to all participating farmers.
• Demand Treatment: This group will receive demand-side economic incentives. Simultaneously, a large-chain supermarket company will commit to purchasing the farmers' uncontaminated and certified agricultural products at a premium above the standard market rate. This pricing strategy provides a direct financial incentive for farmers to adopt this environmentally friendly pest control technology.
• Supply + Demand Treatment: This group will receive both supply-side technical support and demand-side economic incentives. In partnership with the agricultural technology company, we will offer free installation of predatory mites and comprehensive training to all participating farmers. Simultaneously, a large-chain supermarket company will commit to purchasing the farmers' uncontaminated and certified agricultural products at a premium above the standard market rate. This pricing strategy provides a direct financial incentive for farmers to adopt this environmentally friendly pest control technology.
• Control Group: This group will not receive any interventions and will serve as the baseline for comparison to assess the impact of the various interventions on the adoption of green pest control technologies. Control farmers will be selected from both villages with and without any treatment farmers, which will allow us to identify information spillovers.
Experimental Design Details
Not available
Randomization Method
done by computer
Randomization Unit
farm
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
3800 farms
Sample size: planned number of observations
3800 farms
Sample size (or number of clusters) by treatment arms
3800 farms
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
CUHK-SZ IRB
IRB Approval Date
2024-07-18
IRB Approval Number
NA