Willingness to Accept 3-NOP among U.S. Dairy Farmers

Last registered on September 28, 2026
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Pre-Trial

Trial Information

General Information

Title
Willingness to Accept 3-NOP among U.S. Dairy Farmers
RCT ID
AEARCTR-0019814
Initial registration date
September 25, 2026

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
September 28, 2026, 9:50 AM EDT

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

Locations

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Primary Investigator

Name
Jasmin Wehner
Affiliation
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Wendong Zhang
PI Affiliation
PI Name
Christopher A. Wolf
PI Affiliation

Additional Trial Information

Status
In development
Start date
2026-10-07
End date
2026-12-31
Keywords
Agriculture, Behavior, Firms & Productivity
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Enteric fermentation accounts for roughly 50 percent of dairy cattle methane emissions, making
it a primary mitigation target (Dijkstra et al., 2018; Hristov et al., 2022). Among the inter-
ventions available, feed additives, especially 3-nitrooxypropanol (3-NOP), have the most robust
emission reduction potential across studies (de Oliveira et al., 2025; Kebreab et al., 2023; Pupo
et al., 2025; Van De Gucht et al., 2025; Maigaard et al., 2024; Islam et al., 2025; Maigaard
et al., 2025). Yet adoption ultimately depends on many factors such as net revenue, feed intake,
milk yield, management time that determine producers’ assessment of the technology.
We extend earlier work about the effectiveness of 3-NOP and the willingness to accept (WTA)
3-NOP among Swedish dairy farmers by further aspects related to technology adoption Gottlieb
and Rommel (2025). First, how domestic positive peer information compares to foreign negative
peer information in shaping adoption decisions, a distinction motivated by real-world reporting
on 3-NOP that ranges from optimistic domestic coverage of carbon-credit earnings (The Bul-
lvine, 2025) to mixed foreign accounts of Bovaer-linked feed intake and milk yield declines on
426 out of 642 Danish dairy farms (Nielsen et al., 2025; SEGES Innovation, 2025; The Bullvine,
2026). Second, how such information shape the beliefs about 3-NOP (Kumar et al., 2023; Dietrich et al., 2024). To address these gaps, this study
examines the market potential of 3-NOP in the U.S. dairy industry by eliciting producer atti-
tudes toward the technology and the compensation they would require to adopt it, particularly
after exposure to positive domestic versus negative foreign peer information.
External Link(s)

Registration Citation

Citation
Wehner, Jasmin, Christopher A. Wolf and Wendong Zhang. 2026. "Willingness to Accept 3-NOP among U.S. Dairy Farmers." AEA RCT Registry. September 28. https://doi.org/10.1257/rct.19814-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-10-07
Intervention End Date
2026-12-31

Primary Outcomes

Primary Outcomes (end points)
Belief Updating, WTA,
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We use a between-subject design, splitting the sample into groups that each receive a different
information treatment prior to the contingent valuation questions. Information treatments are
designed upon consultation with the project partners from the Clean Air Task Force (Fernanda
Ferreira), The Nature Conservancy (Partha Ray, Alisha Staggs), and the Environmental Defense
Fund (Joe Rudek). Every respondent will see the same information:
“Dairy farmers continually face decisions about feed management, including choices about feed
ingredients, ration formulation, and feeding strategies. These decisions can affect milk produc-
tion, cow health, and farm profitability.One feed additive that has received recent attention is
3- Nitrooxypropanol (3-NOP). It is designed to reduce enteric methane emissions from dairy
cows.” Followed by one out of the three information treatments are nothing in case of the control group
explained in Table 2. Additionally, we randomize the starting net revenue level presented in the contingent valuation question across eight values, ranging from $30 to $149 per cow per year in equal sized increments of approximately $17. In combination with the three information treatments plus control, we
have a total of 32 survey versions.

Table 2: Information Treatments
Treatment Text
1 Positive U.S. dairy farmers who implemented 3-NOP reported positive net revenue.
2 Negative Two-thirds of Danish dairy farmers surveyed in 2025 who used 3-NOP re-
ported reduced feed intake and milk yield in the first year after imple-
mentation.
3 Combined U.S. dairy farmers who implemented 3-NOP reported positive net rev-
enue.. Two-thirds of Danish dairy farmers surveyed in 2025 who used 3-
NOP reported reduced feed intake and milk yield in the first year after
implementation.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
Unit of randomization is the dairy farm
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Unit of randomization is the individual farmer
Sample size: planned number of observations
572 respondents from dairy operators
Sample size (or number of clusters) by treatment arms
The sample size is determined by power analysis below using the R package pwr (Champely
et al., 2020). Calculation is based on four independent groups, one representing each information
treatment. The recruitment target is therefore a minimum of 572, with the goal of reaching
600 total to mitigate the risk of insufficient power due to incomplete responses. According to
response rates of 18 percent in earlier surveys to dairy farmers conducted in October 2025 and
January 2026 as well as other producer surveys in high income countries (Slijper et al., 2026),
we will send the survey to 3,200 dairy farmers.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Institutional Review Board for Human Participants Cornell University
IRB Approval Date
2026-09-02
IRB Approval Number
IRB0151185
Analysis Plan

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