Eliciting farmers' preferences for agricultural policy reform

Last registered on October 23, 2025
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Pre-Trial

Trial Information

General Information

Title
Eliciting farmers' preferences for agricultural policy reform
RCT ID
AEARCTR-0017024
Initial registration date
October 17, 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
October 23, 2025, 6:59 AM EDT

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

Locations

Country
Macedonia (the former Yugoslav Republic of)
Region

Primary Investigator

Name
Andreas Drichoutis
Affiliation
Agricultural University of Athens
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Marina Nacka
PI Affiliation
Ss. Cyril and Methodius University in Skopje
Contact Investigator
PI Name
Claudia Bazzani
PI Affiliation
University of Verona
Contact Investigator
PI Name
Dragi Dimitrievski
PI Affiliation
Ss. Cyril and Methodius University in Skopje
Contact Investigator

Additional Trial Information

Status
In development
Start date
2025-10-01
End date
2025-11-15
Keywords
Agriculture, Behavior
Additional Keywords
Discrete choice experiment (DCE), Direct payments, Rural development, Agricultural subsidies, Stated preferences
JEL code(s)
Q12, Q15, Q18, C35, O13
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study investigates farmers' preferences for alternative agricultural support schemes in North Macedonia using a discrete choice experiment (DCE). The research aims to inform policy design during the country’s alignment with the European Union’s Common Agricultural Policy. in the DCE, farmers face trade-offs between complex but more generous direct payment systems and simplified schemes that reallocate part of the agricultural budget toward rural development. The DCE presents respondents with 15 choice tasks, each consisting of two hypothetical new programs and the current national scheme. Programs vary along six key attributes: share of funds allocated to rural development, type of direct payments (from fully coupled to fully decoupled), reliability and administrative burden, level and scope of investment aid, environmental conditionality, and change in total annual support relative to the status quo. The design is Bayesian D-efficient, informed by a pilot with active farmers. The analysis will estimate preference structures and heterogeneity across farmers, focusing on how simplification, reliability, and the degree of coupling influence support for different policy directions. The findings will provide evidence to guide ongoing subsidy reforms and the balance between income support, investment incentives, and rural development priorities in agricultural policy.
External Link(s)

Registration Citation

Citation
Bazzani, Claudia et al. 2025. "Eliciting farmers' preferences for agricultural policy reform." AEA RCT Registry. October 23. https://doi.org/10.1257/rct.17024-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
The intervention consists of a discrete choice experiment (DCE) in which farmers evaluate alternative agricultural policy programs. Each program is described by six attributes with multiple levels:
- Share of rural development budget: 10% (status quo), 25%, 35%
- Type of direct payments: Fully coupled (current system), partially decoupled simplified, fully decoupled
- Reliability and administrative burden: Low (often late; ≈40h/year, status quo), Medium (most payments by June; ≈20h/year), High (all payments by June; ≈8h/year)
- Investment aid (grants): Up to 50% support (current budget), up to 50% support (higher budget), up to 60% support
- Environmental conditionality: Minimum legal rules, basic cross-compliance, eco-scheme
- Change in total annual support: –20%, –15%, –10%, –5%, 0%, +5%, +10%, +15%, +20%

The full factorial design results in 3*3*3*3*3*9 = 2187 possible combinations per policy alternative, which makes a complete enumeration infeasible. To achieve statistical efficiency while keeping respondent burden reasonable, a Bayesian D-efficient design was used to select a balanced subset of 15 choice tasks per respondent.

In each task, farmers choose one option among two hypothetical new policy programs (A and B) and the current policy (status quo), which remains constant across all tasks. All participants complete the same 15 optimized choice tasks, allowing the estimation of trade-offs and preference heterogeneity across the six policy dimensions.
Intervention (Hidden)
Intervention Start Date
2025-10-01
Intervention End Date
2025-11-15

Primary Outcomes

Primary Outcomes (end points)
Choice outcome per task: Indicator of the selected alternative in each task: Program A, Program B, or Status Quo (primary dependent variable).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The study employs a discrete choice experiment (DCE) to elicit farmers’ preferences for alternative agricultural support programs in North Macedonia. Each respondent completes 15 choice tasks, each containing two hypothetical policy programs (A and B) and the current national policy (status quo). The six attributes and their levels are described in the intervention section.

The design is Bayesian D-efficient, developed based on priors from a pilot study with 21 farmers to improve precision and reduce cognitive burden. All respondents face the same optimized set of 15 tasks, ensuring comparability across individuals.

The sample will consist of active farmers recruited through regional agricultural offices and farmer associations. Participation occurs in controlled laboratory or field settings, where respondents complete the survey individually under supervision.

Randomization occurs at the level of choice task presentation (order randomized across respondents) and option placement (left/right randomization of Programs A and B) to avoid ordering or positional bias.

The analysis will estimate mixed logit and latent class models to capture heterogeneity in preferences and derive willingness-to-pay measures for improvements in reliability, administrative simplicity, investment aid, and rural development funding relative to total payment changes.
Experimental Design Details
Randomization Method
Any randomization are performed by the software/platform (Qualtrics).
Randomization Unit
Individual.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
21 farmers for the pilot, approx. 220 farmers in the main phase.
Sample size: planned number of observations
the number of farmers * (15 choice tasks) * (3 choices per task)
Sample size (or number of clusters) by treatment arms
See pre-registration document.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
See pre-registration document.
Supporting Documents and Materials

Documents

Document Name
pre-registration template
Document Type
other
Document Description
Sagebiel, J., Schulze, C., & Rommel, J. (2025). A Preregistration Template for Choice Experiments (0.1). Zenodo. https://doi.org/10.5281/zenodo.14993225
File
pre-registration template

MD5: 3b2b131ec4a6ca28a8aec7f0fd6c28e2

SHA1: 7c712fcc823b81fe72f6caceb585d8f650be9493

Uploaded At: October 16, 2025

IRB

Institutional Review Boards (IRBs)

IRB Name
Board of Ethics and Deontology, Agricultural University of Athens
IRB Approval Date
2025-09-22
IRB Approval Number
92
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials