Trade-offs between internal and external validity in economic experiments to inform agricultural policy

Abstract Economic experiments are increasingly used to evaluate agri-environmental policies ex-ante. They typically rely on one of three subject pools: standard subject pool students, agricultural students, or farmers. While farmers are often considered most informative for policymaking, experiments outside controlled lab environments face challenges in identifying causal effects. Thus, trade-offs between internal and external validity arise but remain underexplored empirically. Using exploratory analyses, we compare conservation behaviour under a novel agri-environmental policy, four behavioural factors, and methodological measures across farmers, agricultural students, and standard subject pool students in lab, classroom, and online settings in Germany. Conservation behaviour and environmental preferences differ significantly across pools, indicating that student samples – even with agricultural backgrounds – cannot fully substitute for farmers. Yet agricultural samples also show threats to internal validity, including more extreme response times, miscomprehension, and attrition. Trade-offs are thus evident, demonstrating that experiments with standard subject pools and agricultural samples are complements rather than substitutes. We formulate design recommendations for researchers to address threats to internal validity in experiments involving agricultural samples.

Authors

Institutions

Publication Details

Journal
Q Open
Published
2026-03-12
DOI
https://doi.org/10.1093/qopen/qoag008
Primary Topic
Innovations in Educational Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trade-offs between internal and external validity in economic experiments to inform agricultural policy

Fabian Thomas, Thomas Rellensmann
Q Open
Innovations in Educational Methods
article

Trade-offs between internal and external validity in economic experiments to inform agricultural policy

Fabian Thomas, Thomas Rellensmann
article en

Abstract

Abstract Economic experiments are increasingly used to evaluate agri-environmental policies ex-ante. They typically rely on one of three subject pools: standard subject pool students, agricultural students, or farmers. While farmers are often considered most informative for policymaking, experiments outside controlled lab environments face challenges in identifying causal effects. Thus, trade-offs between internal and external validity arise but remain underexplored empirically. Using exploratory analyses, we compare conservation behaviour under a novel agri-environmental policy, four behavioural factors, and methodological measures across farmers, agricultural students, and standard subject pool students in lab, classroom, and online settings in Germany. Conservation behaviour and environmental preferences differ significantly across pools, indicating that student samples – even with agricultural backgrounds – cannot fully substitute for farmers. Yet agricultural samples also show threats to internal validity, including more extreme response times, miscomprehension, and attrition. Trade-offs are thus evident, demonstrating that experiments with standard subject pools and agricultural samples are complements rather than substitutes. We formulate design recommendations for researchers to address threats to internal validity in experiments involving agricultural samples.

Q Open
Osnabrück University (DE), Hochschule Osnabrück (DE)
Openalex Percentile: Top 21%
Innovations in Educational Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.