Ethical Standards & Guidelines

Research Conduct

Experimental Conduct

As researchers advancing causal inference, we adhere to rigorous ethical standards regarding human subjects to ensure safety and trust:

• Institutional Review Board (IRB) Approval: All experiments must be formally reviewed and approved by the appropriate institutional ethics committee prior to any data collection.
• Informed Consent: All participants must be provided with clear, comprehensible information about the study before consenting to participate.
• Non-Deception: In accordance with standard practices, researchers must avoid deceiving participants. Information and incentives provided to subjects must be truthful and accurately represented.

Transparency & Reproducibility

To advance economic science, research must be rigorously transparent and reproducible:

• Data and Code Availability: Researchers are expected to make their datasets, experimental instructions, and analytical code publicly available upon publication.
• Pre-registration: We strongly encourage the pre-registration of research designs and hypotheses before data collection begins to mitigate publication bias and ensure analytical integrity.
• Accurate Reporting: All methodologies, sample sizes, and exclusions must be thoroughly documented in research outputs.

Ethical AI Integration

As the Economic Science Society embraces the integration of Artificial Intelligence and machine learning into causal research, we commit to the responsible and transparent use of these powerful tools:

• Algorithmic Transparency: Researchers must strive to make their AI models and machine learning algorithms interpretable. The use of "black box" models should be explicitly justified.
• Data Privacy and Protection: When training models on observational data, researchers must employ rigorous anonymization techniques to safeguard digital privacy.
• Mitigating Algorithmic Bias: Researchers have a responsibility to audit their training data and AI models for embedded biases that could lead to skewed economic insights.
• Reproducibility of AI Models: Model architectures, hyperparameters, and computational environments used in AI-assisted research must be disclosed to ensure findings can be independently verified.

Professional Code of Conduct

The Economic Science Society (ESS) holds that principles of professional conduct should guide all members. The Society's founding purpose requires intellectual and professional integrity, which demands honesty, care, and transparency in conducting and presenting research.

Equal Opportunity and Respectful Discourse

The ESS encourages the “freedom of economic discussion,” requiring an environment where all can freely participate and where each idea is considered on its own merits. All members have a professional obligation to conduct civil and respectful discourse in all forums.

Unacceptable Conduct

Any form of discrimination, harassment, or bullying, including retaliation against a person who reports such behavior, violates the principles of equal opportunity and fair treatment.

• Solicitation of emotional or physical intimacy despite expressions or indications that it is unwelcome.
• Intentionally intimidating, threatening, harassing, or abusive actions or remarks.
• Defamation, including knowingly sharing false information intended to cause emotional distress or damage a colleague's professional reputation and career advancement.
• Prejudicial actions or comments that undermine the principles of fair treatment or free academic exchange.
• Sustained or aggressive disruption of talks or other activities that undermine free academic exchange.
• Physical assault or the real or implied threat of physical harm.

Research and Publication Integrity

Appropriate principles of professional conduct strictly apply to research and publication activities:

• Research should be conducted and reported with objectivity, accuracy, and high standards of quality.
• Prior and contemporaneous contributions of other researchers should be clearly acknowledged.
• Researchers should take responsibility and credit only for work they have actually performed.
• Referees should review submissions carefully, confidentially, and without prejudice, ensuring conflicts of interest are disclosed.