Your models and forecasts teach the next generation of AI.

Specialists in subfields like mechanism design, public economics, labor economics, and environmental economics are often more valuable than generalists because frontier models struggle most with domain-specific reasoning chains. Demand varies week to week, but if you hold a PhD or have published in your subfield, you will qualify for the highest-complexity tasks rather than being sidelined. You can indicate your specializations during onboarding and will only be matched to tasks within your expertise.

No active professional designation is required. Terac qualifies economists based on demonstrated expertise, which includes a graduate degree in economics, peer-reviewed publication history, or verifiable industry experience in roles like research economist, policy analyst, or quantitative analyst. If you hold a CFA or FSA that has lapsed, that credential still signals domain depth and will be noted in your profile, but it is not a gating requirement.

Yes, tasks often involve reviewing AI-generated analysis of real regulatory and institutional content, including central bank policy reasoning, fiscal scoring frameworks, and competition economics used in antitrust contexts. You are never asked to produce advice that would be delivered to a real client or regulator; your role is to assess whether the model's reasoning is technically sound, identifies the correct tradeoffs, and applies the appropriate economic framework. All tasks are clearly scoped so you can decline any that feel outside your comfort zone.

Tasks span a range of artifacts, including causal inference write-ups (difference-in-differences, RDD, IV designs), structural model expositions, welfare analysis narratives, and policy memo drafts. You may also be asked to create worked examples that demonstrate expert reasoning, such as walking through an identification strategy or critiquing an instrumental variables choice. The specific task type is shown before you accept it, so you can pick work that matches your strongest technical areas.

The work does not require you to endorse any policy position or fabricate data, both of which would conflict with AEA Code of Professional Conduct obligations around honesty and objectivity. You are evaluating and critiquing AI-generated reasoning, not authoring independent research or advocacy, so the work sits outside the scope of typical academic conflict-of-interest rules. If your institution has specific outside-activity disclosure requirements, you should review those independently, but most economists find this work is categorized alongside peer review or consulting rather than research authorship.