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EconEvals: Benchmarks and Litmus Tests for Economic Decision-Making by LLM Agents

Sara Fish, Julia Shephard, Minkai Li, Ran I. Shorrer, Yannai A. Gonczarowski · Mar 24, 2025 · Citations: 0

Automatic Metrics
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How to use this page

Low trust

Use this as background context only. Do not make protocol decisions from this page alone.

Best use

Background context only

What to verify

Validate the evaluation procedure and quality controls in the full paper before operational use.

Evidence quality

Low

Derived from extracted protocol signals and abstract evidence.

Abstract

We develop evaluation methods for measuring the economic decision-making capabilities and tendencies of LLMs. First, we develop benchmarks derived from key problems in economics -- procurement, scheduling, and pricing -- that test an LLM's ability to learn from the environment in context. Second, we develop the framework of litmus tests, evaluations that quantify an LLM's choice behavior on a stylized decision-making task with multiple conflicting objectives. Each litmus test outputs a litmus score, which quantifies an LLM's tradeoff response, a reliability score, which measures the coherence of an LLM's choice behavior, and a competency score, which measures an LLM's capability at the same task when the conflicting objectives are replaced by a single, well-specified objective. Evaluating a broad array of frontier LLMs, we (1) investigate changes in LLM capabilities and tendencies over time, (2) derive economically meaningful insights from the LLMs' choice behavior and chain-of-thought, (3) validate our litmus test framework by testing self-consistency, robustness, and generalizability. Overall, this work provides a foundation for evaluating LLM agents as they are further integrated into economic decision-making.

Abstract-only analysis — low confidence

All signals on this page are inferred from the abstract only and may be inaccurate. Do not use this page as a primary protocol reference.

  • This paper looks adjacent to evaluation work, but not like a strong protocol reference.
  • The available metadata is too thin to trust this as a primary source.
Human Eval Hub LLM-as-Judge Hub Pairwise Preference Hub

Should You Rely On This Paper?

This paper is adjacent to HFEPX scope and is best used for background context, not as a primary protocol reference.

Best use

Background context only

Use if you need

A secondary eval reference to pair with stronger protocol papers.

Main weakness

This paper looks adjacent to evaluation work, but not like a strong protocol reference.

Trust level

Low

Usefulness score

0/100 • Low

Treat as adjacent context, not a core eval-method reference.

Human Feedback Signal

Not explicit in abstract metadata

Evaluation Signal

Detected

Usefulness for eval research

Adjacent candidate

Extraction confidence 35%

If you are doing eval pipeline work, start here:

Human Eval Hub LLM-as-Judge Hub Pairwise Preference Hub Tool-Use Eval Hub

What We Could Verify

These are the protocol signals we could actually recover from the available paper metadata. Use them to decide whether this paper is worth deeper reading.

Human Feedback Types

missing

None explicit

No explicit feedback protocol extracted.

"We develop evaluation methods for measuring the economic decision-making capabilities and tendencies of LLMs."

Evaluation Modes

partial

Automatic Metrics

Includes extracted eval setup.

"We develop evaluation methods for measuring the economic decision-making capabilities and tendencies of LLMs."

Quality Controls

missing

Not reported

No explicit QC controls found.

"We develop evaluation methods for measuring the economic decision-making capabilities and tendencies of LLMs."

Benchmarks / Datasets

missing

Not extracted

No benchmark anchors detected.

"We develop evaluation methods for measuring the economic decision-making capabilities and tendencies of LLMs."

Reported Metrics

partial

Coherence

Useful for evaluation criteria comparison.

"Each litmus test outputs a litmus score, which quantifies an LLM's tradeoff response, a reliability score, which measures the coherence of an LLM's choice behavior, and a competency score, which measures an LLM's capability at the same task when the conflicting objectives are replaced by a single, well-specified objective."

Human Feedback Details

  • Uses human feedback: No
  • Feedback types: None
  • Rater population: Not reported
  • Expertise required: General

Evaluation Details

  • Evaluation modes: Automatic Metrics
  • Agentic eval: None
  • Quality controls: Not reported
  • Evidence quality: Low
  • Use this page as: Background context only

Protocol And Measurement Signals

Benchmarks / Datasets

No benchmark or dataset names were extracted from the available abstract.

Reported Metrics

coherence

Research Brief

Metadata summary

We develop evaluation methods for measuring the economic decision-making capabilities and tendencies of LLMs.

Based on abstract + metadata only. Check the source paper before making high-confidence protocol decisions.

Key Takeaways

  • We develop evaluation methods for measuring the economic decision-making capabilities and tendencies of LLMs.
  • First, we develop benchmarks derived from key problems in economics -- procurement, scheduling, and pricing -- that test an LLM's ability to learn from the environment in context.
  • Second, we develop the framework of litmus tests, evaluations that quantify an LLM's choice behavior on a stylized decision-making task with multiple conflicting objectives.

Researcher Actions

  • Compare this paper against nearby papers in the same arXiv category before using it for protocol decisions.
  • Validate inferred eval signals (Simulation environment) against the full paper.
  • Use related-paper links to find stronger protocol-specific references.

Caveats

  • Generated from abstract + metadata only; no PDF parsing.
  • Signals below are heuristic and may miss details reported outside the abstract.

Recommended Queries

Research Summary

Contribution Summary

  • We develop evaluation methods for measuring the economic decision-making capabilities and tendencies of LLMs.
  • First, we develop benchmarks derived from key problems in economics -- procurement, scheduling, and pricing -- that test an LLM's ability to learn from the environment in context.
  • Second, we develop the framework of litmus tests, evaluations that quantify an LLM's choice behavior on a stylized decision-making task with multiple conflicting objectives.

Why It Matters For Eval

  • We develop evaluation methods for measuring the economic decision-making capabilities and tendencies of LLMs.
  • First, we develop benchmarks derived from key problems in economics -- procurement, scheduling, and pricing -- that test an LLM's ability to learn from the environment in context.

Researcher Checklist

  • Gap: Human feedback protocol is explicit

    No explicit human feedback protocol detected.

  • Pass: Evaluation mode is explicit

    Detected: Automatic Metrics

  • Gap: Quality control reporting appears

    No calibration/adjudication/IAA control explicitly detected.

  • Gap: Benchmark or dataset anchors are present

    No benchmark/dataset anchor extracted from abstract.

  • Pass: Metric reporting is present

    Detected: coherence

Related Papers

Papers are ranked by protocol overlap, extraction signal alignment, and semantic proximity.

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