mlsanityData to 14 Oct 2026

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

arXiv 2503.18825 ↗First posted 24 Mar 2025cs.AI cs.CL cs.GTcited by 10

On the map: LLM agents and tool use → Social simulation and multi-agent debate

Abstract (arXiv)

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.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 26 of its 81 references that are in the map. First posted on arXiv 24 Mar 2025.

Builds on

26 of 81 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents25 Apr

Other references · 25

  1. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  2. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,191
  3. 2022Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studiescited by 515
  4. 2025Humanity's Last Examcited by 491
  5. 2022PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Changecited by 382
  6. 2024TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Taskscited by 326
  7. 2023FinanceBench: A New Benchmark for Financial Question Answeringcited by 270
  8. 2024FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AIcited by 243
  9. 2023Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmarkcited by 182
  10. 2024GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluationscited by 120
  11. 2024ARC Prize 2024: Technical Reportcited by 104
  12. 2025Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversationscited by 96
13 more
  1. 2024CyberSecEval 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Modelscited by 89
  2. 2025Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agentscited by 80
  3. 2023Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arenacited by 78
  4. 2024Can large language models explore in-context?cited by 76
  5. 2024How Far Are We on the Decision-Making of LLMs? Evaluating LLMs' Gaming Ability in Multi-Agent Environmentscited by 67
  6. 2025Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIscited by 67
  7. 2024Algorithmic Collusion by Large Language Modelscited by 62
  8. 2024LLM economicus? Mapping the Behavioral Biases of LLMs via Utility Theorycited by 47
  9. 2025Infrastructure for AI Agentscited by 41
  10. 2024How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?cited by 27
  11. 2024STEER: Assessing the Economic Rationality of Large Language Modelscited by 27
  12. 2022Artificial Intelligence and Auction Designcited by 20
  13. 2021On the Fairness of Machine-Assisted Human Decisionscited by 11

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 9.

10 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025Noise, Adaptation, and Strategy: Assessing LLM Fidelity in Decision-Making
  2. 2026EcoGym: Evaluating LLMs for Long-Horizon Plan-and-Execute in Interactive Economies
  3. 2026EcoAgent-Bench: Evaluating Economic Decision-Making in Budget-Constrained LLM Agents
  4. 2026Cost-Utility Alignment in LLM Agent Trajectories:Profiling,Attribution,Diagnosis,Adaptation,and Evaluation
  5. 2026Probing Outcome-Level Resemblance and Mechanism-Level Alignment in LLM Risk Decisions: Evidence from the St. Petersburg Game
  6. 2026Do LLMs Choose Like Humans? Using Cognitive Theory to Evaluate LLM Decision-Making
  7. 2025Predicting Effects, Missing Distributions: Evaluating LLMs as Human Behavior Simulators in Operations Management
  8. 2026LLM Consumer Behavior Theory: Foundations of a Novel Research Field