⌁ Awesome World Model Hub Papers · Datasets · Projects
中文 GitHub
← Back to papers

From Economic Agents to Agentic Economies: A Systems Blueprint for Economic World Models

arXiv 2026 36.5 method, system, application

TLDR

This paper proposes a six-level capability ladder for building economic world models as generative engines, surveying existing work and providing an implementation blueprint for future simulation environments.

Reasoning

The paper provides a clear taxonomy and systematic survey of economic world models, which is a strength. However, it lacks concrete experimental validation or real-world implementations, focusing instead on a conceptual roadmap and literature review.

Read-first score

Read-first score 36.5, weighted from topical fit, citation, graph, method, reproducibility, and recency signals. Original total remains 35.

Recency 6%
100

Uses a gentle age decay so recent papers surface without erasing older foundations. 2026

Methodology quality 18%
60

Screens visible abstract and analysis fields for experiment, dataset, baseline, metric, and limitation evidence. markers=evaluation

Topical relevance 29%
50

Uses existing LLM keyword relevance scores normalized to 0-100. world model,world simulator,generative world model,interactive world model,video world model,world dynamics prediction,model-based reinforcement learning world model

Reproducibility 18%
30

Screens links and visible text for paper, code, dataset, artifact, and repository signals. pdf=True; code=False; dataset=False; markers=none

Citation impact 18%
0

Uses OpenAlex-shaped citation metadata as a bibliometric attention signal, separate from paper quality. cited_by_count=0

Citation velocity 12%
0

Citation velocity estimates citations per publication-year to reduce old-paper bias. velocity=0.00

Field roles

Frontier

Rank sensitivity

Stability: volatile; rank range: 183.

Keyword Scores

generative world model
9
world model
8
world simulator
6
interactive world model
5
world dynamics prediction
4
model-based reinforcement learning world model
2
video world model
1

Deep Analysis

Innovations

  • A six-level capability ladder for economic world models, spanning fixed rule-based agents to sim-to-real economic twins
  • An implementation roadmap for building generative economic world models with co-evolving agents, markets, and institutions
  • A systematic literature survey mapping existing economic simulation work to the capability ladder and identifying underexplored higher-level capabilities

Methodology

The paper develops a conceptual framework by organizing economic world model systems into a six-level capability ladder and then conducts a systematic literature survey to classify existing work according to these levels, revealing the distribution of research across lower and higher capabilities.

Key Results

The literature survey finds that existing work is concentrated in lower-level agent and simulation environments, while systems featuring self-evolving agents, endogenous institutions, persistent empirical alignment, and validated economic mechanisms remain rare.

Limitations

  • The work is a blueprint and literature survey, not an implemented or validated economic world model system
  • The higher-level capabilities (self-evolving agents, endogenous institutions, sim-to-real twins) are aspirational and currently lack empirical realization
  • The curated paper list provides a snapshot of the field and may not capture all relevant work or emerging developments

Resources

Paper

Tags