Causal Claims in Economics
Abstract
As economics scales, a key bottleneck is representing what papers claim in a comparable, aggregable form. We introduce evidence-annotated claim graphs that map each paper into a directed network of standardized economic concepts (nodes) and stated relationships (edges), with each edge labeled by evidentiary basis, including whether it is supported by causal inference designs or by non-causal evidence. Using a structured multi-stage AI workflow, we construct claim graphs for 44,852 economics papers from 1980-2023. The share of causal edges rises from 7.7% in 1990 to 31.7% in 2020. Measures of causal narrative structure and causal novelty are positively associated with top-five publication and long-run citations, whereas non-causal counterparts are weakly related or negative.
Keywords
Cite
@article{arxiv.2501.06873,
title = {Causal Claims in Economics},
author = {Prashant Garg and Thiemo Fetzer},
journal= {arXiv preprint arXiv:2501.06873},
year = {2026}
}
Comments
Data, code, prompts, and workflow documentation are publicly available at our GitHub repository: https://github.com/prashgarg/CausalClaimsInEconomics