# Causal Claims in Economics

arXiv: https://arxiv.org/abs/2501.06873 · HTML: https://mlsanity.com/paper/2501.06873/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Jan 2025.

## Built on by (most cited first, 3 of 3)

- [EconCausal: A Context-Aware Economic Reasoning Benchmark for Large Language Models](https://mlsanity.com/paper/2510.07231/) (2025)
- [On Bob Dylan: A Computational Perspective](https://mlsanity.com/paper/2502.01772/) (2025)
- [DAGverse: Building Document-Grounded Semantic DAGs from Scientific Papers](https://mlsanity.com/paper/2603.25293/) (2026)

## Abstract (arXiv)

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.