---
title: Validating Causal Models with Quantitative Probing
url: https://www.ml-quant.com/papers/repec/bpj-causin-v-11-y-2023-i-1-p-23-n-1019/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:bpj:causin:v:11:y:2023:i:1:p:23:n:1019
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1515%2Fjci-2022-0060%3Bh%3Drepec%3Abpj%3Acausin%3Av%3A11%3Ay%3A2023%3Ai%3A1%3Ap%3A23%3An%3A1019
featured: 2024-09-10
citations: unknown
topic: Econometrics & Forecasting
---


# Validating Causal Models with Quantitative Probing

The piece introduces a new method called quantitative probing for validating causal models, showcasing its success in simulations and offering a guide for its application in causal modelling.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1515%2Fjci-2022-0060%3Bh%3Drepec%3Abpj%3Acausin%3Av%3A11%3Ay%3A2023%3Ai%3A1%3Ap%3A23%3An%3A1019
- Identifier: RePEc:bpj:causin:v:11:y:2023:i:1:p:23:n:1019
- Released: 2023-06-12
- First featured: Quant Letter No. 65 (2024-09-10): https://www.ml-quant.com/issues/2024-09-10/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Econometrics & Forecasting

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