---
title: ML and Trade Agreements
url: https://www.ml-quant.com/papers/repec/kap-openec-v-34-y-2023-i-4-d-10-1007-s11079-022-09685-3/
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:kap:openec:v:34:y:2023:i:4:d:10.1007_s11079-022-09685-3
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs11079-022-09685-3%3Bh%3Drepec%3Akap%3Aopenec%3Av%3A34%3Ay%3A2023%3Ai%3A4%3Ad%3A10.1007_s11079-022-09685-3
featured: 2023-10-12
citations: unknown
topic: ML & AI Methods
---


# ML and Trade Agreements

The article uses machine learning to study the effect of free trade agreement policies on trade flows, concluding that more detailed agreements have a greater impact.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs11079-022-09685-3%3Bh%3Drepec%3Akap%3Aopenec%3Av%3A34%3Ay%3A2023%3Ai%3A4%3Ad%3A10.1007_s11079-022-09685-3
- Identifier: RePEc:kap:openec:v:34:y:2023:i:4:d:10.1007_s11079-022-09685-3
- Released: 2023-10-12
- First featured: Quant Letter No. 20 (2023-10-12): https://www.ml-quant.com/issues/2023-10-12/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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