---
title: Macroeconomic Time Series Unit Roots
url: https://www.ml-quant.com/papers/repec/kap-compec-v-63-y-2024-i-6-d-10-1007-s10614-023-10397-0/
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:compec:v:63:y:2024:i:6:d:10.1007_s10614-023-10397-0
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs10614-023-10397-0%3Bh%3Drepec%3Akap%3Acompec%3Av%3A63%3Ay%3A2024%3Ai%3A6%3Ad%3A10.1007_s10614-023-10397-0
featured: 2024-07-10
citations: unknown
topic: Macro-Finance & Rates
---


# Macroeconomic Time Series Unit Roots

Machine Learning methods are more effective than Classical Bayesian methods in predicting unit root in univariate time-series models, particularly when there is class imbalance.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs10614-023-10397-0%3Bh%3Drepec%3Akap%3Acompec%3Av%3A63%3Ay%3A2024%3Ai%3A6%3Ad%3A10.1007_s10614-023-10397-0
- Identifier: RePEc:kap:compec:v:63:y:2024:i:6:d:10.1007_s10614-023-10397-0
- Released: 2024-07-10
- First featured: Quant Letter No. 56 (2024-07-10): https://www.ml-quant.com/issues/2024-07-10/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Macro-Finance & Rates

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