Forecasting Recessions Using Machine Learning on Text Data and Mixed-Frequency Predictors

Yusuke Oh and Mototsugu Shintani
Additional contact information
Yusuke Oh: Deputy Director, Institute for Monetary and Economic Studies, Bank of Japan (E-mail: yuusuke.ou@boj.or.jp)
Mototsugu Shintani: The University of Tokyo (E-mail: shintani@e.u-tokyo.ac.jp)

No 26-E-07, IMES Discussion Paper Series from Institute for Monetary and Economic Studies, Bank of Japan

Abstract: We forecast Japanese recessions by integrating machine learning methods, mixed-frequency data, and text-based indicators within an unrestricted mixed data sampling (U-MIDAS) framework. The model combines monthly macroeconomic variables with weekly financial indicators and newspaper-based text indicators. A pseudo-real-time forecasting exercise over three decades shows that machine learning models consistently outperform traditional logit benchmarks. The model confidence set (MCS) suggests horizon dependence: Text indicators are more informative at short horizons, while financial variables are more informative at longer horizons. To improve interpretability, we apply sparse principal component analysis (Sparse PCA) to the text indicators and identify three economic narratives: 'Corporate Distress,' 'Financial Distress,' and 'Deflationary Pressure.' Furthermore, SHAP (SHapley Additive exPlanations) analysis indicates that different recession episodes are associated with different combinations of these narratives, underscoring the heterogeneous nature of economic downturns.

Keywords: business cycles; mixed data sampling; model confidence set; text analysis; recession forecasting (search for similar items in EconPapers)
JEL-codes: C32 C53 E37 O53 (search for similar items in EconPapers)
Date: 2026-03
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.imes.boj.or.jp/research/papers/english/26-E-07.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ime:imedps:26-e-07

Access Statistics for this paper

More papers in IMES Discussion Paper Series from Institute for Monetary and Economic Studies, Bank of Japan Contact information at EDIRC.
Bibliographic data for series maintained by Kinken ().