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Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods

Marcelo C. Medeiros, Gabriel F. R. Vasconcelos, Álvaro Veiga, Eduardo Zilberman

Journal of Business & Economic Statistics, 2019. DOI 10.1080/07350015.2019.1637745

Has this study been replicated?

The atlas records 1 replication of this study. Recorded outcomes: 1 mixed. The earliest on record is from 2024.

Replications

• The benefits of forecasting inflation with machine learning: New evidence, Naghi et al. (2024). Journal of Applied Econometrics. Outcome recorded: mixed. Our narrow replication confirms the main findings of the original paper. However, the wider replication results suggest that other methods are competitive with RF and often more accurate. Outcome read from the abstract. View paper

Cite this record

Medeiros, M. C., Vasconcelos, G. F. R., Veiga, Á., & Zilberman, E. (2019). Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods. Journal of Business & Economic Statistics, 39(1), 98–119. https://doi.org/10.1080/07350015.2019.1637745

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