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Forecasting inflation with the hedged random forest

Author

Listed:
  • Elliot Beck
  • Michael Wolf

Abstract

Accurately forecasting inflation is critical for economic policy, financial markets, and broader societal stability. In recent years, machine learning methods have shown great potential for improving the accuracy of inflation forecasts; specifically, the random forest stands out as a particularly effective approach that consistently outperforms traditional benchmark models in empirical studies. Building on this foundation, this paper adapts the hedged random forest (HRF) framework of Beck et al. (2024) for the task of forecasting inflation. Unlike the standard random forest, the HRF employs non-equal (and even negative) weights of the individual trees, which are designed to improve forecasting accuracy. We develop estimators of the HRF's two inputs, the mean and the covariance matrix of the errors corresponding to the individual trees, that are customized for the task at hand. An extensive empirical analysis demonstrates that the proposed approach consistently outperforms the standard random forest.

Suggested Citation

  • Elliot Beck & Michael Wolf, 2025. "Forecasting inflation with the hedged random forest," Working Papers 2025-07, Swiss National Bank.
  • Handle: RePEc:snb:snbwpa:2025-07
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    File URL: https://www.snb.ch/en/publications/research/working-papers/2025/working_paper_2025_07
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    More about this item

    Keywords

    Exponentially weighted moving average; Linear shrinkage; Machine learning;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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