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ForeComp: An R Package for Comparing Predictive Accuracy Using Fixed-Smoothing Asymptotics

Author

Listed:
  • Nathan Schor
  • Minchul Shin

Abstract

We introduce ForeComp, an R package for comparing predictive accuracy using Diebold–Mariano type tests of equal predictive ability with standard and fixed-smoothing inference. The package provides a common interface for loss-differential based testing and includes Plot Tradeoff, a visual diagnostic for bandwidth sensitivity and the size–power tradeoff. We illustrate the toolkit with Survey of Professional Forecasters applications and Monte Carlo evidence on finite-sample performance.

Suggested Citation

  • Nathan Schor & Minchul Shin, 2026. "ForeComp: An R Package for Comparing Predictive Accuracy Using Fixed-Smoothing Asymptotics," Working Papers 26-38, Federal Reserve Bank of Philadelphia.
    • Handle: RePEc:fip:fedpwp:103596
    DOI: 10.21799/frbp.wp.2026.38
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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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