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Nowcasting the output gap with shadow rates

Author

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  • Dubbert, Tore
  • Kempa, Bernd

Abstract

In a recent paper, Berger et al. (2023) employ the Beveridge–Nelson trend-cycle decomposition based on a mixed-frequency Bayesian vector autoregressive model to nowcast the U.S. output gap, producing more timely estimates compared to a set of alternative measures. Applying the model to a much shorter and slightly modified data set, we show that utilizing shadow interest rates instead of the federal funds rate in the model produces output gap estimates that are more in line with other measures such as those provided by the CBO or the IMF, and further enhances the timeliness of nowcasts.

Suggested Citation

  • Dubbert, Tore & Kempa, Bernd, 2024. "Nowcasting the output gap with shadow rates," Economics Letters, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:ecolet:v:236:y:2024:i:c:s0165176524000661
    DOI: 10.1016/j.econlet.2024.111583
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    More about this item

    Keywords

    Nowcasting; Output gap; Post-covid economic recovery;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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