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Nowcasting the output gap with shadow rates

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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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    References listed on IDEAS

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    1. James Morley & Benjamin Wong, 2020. "Estimating and accounting for the output gap with large Bayesian vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 1-18, January.
    2. Jing Cynthia Wu & Fan Dora Xia, 2016. "Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(2-3), pages 253-291, March.
    3. Krippner, Leo, 2013. "Measuring the stance of monetary policy in zero lower bound environments," Economics Letters, Elsevier, vol. 118(1), pages 135-138.
    4. Berger, Tino & Richter, Julia & Wong, Benjamin, 2022. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    5. Sophocles Mavroeidis, 2021. "Identification at the Zero Lower Bound," Econometrica, Econometric Society, vol. 89(6), pages 2855-2885, November.
    6. Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
      • Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Aruoba, S. Borağan & Mlikota, Marko & Schorfheide, Frank & Villalvazo, Sergio, 2022. "SVARs with occasionally-binding constraints," Journal of Econometrics, Elsevier, vol. 231(2), pages 477-499.
    8. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    9. Berger, Tino & Richter, Julia & Wong, Benjamin, 2022. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    10. Tino Berger & Tore Dubbert, 2022. "Government spending effects on the business cycle in times of crisis," CQE Working Papers 10022, Center for Quantitative Economics (CQE), University of Muenster.
    Full references (including those not matched with items on IDEAS)

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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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