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Trends and cycles during the COVID-19 pandemic period

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  • Júlio, Paulo
  • Maria, José R.

Abstract

We perform several trend-cycle decompositions through the lens of two unobserved components models, herein estimated for Portugal and the euro area. Our procedure copes with the COVID-19’s consequences by explicitly considering potentially larger second moments during that period. This is achieved through a set of pandemic-specific shocks affecting only the 2020–21 period and embedded into estimation through a piecewise linear Kalman filter. Our methodology generates negligible historical revisions in key smoothed variables when the sample period is expanded until 2021:4, since pandemic shocks absorb a great deal of data volatility with minimal impacts on filtered data revisions or estimated parameters. Furthermore, non-pandemic shock volatility remains largely unaffected by the pandemic period. Innovations affecting the cycle in our preferred model are the key propellers of GDP developments during the COVID-19 pandemic period.

Suggested Citation

  • Júlio, Paulo & Maria, José R., 2024. "Trends and cycles during the COVID-19 pandemic period," Economic Modelling, Elsevier, vol. 139(C).
    • Handle: RePEc:eee:ecmode:v:139:y:2024:i:c:s0264999324001871
    DOI: 10.1016/j.econmod.2024.106830
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    1. Marko Melolinna & Máté Tóth, 2019. "Output gaps, inflation and financial cycles in the UK," Empirical Economics, Springer, vol. 56(3), pages 1039-1070, March.
    2. Duarte, Cláudia & Maria, José R. & Sazedj, Sharmin, 2020. "Trends and cycles under changing economic conditions," Economic Modelling, Elsevier, vol. 92(C), pages 126-146.
    3. James D. Hamilton, 2018. "Why You Should Never Use the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 831-843, December.
    4. Bodnár, Katalin & Le Roux, Julien & Lopez-Garcia, Paloma & Szörfi, Béla, 2020. "The impact of COVID-19 on potential output in the euro area," Economic Bulletin Articles, European Central Bank, vol. 7.
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    More about this item

    Keywords

    COVID-19; Semi-structural models; Unobserved components; Potential output; Output gap; Bayesian estimation;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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