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A robust method to date recessions and compute output gaps: the Portuguese case

Author

Listed:
  • João B. Assunção

    (Católica Lisbon School of Business & Economics, Universidade Católica Portuguesa)

  • Pedro Afonso Fernandes

    (Católica Lisbon School of Business & Economics, Universidade Católica Portuguesa)

Abstract

The application of the Hodrick-Prescott (HP) and other linear filters to remove trend and extract business cycles in macroeconomic time series is a common practice despite its limitations, namely, in signaling recessions. Median filters and other nonlinear techniques can perform better by accommodating sharp but fundamental changes in the growth trend and passing only the relevant information to the cycle component, a possible measure of the output gap of an economy. An application to the Portuguese relevant macroeconomic series confirmed the robustness of nonlinear filters in signaling the recessions and recoveries. In particular, the Mosheiov-Raveh (MR) filter estimates piecewise trend growth paths that naturally date the specific periods of the Portuguese economy since 1977.

Suggested Citation

  • João B. Assunção & Pedro Afonso Fernandes, 2025. "A robust method to date recessions and compute output gaps: the Portuguese case," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 24(1), pages 101-121, January.
    • Handle: RePEc:spr:portec:v:24:y:2025:i:1:d:10.1007_s10258-024-00259-4
    DOI: 10.1007/s10258-024-00259-4
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    References listed on IDEAS

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    More about this item

    Keywords

    Time series models; Trend estimation; Business cycles; Linear and nonlinear filtering;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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