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Modelling Italian potential output and the output gap

Author

Listed:
  • Antonio Bassanetti

    () (Bank of Italy)

  • Michele Caivano

    () (Bank of Italy)

  • Alberto Locarno

    () (Bank of Italy)

Abstract

The aim of the paper is to estimate a reliable quarterly time-series of potential output for the Italian economy, exploiting four alternative approaches: a Bayesian unobserved component method, a univariate time-varying autoregressive model, a production function approach and a structural VAR. Based on a wide range of evaluation criteria, all methods generate output gaps that accurately describe the Italian business cycle over the past three decades. All output gap measures are subject to non-negligible revisions when new data become available. Nonetheless they still prove to be informative about the current cyclical phase and, unlike the evidence reported in most of the literature, helpful at predicting inflation compared with simple benchmarks. We assess also the performance of output gap estimates obtained by combining the four original indicators, using either equal weights or Bayesian averaging, showing that the resulting measures (i) are less sensitive to revisions; (ii) are at least as good as the originals at tracking business cycle fluctuations; (iii) are more accurate as inflation predictors.

Suggested Citation

  • Antonio Bassanetti & Michele Caivano & Alberto Locarno, 2010. "Modelling Italian potential output and the output gap," Temi di discussione (Economic working papers) 771, Bank of Italy, Economic Research and International Relations Area.
  • Handle: RePEc:bdi:wptemi:td_771_10
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Fioramanti, Marco, 2016. "Potential Output, Output Gap and Fiscal Stance: is the EC estimation of the NAWRU too sensitive to be reliable?," MPRA Paper 73762, University Library of Munich, Germany, revised Sep 2016.
    2. Fioramanti, Marco & Waldmann, Robert J., 2017. "The Econometrics of the EU Fiscal Governance: is the European Commission methodology still adequate?," MPRA Paper 81858, University Library of Munich, Germany.
    3. Fabio Busetti & Michele Caivano, 2013. "The trend-cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy," Temi di discussione (Economic working papers) 941, Bank of Italy, Economic Research and International Relations Area.
    4. Michele Caivano & Lisa Rodano & Stefano Siviero, 2010. "The transmission of the global financial crisis to the Italian economy. A counterfactual analysis, 2008-2010," Questioni di Economia e Finanza (Occasional Papers) 64, Bank of Italy, Economic Research and International Relations Area.
    5. Guido Bulligan & Lorenzo Burlon & Davide Delle Monache & Andrea Silvestrini, 2017. "Real and financial cycles: estimates using unobserved component models for the Italian economy," Questioni di Economia e Finanza (Occasional Papers) 382, Bank of Italy, Economic Research and International Relations Area.
    6. Fabio Busetti & Michele Caivano, 2016. "The trend–cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy and the Euro area," Empirical Economics, Springer, vol. 50(4), pages 1565-1587, June.
    7. Silvia Fabiani & Stefano Federico & Alberto Felettigh, 2016. "Adjusting the external adjustment: cyclical factors and the Italian current account," Questioni di Economia e Finanza (Occasional Papers) 346, Bank of Italy, Economic Research and International Relations Area.
    8. Libero Monteforte & Giordano Zevi, 2016. "An inquiry into manufacturing capacity in Italy after the double-dip recession," Questioni di Economia e Finanza (Occasional Papers) 302, Bank of Italy, Economic Research and International Relations Area.

    More about this item

    Keywords

    potential output; business cycle; Phillips curve; output gap;

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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