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Modelling Italian potential output and the output gap

  • Antonio Bassanetti

    ()

    (Bank of Italy)

  • Michele Caivano

    ()

    (Bank of Italy)

  • Alberto Locarno

    ()

    (Bank of Italy)

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.

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Paper provided by Bank of Italy, Economic Research and International Relations Area in its series Temi di discussione (Economic working papers) with number 771.

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Date of creation: Sep 2010
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Handle: RePEc:bdi:wptemi:td_771_10
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Web page: http://www.bancaditalia.it

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  1. Claude Giorno & Pete Richardson & Deborah Roseveare & Paul van den Noord, 1995. "Estimating Potential Output, Output Gaps and Structural Budget Balances," OECD Economics Department Working Papers 152, OECD Publishing.
  2. Isabell Koske & Nigel Pain, 2008. "The Usefulness of Output Gaps for Policy Analysis," OECD Economics Department Working Papers 621, OECD Publishing.
  3. Athanasios Orphanides & Simon van Norden, 2004. "The reliability of inflation forecasts based on output gap estimates in real time," Finance and Economics Discussion Series 2004-68, Board of Governors of the Federal Reserve System (U.S.).
  4. Eugenio Gaiotti, 2008. "Has globalisation changed the Phillips curve? Firm-level evidence on the effect of activity on prices," Temi di discussione (Economic working papers) 676, Bank of Italy, Economic Research and International Relations Area.
  5. Harvey, A.C. & Trimbur, T.M. & van Dijk, H.K., 2005. "Trends and cycles in economic time series: A Bayesian approach," Econometric Institute Research Papers EI 2005-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  6. Parigi, Giuseppe & Siviero, Stefano, 2001. "An investment-function-based measure of capacity utilisation.: Potential output and utilised capacity in the Bank of Italy's quarterly model," Economic Modelling, Elsevier, vol. 18(4), pages 525-550, December.
  7. Olivier Jean Blanchard & Danny Quah, 1988. "The Dynamic Effects of Aggregate Demand and Supply Disturbance," Working papers 497, Massachusetts Institute of Technology (MIT), Department of Economics.
  8. Bassanetti, Antonio & Döpke, Jörg & Torrini, Roberto & Zizza, Roberta, 2006. "Capital, labour and productivity: What role do they play in the potential GPD weakness of France, Germany and Italy?," Discussion Paper Series 1: Economic Studies 2006,09, Deutsche Bundesbank, Research Centre.
  9. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-47, July-Sept.
  10. Nigel Pain & Isabell Koske & Marte Sollie, 2006. "Globalisation and Inflation in the OECD Economies," OECD Economics Department Working Papers 524, OECD Publishing.
  11. Mark W. Watson, 2007. "How accurate are real-time estimates of output trends and gaps?," Economic Quarterly, Federal Reserve Bank of Richmond, issue Spr, pages 143-161.
  12. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
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