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The Bank of Italy econometric model: an update of the main equations and model elasticities

Author

Listed:
  • Guido Bulligan

    () (Bank of Italy)

  • Fabio Busetti

    () (Bank of Italy)

  • Michele Caivano

    () (Bank of Italy)

  • Pietro Cova

    () (Bank of Italy)

  • Davide Fantino

    () (Bank of Italy)

  • Alberto Locarno

    () (Bank of Italy)

  • Lisa Rodano

    () (Bank of Italy)

Abstract

The Bank of Italy quarterly econometric model (BIQM) is a large-scale ‘semi structural’ macro-econometric model. It tries to strike the right balance between theoretical rigour and statistical fit to the data. This paper provides an update of the features and the properties of the model, focussing on the empirical estimates of its main equations and on the system responses to various shocks; interactions and feedback mechanisms between the financial and the real side of the economy are also illustrated. The BIQM is primarily used to produce macroeconomic forecasts, but it is also employed – in conjunction with other tools – for evaluating the impact of monetary and fiscal policy options and for counterfactual analyses. Examples of the types of macro-economic analyses carried out with the model are provided.

Suggested Citation

  • Guido Bulligan & Fabio Busetti & Michele Caivano & Pietro Cova & Davide Fantino & Alberto Locarno & Lisa Rodano, 2017. "The Bank of Italy econometric model: an update of the main equations and model elasticities," Temi di discussione (Economic working papers) 1130, Bank of Italy, Economic Research and International Relations Area.
  • Handle: RePEc:bdi:wptemi:td_1130_17
    as

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    File URL: http://www.bancaditalia.it/pubblicazioni/temi-discussione/2017/2017-1130/en_tema_1130.pdf
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    References listed on IDEAS

    as
    1. Stefano Siviero & Daniele Terlizzese, 2008. "Macroeconomic Forecasting: Debunking a Few Old Wives' Tales," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2007(3), pages 287-316.
    2. Lorenzo Bencivelli & Massimiliano Marcellino & Gianluca Moretti, 2012. "Selecting predictors by using Bayesian model averaging in bridge models," Temi di discussione (Economic working papers) 872, Bank of Italy, Economic Research and International Relations Area.
    3. 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.
    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. Alessandro Notarpietro & Lisa Rodano, 2016. "The evolution of bad debts in Italy during the global financial crisis and the sovereign debt crisis: a counterfactual analysis," Questioni di Economia e Finanza (Occasional Papers) 350, Bank of Italy, Economic Research and International Relations Area.
    6. Ugo Albertazzi & Alessandro Notarpietro & Stefano Siviero, 2016. "An inquiry into the determinants of the profitability of Italian banks," Questioni di Economia e Finanza (Occasional Papers) 364, Bank of Italy, Economic Research and International Relations Area.
    7. Fabio Busetti & Claire Giordano & Giordano Zevi, 2016. "The Drivers of Italy’s Investment Slump During the Double Recession," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 2(2), pages 143-165, July.
    8. Fabio Busetti & Pietro Cova, 2013. "The macroeconomic impact of the sovereign debt crisis: a counterfactual analysis for the Italian economy," Questioni di Economia e Finanza (Occasional Papers) 201, Bank of Italy, Economic Research and International Relations Area.
    9. Claudia Miani & Stefano Siviero, 2010. "A non-parametric model-based approach to uncertainty and risk analysis of macroeconomic forecast," Temi di discussione (Economic working papers) 758, Bank of Italy, Economic Research and International Relations Area.
    10. van Els, Peter J. A. & Morgan, Julian & Locarno, Alberto & Villetelle, Jean-Pierre, 2001. "Monetary policy transmission in the euro area: What do aggregate and national structural models tell us?," Working Paper Series 94, European Central Bank.
    11. Pietro Cova & Giuseppe Ferrero, 2015. "The Eurosystem�s asset purchase programmes for monetary policy purposes," Questioni di Economia e Finanza (Occasional Papers) 270, Bank of Italy, Economic Research and International Relations Area.
    12. Baffigi, Alberto & Golinelli, Roberto & Parigi, Giuseppe, 2004. "Bridge models to forecast the euro area GDP," International Journal of Forecasting, Elsevier, vol. 20(3), pages 447-460.
    13. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    14. Felettigh, Alberto & Giordano, Claire & Oddo, Giacomo & Romano, Valentina, 2016. "New indicators to assess price-competitiveness developments in the four largest euro-area countries and in their main trading partners," Journal of Economic and Social Measurement, IOS Press, issue 3, pages 203-235.
    15. Marco Casiraghi & Eugenio Gaiotti & Lisa Rodano & Alessandro Secchi, 2013. "The impact of unconventional monetary policy on the Italian economy during the sovereign debt crisis," Questioni di Economia e Finanza (Occasional Papers) 203, Bank of Italy, Economic Research and International Relations Area.
    16. Matthieu Bussière & Giovanni Callegari & Fabio Ghironi & Giulia Sestieri & Norihiko Yamano, 2013. "Estimating Trade Elasticities: Demand Composition and the Trade Collapse of 2008-2009," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(3), pages 118-151, July.
    17. Fair, Ray C & Jaffee, Dwight M, 1972. "Methods of Estimation for Markets in Disequilibrium," Econometrica, Econometric Society, vol. 40(3), pages 497-514, May.
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    Cited by:

    1. Valerio Della Corte & Stefano Federico & Enrico Tosti, 2018. "Unwinding external stock imbalances? The case of Italy’s net international investment position," Questioni di Economia e Finanza (Occasional Papers) 446, Bank of Italy, Economic Research and International Relations Area.
    2. Matteo Bugamelli & Silvia Fabiani & Stefano Federico & Alberto Felettigh & Claire Giordano & Andrea Linarello, 2018. "Back on Track? A Macro–Micro Narrative of Italian Exports," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 4(1), pages 1-31, March.
    3. Giordano, Claire & Marinucci, Marco & Silvestrini, Andrea, 2019. "The macro determinants of firms' and households' investment: Evidence from Italy," Economic Modelling, Elsevier, vol. 78(C), pages 118-133.
    4. Casiraghi, Marco & Gaiotti, Eugenio & Rodano, Lisa & Secchi, Alessandro, 2018. "A “reverse Robin Hood”? The distributional implications of non-standard monetary policy for Italian households," Journal of International Money and Finance, Elsevier, vol. 85(C), pages 215-235.
    5. Robert-Paul Berben & Ide Kearney & Robert Vermeulen, 2018. "DELFI 2.0, DNB's Macroeconomic Policy Model of the Netherlands," DNB Occasional Studies 1605, Netherlands Central Bank, Research Department.
    6. Walter Paternesi Meloni, 2018. "Italy’s Price Competitiveness: An Empirical Assessment Through Export Elasticities," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 4(3), pages 421-462, November.

    More about this item

    Keywords

    macro-econometric models; Italy; forecasting; policy simulation;

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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