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An Indicator of Economic Sentiment for the Italian Economy

Author

Listed:
  • Giancarlo Bruno

    (ISAE - Institute for Studies and Economic Analyses)

  • Marco Malgarini

    () (ISAE - Institute for Studies and Economic Analyses)

Abstract

The long and sustained expansion of the nineties has generated, especially in the US, widespread rumours about the “death of the cycle”. Nevertheless, towards the end of the last decade, it became clear that fluctuations of economic activity were far from being extinct. This has contributed greatly to a renewed interest among economists for the elaboration of statistical indicators capable of tracking and, if possible, anticipating the cyclical features of the economy. The aim of this paper is to build such an aggregate composite indicator for the Italian Economy, based on the ISAE surveys on households and those on the manufacturing, retail and construction sector. The first step of the analysis consists in using a dynamic factor model to extract a “common factor” from the different series of each survey, which may be interpreted as a composite confidence indicator. We then evaluate, for each survey, its in-sample and out-of sample properties, comparing them with those of the usual ISAE-EC Confidence indicators. Finally, we use again the dynamic factor model to build, from the sectoral Composite Indicator (CI), a Composite Aggregate Indicator (CAI) for the Italian economy, and test its ability in tracking the cyclical features of Italian aggregate GDP.

Suggested Citation

  • Giancarlo Bruno & Marco Malgarini, 2002. "An Indicator of Economic Sentiment for the Italian Economy," ISAE Working Papers 28, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
  • Handle: RePEc:isa:wpaper:28
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    References listed on IDEAS

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    Cited by:

    1. Hansson, Jesper & Jansson, Per & Löf, Mårten, 2003. "Business Survey Data: Do They Help in Forecasting the Macro Economy?," Working Papers 84, National Institute of Economic Research.
    2. Malgarini, Marco & Margani, Patrizia & Martelli, Bianca Maria, 2005. "Re-engineering the ISAE manufacturing survey," MPRA Paper 42440, University Library of Munich, Germany.
    3. Aslihan Atabek & Evren Erdogan Cosar & Saygin Sahinöz, 2005. "A New Composite Leading Indicator for Turkish Economic Activity," Emerging Markets Finance and Trade, M.E. Sharpe, Inc., vol. 41(1), pages 45-64, January.
    4. Lise Pichette, 2012. "Extracting Information from the Business Outlook Survey Using Statistical Approaches," Discussion Papers 12-8, Bank of Canada.
    5. Hyejung Moon & Jungick Lee, 2013. "Forecast evaluation of economic sentiment indicator for the Korean economy," IFC Bulletins chapters,in: Bank for International Settlements (ed.), Proceedings of the Sixth IFC Conference on "Statistical issues and activities in a changing environment", Basel, 28-29 August 2012., volume 36, pages 180-190 Bank for International Settlements.
    6. Gagea, Mariana, 2014. "Modelling the Confidence in Industry in Romania and other European Member Countries Using the Ordered Logit Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 15-34, March.
    7. Goggin, Jean, 2008. "An Analysis of the Potential of the European Commission Business and Consumer Surveys for Macroeconomic Forecasting," Quarterly Economic Commentary: Special Articles, Economic and Social Research Institute (ESRI), vol. 2008(4-Winter), pages 46-67.
    8. Hansson, Jesper & Jansson, Per & Lof, Marten, 2005. "Business survey data: Do they help in forecasting GDP growth?," International Journal of Forecasting, Elsevier, vol. 21(2), pages 377-389.
    9. Gagea Mariana, 2012. "The Contribution Of Business Confidence Indicators In Short-Term Forecasting Of Economic Development," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 617-623, July.
    10. Elena Doina Dascălu & Nicu Marcu & Ştefan Pete & Maria-Lenuţa Ulici & Vadim Dumitraşcu, 2016. "Dependent Business Climate. A Network-Based Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 138-152, March.

    More about this item

    Keywords

    Confidence Indicators; Leading Indicators; Cyclical Analysis;

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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