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The predictive content of business survey indicators: evidence from SIGE

Listed author(s):
  • Tatiana Cesaroni

    ()

    (Bank of Italy)

  • Stefano Iezzi

    ()

    (Bank of Italy)

Business survey indicators represent an important tool in economic analysis and forecasting practices. While there is wide consensus on the coincident properties of such data, there is mixed evidence on their ability to predict macroeconomic developments in the short term. In this study we extend the previous research on the predictive content of business surveys by examining the leading properties of the main business survey indicators of the Italian Survey on Inflation and Growth Expectations (SIGE). To this end, we provide a complete characterization of the business cycle properties of survey data (volatility, stationarity, turning points etc.) and we compare them with the national accounts reference series. We further analyse the ability of SIGE indicators to detect turning points using both discrete and continuous dynamic single equation models as compared with their benchmark (B)ARIMA models. Overall, the results indicate that SIGE business indicators are able to make detect early the turning points of their corresponding national account reference series. These findings are very important from a policy-making point of view.

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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 1031.

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Date of creation: Sep 2015
Handle: RePEc:bdi:wptemi:td_1031_15
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  1. Tatiana Cesaroni, 2010. "Estimating potential output using business survey data in a svar framework," Economics Bulletin, AccessEcon, vol. 30(3), pages 2249-2258.
  2. Lemmens, Aurelie & Croux, Christophe & Dekimpe, Marnik G., 2005. "On the predictive content of production surveys: A pan-European study," International Journal of Forecasting, Elsevier, vol. 21(2), pages 363-375.
  3. Tatiana Cesaroni, 2011. "The cyclical behavior of the Italian business survey data," Empirical Economics, Springer, vol. 41(3), pages 747-768, December.
  4. Cesaroni, Tatiana & Maccini, Louis & Malgarini, Marco, 2011. "Business cycle stylized facts and inventory behaviour: New evidence for the Euro area," International Journal of Production Economics, Elsevier, vol. 133(1), pages 12-24, September.
  5. Abberger, Klaus, 2007. "Qualitative business surveys and the assessment of employment -- A case study for Germany," International Journal of Forecasting, Elsevier, vol. 23(2), pages 249-258.
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  9. Giancarlo Bruno & Claudio Lupi, 2004. "Forecasting industrial production and the early detection of turning points," Empirical Economics, Springer, vol. 29(3), pages 647-671, September.
  10. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters,in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1 National Bureau of Economic Research, Inc.
  11. Michael Dueker, 2005. "Dynamic Forecasts of Qualitative Variables: A Qual VAR Model of U.S. Recessions," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 96-104, January.
  12. Wheeler, Tracy, 2010. "What can we learn from surveys of business expectations?," Bank of England Quarterly Bulletin, Bank of England, vol. 50(3), pages 190-198.
  13. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2005. "On the Predictive Content of Production Surveys : a Pan-European Study," Other publications TiSEM adab9f0e-7dfd-4dc4-bd92-b, Tilburg University, School of Economics and Management.
  14. Bergstrom, Reinhold, 1995. "The relationship between manufacturing production and different business survey series in Sweden 1968-;1992," International Journal of Forecasting, Elsevier, vol. 11(3), pages 379-393, September.
  15. Raffaele Tartaglia-Polcini, 2011. "Inflation forecasts from the Bank of Italy-Sole 24 Ore survey of expectations of inflation and growth," IFC Bulletins chapters,in: Bank for International Settlements (ed.), Proceedings of the IFC Conference on "Initiatives to address data gaps revealed by the financial crisis", Basel, 25-26 August 2010, volume 34, pages 278-292 Bank for International Settlements.
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