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The Predictive Content of Business Survey Indicators: evidence from SIGE

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  • Tiziana Cesaroni
  • Stefano Iezzi

Abstract

Business surveys 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 business surveys predictive content by examining the leading properties of the main business survey indicators coming from 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 National Accounts reference series. We further analyze the forecast ability of the SIGE indicators to detect turning points using both discrete and continuous dynamic single equation models against their benchmark (B)ARIMA models. Overall the results indicate that SIGE business indicators are able to early detect turning points of their corresponding national account reference series. These findings are very important from a policy making point of view.

Suggested Citation

  • Tiziana Cesaroni & Stefano Iezzi, 2015. "The Predictive Content of Business Survey Indicators: evidence from SIGE," Working Papers LuissLab 15118, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    • Handle: RePEc:lui:lleewp:15118
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    Cited by:

    1. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    2. Deimante Teresiene & Greta Keliuotyte-Staniuleniene & Yiyi Liao & Rasa Kanapickiene & Ruihui Pu & Siyan Hu & Xiao-Guang Yue, 2021. "The Impact of the COVID-19 Pandemic on Consumer and Business Confidence Indicators," JRFM, MDPI, vol. 14(4), pages 1-23, April.
    3. Richard T. Curtin, 2022. "A New Theory of Expectations," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(3), pages 239-259, November.
    4. Liudmila Kitrar & Tamara Lipkind & Georgy Ostapkovich, 2020. "The Performance Of Business And Consumer Sentiment For Early Estimates Of Gdp Growth: Old Turning Points And New Challenges Of The Corona Crisis," HSE Working papers WP BRP 110/STI/2020, National Research University Higher School of Economics.
    5. Liudmila Kitrar & Tamara Lipkind, 2021. "Assessment Of GDP Growth After The Corona Crisis Using The Results Of Business And Consumer Surveys," HSE Working papers WP BRP 118/STI/2021, National Research University Higher School of Economics.
    6. Alessandro Mistretta, 2021. "Business cycle synchronization or business cycle transmission? The effect of the German slowdown on the Italian economy," Temi di discussione (Economic working papers) 1346, Bank of Italy, Economic Research and International Relations Area.
    7. Maria Rita Ippoliti & Fabiana Sartor & Luigi Martone, 2021. "Trade surveys: qualitative and quantitative indicators," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 75(4), pages 75-85, October-D.
    8. G. Bruno & L. Crosilla & P. Margani, 2019. "Inspecting the Relationship Between Business Confidence and Industrial Production: Evidence on Italian Survey Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(1), pages 1-24, April.

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    More about this item

    Keywords

    Business cycle; Business survey data; Turning points; cyclical analysis; Forecast accuracy; Macroeconomic forecasts;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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