The Predictive Content of Business Survey Indicators: Evidence from SIGE
Tatiana Cesaroni and
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Stefano Iezzi: Bank of Italy
Journal of Business Cycle Research, 2017, vol. 13, issue 1, 75-104
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 forecast macroeconomic developments in the short term. In this study we extend the previous research on business surveys predictive content by examining for the first time 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 leading/coincident properties of SIGE data (turning points, average duration, synchronization etc.) with respect to the National Accounts reference series using both non parametric approaches (i.e. Harding and Pagan in J Monet Econ 49(2):365–381, 2002) and econometric models (discrete and continuous dynamic single equation models). Overall the results indicate that in both the approaches SIGE business indicators are able to early detect turning points of their corresponding national account reference series in almost all cases. Overall, the average lead of troughs is found to be higher than the average lead of peaks.
Keywords: Business survey data; Turning points; Pseudo real time; Forecast accuracy; Macroeconomic forecasts (search for similar items in EconPapers)
JEL-codes: C32 E32 (search for similar items in EconPapers)
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Working Paper: The predictive content of business survey indicators: evidence from SIGE (2015)
Working Paper: The Predictive Content of Business Survey Indicators: evidence from SIGE (2015)
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