The Predictive Content of Business Survey Indicators: evidence from SIGE

Tatiana Cesaroni and Stefano Iezzi

No 15118, Working Papers LuissLab from Dipartimento di Economia e Finanza, LUISS Guido Carli

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.

Keywords: Business cycle; Business survey data; Turning points; cyclical analysis; Forecast accuracy; Macroeconomic forecasts (search for similar items in EconPapers)
JEL-codes: C32 E32 (search for similar items in EconPapers)
Date: 2015
New Economics Papers: this item is included in nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Journal Article: The Predictive Content of Business Survey Indicators: Evidence from SIGE (2017)
Working Paper: The predictive content of business survey indicators: evidence from SIGE (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:lui:lleewp:15118

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