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.
Published in 2017 in: Journal of Business Cycle Research, v.13, 1, pp 75–104.
