Management

Forecasting is a tool used in business and industry to predict the future behaviour of customers. One of the most popular statistical models of forecasting is the so-called damped trend model.

Giacomo Sbrana (NEOMA Business School) and Andrea Silvestrini (Bank of Italy) use a real macroeconomic data set with 270 one-time series and covering almost 50 economies, to propose an approach that might outperform the standard one. A simple, rigorous and easy to use tool that can help the practice of predicting future data.

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Forecasting with the damped trend model using the structural approach, Giacomo Sbrana, Andrea Silvestrini. International Journal of Production Economics, Volume 226, August 2020, 107654.

4 October 2021
Sbrana Giacomo

THE AUTHOR

Sbrana Giacomo

Professor NEOMA BS

Giacomo SBRANA is Full professor at NEOMA Business School since 2019. He joined the school as assistant professor in August 2011 and became Associate professor in 2014. Before joining NEOMA, from 2005 until 2009, he worked as associate expert at the Department of Economic and Social Affairs of the United Nations in New York (USA). Giacomo holds a M.Sc. in Economics and Econometrics from the University of Southampton (obtained in 2003), a PhD in Statistics from the University of Roma TRE (obtained in 2004) and a postdoc at BETA, Université de Strasbourg (from 2009 until 2011). He teaches several courses in quantitative methods and programming with R both at undergraduate (PGE program) and postgraduate level (MSc and PhD). His primary research interests include time series analysis and forecasting especially using State-Space models and the Kalman filter. He has published in several academic journals such as: International Journal of Production Economics, Journal of Banking & Finance, International Journal of Forecasting, Macroeconomic Dynamics, Cliometrica, Journal of the Operational Research Society, Economic Modelling, Journal of Time Series Analysis, Journal of Forecasting, Journal of Multivariate Analysis, Bulletin of Economic Research.