Governments and central banks need to have an accurate and timely assessment of Gross Domestic Product's (GDP) growth rate for the current quarter, as this is essential for providing a reliable and early analysis of the current economic situation. This paper presents a series of models conceived to forecast the current German GDP's quarterly growth rate. These models are designed to be used on a monthly basis by integrating monthly economic information through bridge models, thus allowing for the economic interpretation of the data. We do also forecast German GDP by dynamic factor models. The combination of these two approaches allows selecting economically relevant explanatory variables among a large data set of hard and soft data. In addition, a rolling forecast study is carried out to assess the forecasting performance of the estimated models. To this end, publication lags are taken into account in order to run pseudo out-of-sample forecasts. We show that it is possible to get reasonably good estimates of current quarterly GDP growth in anticipation of the official release, especially from bridge models.
Pamfili Antipa, Karim Barhoumi, Véronique Brunhes-Lesage and Olivier Darné - To be published in "The Journal of Policy Modeling"
Classification JEL : C52, C53, E20.
Keywords : GDP forecasting; Bridge models; Factor models.Threshold auto-regression, bounce-back effects, business cycles, inventory investment.
Updated on: 06/12/2018 11:09