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Forecasting GDP at the Regional Level with Many Predictors

Robert Lehmann () and Klaus Wohlrabe ()

German Economic Review, 2015, vol. 16, issue 2, 226-254

Abstract: type="main" xml:id="geer12042-abs-0001"> In this study, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden-Württemberg) and Eastern Germany. We overcome the problem of a ‘data-poor environment’ at the sub-national level by complementing various regional indicators with more than 200 national and international indicators. We calculate single-indicator, multi-indicator, pooled and factor forecasts in a ‘pseudo-real-time’ setting. Our results show that we can significantly increase forecast accuracy compared with an autoregressive benchmark model, both for short- and long-term predictions. Furthermore, regional indicators play a crucial role for forecasting regional GDP.

Date: 2015
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Related works:
Working Paper: Forecasting GDP at the regional level with many predictors (2013) Downloads
Working Paper: Forecasting GDP at the regional level with many predictors (2013) Downloads
Working Paper: Forecasting GDP at the Regional Level with Many Predictors (2012) Downloads
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German Economic Review is currently edited by Bernhard Felderer, Joseph F. Francois, Ivo Welch, Urs Schweizer and David E. Wildasin

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