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Title:Heuristic model selection for leading indicators in Russia and Germany PDF Logo
Authors:Savin, Ivan
Winker, Peter
Issue Date:2011
Series/Report no.:Joint discussion paper series in economics 01-2011
Abstract:Business tendency survey indicators are widely recognized as a key instrument for business cycle forecasting. Their leading indicator property is assessed with regard to forecasting industrial production in Russia and Germany. For this purpose, vector autoregressive (VAR) models are specified and estimated to construct forecasts. As the potential number of lags included is large, we compare full's specified VAR models with subset models obtained using a Genetic Algorithm enabling in multivariate lag structures. The problem is complicated by the fact that a structural break and seasonal variation of indicators have to be taken into account. The models allow for a comparison of the dynamic adjustment and the forecasting performance of the leading indicators for both countries revealing marked differences between Russia and Germany.
Subjects:leading indicators
business cycle forecasts
VAR
model selection
genetic algorithms
JEL:C32
C52
C53
C61
E37
Document Type:Working Paper
Appears in Collections:MAGKS Joint Discussion Paper Series in Economics, Universität Marburg

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