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Heuristic model selection for leading indicators in Russia and Germany

  • Ivan Savin


    (Justus Liebig University Giessen)

  • Peter Winker


    (Justus Liebig University Giessen)

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–specified VAR models with subset models obtained using a Genetic Algorithm enabling ’holes’ 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.

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Paper provided by Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung) in its series MAGKS Papers on Economics with number 201101.

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Length: 30 pages
Date of creation: 2011
Date of revision:
Publication status: Forthcoming in
Handle: RePEc:mar:magkse:201101
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