Heuristic Model Selection for Leading Indicators in Russia and Germany

MAGKS Papers on Economics 201101

31 Pages Posted: 12 Jul 2012

See all articles by Ivan Savin

Ivan Savin

Ural Federal University; Autonomous University of Barcelona

Peter Winker

University of Giessen - Department of Economics

Date Written: January 27, 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-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.

Keywords: Leading indicators, business cycle forecasts, VAR, model selection, genetic algorithms

JEL Classification: C32, C52, C53, C61, E37

Suggested Citation

Savin, Ivan and Winker, Peter, Heuristic Model Selection for Leading Indicators in Russia and Germany (January 27, 2011). MAGKS Papers on Economics 201101. Available at SSRN: https://ssrn.com/abstract=2104436 or http://dx.doi.org/10.2139/ssrn.2104436

Ivan Savin (Contact Author)

Ural Federal University ( email )

Yekaterinburg
Russia

Autonomous University of Barcelona ( email )

Plaça Cívica
Cerdañola del Valles
Barcelona, Barcelona 08193
Spain

Peter Winker

University of Giessen - Department of Economics ( email )

Licher Str. 62
D-35394 Giessen, DE
Germany

HOME PAGE: http://wiwi.uni-giessen.de/home/oekonometrie/

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