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Variable-ordering induced problems of impulse-response analysis and other difficulties: the dividend policy of Austrian firms

Variable-ordering induced problems of impulse-response analysis and other difficulties: the... Orthogonalised impulses are the standard way to isolate shocks to variables in a vector error correction model. While using the Cholesky decomposition to adjust interdependencies of the shocks, the ordering of the variables on the stage of estimation has a great impact on the resulting impulse response functions. It is shown how the variable ordering affects the empirical evaluation of the dividend policy of Austrian firms examining corporate earnings, dividends and inflation. Additional problems are discussed (e.g., bootstrapped confidence intervals and seasonal adjustment procedures, missing variables). The paper has two messages: it is a fatal flaw of any economic model to omit important variables. Moreover, it is also of major importance to use appropriate econometric modelling techniques. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Computational Economics and Econometrics Inderscience Publishers

Variable-ordering induced problems of impulse-response analysis and other difficulties: the dividend policy of Austrian firms

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References (20)

Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1757-1170
eISSN
1757-1189
DOI
10.1504/IJCEE.2010.037938
Publisher site
See Article on Publisher Site

Abstract

Orthogonalised impulses are the standard way to isolate shocks to variables in a vector error correction model. While using the Cholesky decomposition to adjust interdependencies of the shocks, the ordering of the variables on the stage of estimation has a great impact on the resulting impulse response functions. It is shown how the variable ordering affects the empirical evaluation of the dividend policy of Austrian firms examining corporate earnings, dividends and inflation. Additional problems are discussed (e.g., bootstrapped confidence intervals and seasonal adjustment procedures, missing variables). The paper has two messages: it is a fatal flaw of any economic model to omit important variables. Moreover, it is also of major importance to use appropriate econometric modelling techniques.

Journal

International Journal of Computational Economics and EconometricsInderscience Publishers

Published: Jan 1, 2010

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