Abstract
The aim of the paper is to decompose two important economic variables (GDP and unemployment rate in the Czech Republic) into a cyclical and a trend component by applying a state space methodology. An unobserved component model is econometrically estimated by the method of maximum likelihood. The likelihood function is constructed using the square root version of the Kalman filter. The results are economically interpreted and it is found that (1) the cyclical component of output and unemployment rate has already recovered from an initial shock at the beginning of the economic crisis in 2008, (2) there has been a persistently decreased growth of the trend component of output after the outbreak of the economic crisis, (3) the trend component of unemployment rate has been constant during the current crisis which suggests that possible hysteresis effects have not played an important role yet, (4) the growth of the GDP trend component is highly volatile in the Czech Republic.
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Notes
- 1.
Specifically, the Matlab function qr was used for this purpose. \( \left[ {{\mathbf{Q}}_{{}} {\mathbf{R}}} \right] = qr\left( {\mathbf{A}} \right) \) calculates an upper triangular matrix \( {\mathbf{R}} \) (with same dimensions as \( {\mathbf{A}} \)) and an orthogonal matrix \( {\mathbf{Q}} \) such that \( {\mathbf{A}} = {\mathbf{Q}} \cdot {\mathbf{R}} \), or \( {\mathbf{R}} = {\mathbf{Q}}^{\prime } \cdot {\mathbf{A}} \).
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Acknowledgements
Financial support of VŠE IGA IG403036 is gratefully acknowledged by the author. Paper was processed with contribution of long term support of scientific work on Faculty of Informatics and Statistics, University of Economics, Prague (IP 400040).
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Čížek, O. (2018). Trend-Cycle Decomposition of Economic Activity in the Czech Republic. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Applied Computational Intelligence and Mathematical Methods. CoMeSySo 2017. Advances in Intelligent Systems and Computing, vol 662. Springer, Cham. https://doi.org/10.1007/978-3-319-67621-0_2
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DOI: https://doi.org/10.1007/978-3-319-67621-0_2
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