Technology, employment and the business cycle in post-transition countries of the EU

Abstract

This article analyses the importance of technology and non-technology shocks in the business cycles of European Union post-transition countries. Different assumptions of New Keynesian and Real Business Cycle theory are tested. The results demonstrate that a non-technology shock is more important in explaining business cycles in post-transition countries, although a technology shock is not trivial. The technology shock cannot replicate basic business cycle facts observed in the data: it produces a low or negative correlation between employment and GDP, and a strong negative correlation between labour productivity and employment. Technology and non-technology GDP components are analysed in the transition and post-transition period. The results show a non-technology shock was the dominant source of business cycles both during and after the transition period.

Keywords:

• Business cycles
• post-transition countries
• New-Keynesian theory
• technology shocks
• nominal rigidities
• SVAR model

Acknowledgements

This article is based on the author’s PhD thesis named ‘Technology Shocks and Nominal Rigidities as a Source of Business Cycles in Post-Transition Countries of the EU’ defended in February 2015 at the Faculty of Economics and Business, University of Zagreb. I would like to thank Radmila Jovančević, Josip Tica, Maruška Vizek, Ivo Družić and Robert J. Sonora for helpful discussion on the topic. Also, I gratefully acknowledge very helpful comments and suggestions from the editor and an anonymous referee.

Notes

1. For a detailed literature review, refer to Galí and Rabanal (2004).

2. In order to estimate the augmented model, restrictions are set as a lower triangular matrix.

3. Complete results of variance decomposition are available from the author upon request. See also Table 4 for complete results of the augmented model.

4. These results do not hold in the augmented SVAR model, where the technology shock is less important in explaining variations of employment (20–45% at the eight quarter horizon).

5. Confidence intervals are obtained by Monte Carlo simulation with 1000 replications, and represent one standard deviation band.

6. The original data start with 1995:Q1, but the benchmark SVAR model is estimated with four lags. The results of the augmented model are not presented, because it does not cover the transition period. In the augmented model the sample starts at best with 1997:Q1, because the inflation series is shorter. In Croatia for instance it starts with 1999:Q1, which is the end of the transition period.