Abstract
The purpose of this paper is to assess the main aspects involved in the competitiveness of manufacturing industries in the Euro zone area (EZ-12). To this end, we apply the generalized method of moments to a panel data error correction model. Our sample spans the period from 1970 to 2007, and our findings provide insight into the impact of manufacturing on the international competitiveness of European firms and industries. From the estimated magnitude of the relevant coefficients, we conclude that in the long run, a change in labor and capital compensation is not fully passed on to manufacturing growth, while an increase in the market power of the manufacturing sector will negatively affect its competitiveness.
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Notes
Nace codes 20, 21–22, 24 and 25 respectively (See Appendix Table 6).
HHI is given by \( H=\sum\nolimits_i {{{{\left( {{S_i}} \right)}}^2}} \) where S is the share of firm i in industry sales. The adjusted HHI is defined as \( \mathrm{H}={{{\left( {{{{\mathrm{H}-1}} \left/ {\mathrm{N}} \right.}} \right)}} \left/ {{\left( {{1-1 \left/ {\mathrm{N}} \right.}} \right)}} \right.} \), where N is the number of companies in the industry. The closer this is to 1, the more concentrated the industry.
The producer price index for the EU-15 is taken from the European Central Bank.
The EU-KLEMS project, which was funded by the European Commission (Research Directorate General), aims to create a database on measures of economic growth, productivity, employment creation, capital formation, and technological change at the industry level for all EU member states from 1970 onwards (from 1990 for the recently acceded Member States). The database uses a 63-industry breakdown for the major of the EU’s 25 Member States as well as for the US, Japan, and Canada. For more information visit the website http://www.euklems.net.
\( E{{\left[ {\begin{array}{*{20}c} {{d_{u,3 }}.......{d_{y,i }}} \hfill \\ {.\quad \quad\,.\quad \quad\,.} \hfill \\ {{d_{u,i,T }}\quad\,{d_{y,i,T-2 }}} \hfill \\ \end{array}} \right]}_{mx1 }}=E\left( {Z\prime {u_i}} \right)=E\left( {{\phi_i}} \right)=0,\;{u_i}={\alpha_i}+{\varepsilon_{i,t }} \)
$$ {Z_i}=diag{{\left[ {{d_{y,i,1 }}......{d_{y,s }}} \right]}_{T-2xm }},\;\;\mathrm{s}=1....T-2 $$\( d{u_{i,t }}=\left[ {d{u_{i,3 }}......d{u_{i,T }}} \right]\prime \) and T the periods of cross section observations.
Estimation of \( \mathop{\mu}\limits_{GMM } \) is based on the empirical moments \( \varphi =E\left( {{\varphi_i}} \right)=\left( {\frac{1}{N}} \right)\sum\limits_{i=1}^N {\Pi_i^{\prime }d{u_i}=\frac{1}{N}\varPi \prime du.} \)
N is the number of cross sectional observations.
We have used Eviews 6 in order to perform the econometric analysis. The data are available from the authors upon request.
The J statistic is the most common diagnostic utilized in GMM estimation to evaluate the suitability of the model (Hansen 1982). A rejection of the null hypothesis implies that the instruments are not satisfying the required orthogonality conditions. This may be either because they are not truly exogenous, or because they are being incorrectly excluded from the regression. The J-statistic is distributed as χ2 (p-k), where k is the number of estimated coefficients and p is the instrument rank.
Due to space limitation, the long-run estimation results for the two separated cointegrated equations (see eq.8 and 9) regarding the two sub-periods (1970–1986 and 1987–2007) are omitted, but they are available from the authors upon request.
The main reason for splitting the sample period was not to search for possible structural breaks in the long-run estimated relations, but to investigate the main determinants of the competitiveness of the manufacturing industries in the EZ-12 before and after the enlargement of the European Union (EU-12) with the accession of Portugal and Spain respectively (1986).
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Acknowledgments
An earlier version of this paper was presented at the 73rd International Atlantic Economic Conference which was held in Istanbul, Turkey, 28–31 March 2012. Special acknowledgements should be given to participants of the conference and especially to Professor Nicholas Apergis for his fruitful suggestions. The authors also want to thank the anonymous reviewers for their useful comments. All remaining errors are the authors’ responsibility. Usually disclaimer applies.
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Fafaliou, I., Polemis, M.L. Competitiveness of the Euro Zone Manufacturing: A Panel Data Analysis. Int Adv Econ Res 19, 45–61 (2013). https://doi.org/10.1007/s11294-012-9381-0
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DOI: https://doi.org/10.1007/s11294-012-9381-0