Determinants of trade balance in Polish and Czech manufacturing sectors

Abstract

Research background: A strong industrial base is essential for achieving long-term sustainable economic growth and export competitiveness. In that sense, manufacturing remains a significant contributor to exports in the CEE countries. How-ever, its role and its influence vary between CEE economies and change over time.

Purpose of the article: The main objective of this paper is to compare the determinants of the international competitiveness, measured by the net exports of the manufacturing sectors in the Czech and Polish economies, by using the database of 13 manufacturing sub-sectors in 1995-2011. The authors research the question of how much foreign and domestic demand, the level of labour costs, the level of sector innovation intensity, the level of sector openness to foreign markets as well as sectoral labour productivity influence the changes in trade balance.

Methods: Our approach is based on employing an error correction model and SUR model to disaggregated sectoral manufacturing data.

Findings & Value added: The results of the analysis conducted show substantial differences in the roles particular variables play in explaining the net exports in individual sectors. For the majority of Polish and Czech manufacturing sub-sectors, generation of positive trade balance is determined by relative demand growth. An increasing labour productivity influences heavily a positive trade balance of Polish goods in majority of sub-sectors, however, a key factor in Czech sub-sectors is decreasing unit labour costs. The results of the analysis indicate mostly a greater impact of the researched factors on net exports in long rather than short term and the better capacity of the Czech economy to correct deviations from the equilibrium.

Keywords

CEE economies, trade balance, international competitiveness, manufacturing, error correction model

References

1. Bahmani-Oskooee, M. (1985). Devaluations and the J-curve: some evidence from LDCs. Review of Economics and Statistics, 67(3). doi: 10.2307/1925980. DOI: https://doi.org/10.2307/1925980
   View in Google Scholar
2. Bahmani-Oskooee, M. (1991). Is there a long-run relation between the trade balance and the real effective rate of LDCs. Economics Letters, 36(4). doi: 10.1016/0165-1765(91)90206-Z. DOI: https://doi.org/10.1016/0165-1765(91)90206-Z
   View in Google Scholar
3. Bierut, B. K., & Kuziemska-Pawlak, K. (2017). Competitiveness and export performance of CEE countries. Easter European Economics, 55(6). doi: 10.1080/00128775.2017.1382378. DOI: https://doi.org/10.1080/00128775.2017.1382378
   View in Google Scholar
4. Breitung, J. (2000). The local power of some unit root tests for panel data. In B. Baltagi (Ed.). Nonstationary panels, panel cointegration, and dynamic panels. Advances in econometrics. Amsterdam: JAI.
   View in Google Scholar
5. Bustos, P. (2011). Trade liberalization, exports, and technology upgrading: Evidence on the impact of MERCOSUR on Argentinian firms. American Econom-ic Review, 101(1). doi: 10.1257/aer.101.1.304. DOI: https://doi.org/10.1257/aer.101.1.304
   View in Google Scholar
6. Cieślik, A., Michałek, J. J., & Tovias, A. (2017). The determinants of export performance of firms in selected MENA countries: comparison with CEE countries, Israel and Turkey. Central European Economic Journal, 2(49). doi: 10.1515/ceej-2017-0009. DOI: https://doi.org/10.1515/ceej-2017-0009
   View in Google Scholar
7. Cieślik, A., & Michałek, J.J. (2018). Firm-level determinants of direct and indirect exports: empirical evidence for C.E.E. and M.E.N.A. countries. Economic Research-Ekonomska Istraživanja, 31(1). doi: 10.1080/1331677X.2018. 1436452. DOI: https://doi.org/10.1080/1331677X.2018.1436452
   View in Google Scholar
8. Deardorff, A. V. (1984). Testing trade theories and predicting trade flows. In R. W. Jones & P. B. Kenen (Eds.). Handbook of international economics. Amsterdam: North-Holland. DOI: https://doi.org/10.1016/S1573-4404(84)01013-3
   View in Google Scholar
9. Dixit, A. K., & Stiglitz, J. E. (1977). Monopolistic competition and optimum product diversity. American Economic Review, 67(3).
   View in Google Scholar
10. EC (2017). European innovation scoreboard 2017. European Commission.
    View in Google Scholar
11. Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica, 55(2). doi: 10.2307/1913 236. DOI: https://doi.org/10.2307/1913236
    View in Google Scholar
12. Goldberg, I., Branstetter, L., Goddard, J. G., & Kuriakose, S. (2008). Globalization and technology absorption in Europe and Central Asia: the role of trade, FDI, and cross-border knowledge flows. World Bank Working Paper, 150. DOI: https://doi.org/10.1596/978-0-8213-7583-9
    View in Google Scholar
13. Golik, M., Grela, M., Humanicki, M., Kitala, M., Michałek, T., Mroczek, W., Mućk, J., & Rzeszutek, E. (2014). Analysis of the economic situation in the countries of Central and Eastern Europe. Narodowy Bank Polski Working Papers,1/14.
    View in Google Scholar
14. Guarascio, D., Pianta, M., & Bogliacino, F. (2016). Export, R&D and new products. a model and a test on European industries. Journal of Evolutionary Economics, 26(4). doi: 10.1007/s00191-016-0445-9. DOI: https://doi.org/10.1007/s00191-016-0445-9
    View in Google Scholar
15. Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1). doi: 10.1016/S0304-4076(03)00092-7. DOI: https://doi.org/10.1016/S0304-4076(03)00092-7
    View in Google Scholar
16. Kao, C., & Chiang, M. (2000). On the estimation and inference of a cointegrated regression in panel data. In B. Baltagi (Ed.). Nonstationary panels, panel cointegration, and dynamic panels. Advances in econometrics. Amsterdam: JAI.
    View in Google Scholar
17. Karo, E., & Kattel, R. (2015). Economic development and evolving state capacities in Central and Eastern Europe: can “smart specialization” make a difference?. Journal of Economic Policy Reform, 18(2). doi: 10.1080/17487870.2015. 1009068. DOI: https://doi.org/10.1080/17487870.2015.1009068
    View in Google Scholar
18. Lewney, R. (2011). Study on the cost competitiveness of European industry in the globalization era – empirical evidence on the basis of relative unit labour cost at sectoral level. Ecorys Nederland BV.
    View in Google Scholar
19. Mark, N. C., Ogaki, M., & Sul, D. (2005). Dynamic seemingly unrelated cointegrating regressions. Review of Economic Studies, 72(3). doi: 10.1016/S0304-4076(03)00092-7. DOI: https://doi.org/10.1111/j.1467-937X.2005.00352.x
    View in Google Scholar
20. Melitz, M. J. (2003). The impact of trade on intra-industry reallocations and aggregate industry productivity. Econometrica, 71(6). doi: 10.1111/1468-0262. 00467. DOI: https://doi.org/10.1111/1468-0262.00467
    View in Google Scholar
21. Melitz, M. J., & Ottaviano, G. I. P. (2008). Market size, trade and productivity. Review of Economic Studies, 75(1). doi: 10.1111/j.1467-937X .2007.00463.x. DOI: https://doi.org/10.1111/j.1467-937X.2007.00463.x
    View in Google Scholar
22. Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics, 61(4). doi: 10.1111/1468-0084.61.s1.14. DOI: https://doi.org/10.1111/1468-0084.0610s1653
    View in Google Scholar
23. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross section dependence. Journal of Applied Econometrics, 22(2). doi: 10.1002/jae.951. DOI: https://doi.org/10.1002/jae.951
    View in Google Scholar
24. Porter, M. E. (1990). The competitive advantage of nations. New York: Macmillan Press. DOI: https://doi.org/10.1007/978-1-349-11336-1
    View in Google Scholar
25. Rivera-Batiz, L. A., & Romer, P. M. (1991). International trade with endogenous technological change. European Economic Review, 35(4). doi: 10.1016/0014-2921(91)90048-N. DOI: https://doi.org/10.1016/0014-2921(91)90048-N
    View in Google Scholar
26. Rivera Leon, L., Miedzinski, M., & Reid, A. (2011). Cohesion policy and regional research and innovation potential: an analysis of the effects of structural funds support for research, technological development and innovation 2000–2010. Studies and reports, EUR 24199, European Commission.
    View in Google Scholar
27. Sharma, K. (2003). Factors determining India's export performance. Journal of Asia Economics, 14(3). doi: 10.1016/S1049-0078(03)00036-8. DOI: https://doi.org/10.1016/S1049-0078(03)00036-8
    View in Google Scholar
28. Timmer, M. P., Dietzenbacher, E., Los, B., Stehrer, R., & de Vries, G. J. (2015). An illustrated user guide to the world input–output database: the case of global automotive production. Review of International Economics, 23. doi: 10.1111/roie.12178. DOI: https://doi.org/10.1111/roie.12178
    View in Google Scholar
29. Turner, A. G., & Golub, S. S. (1997). Towards a system of multilateral unit labor cost-based competitiveness indicators for advanced, developing and transition countries. IMF Working Paper, 97/151. DOI: https://doi.org/10.5089/9781451922882.001
    View in Google Scholar
30. Vernon, R. (1966). International investment and international trade in the product cycle. Quarterly Journal of Economics, 80(2). doi: 10.2307/1880689. DOI: https://doi.org/10.2307/1880689
    View in Google Scholar
31. Vrh, N. (2018). What drives the differences in domestic value added in exports between old and new E.U. member states? Economic Research-Ekonomska Istraživanja, 31(1). doi: 10.1080/1331677X.2018. 1438910. DOI: https://doi.org/10.1080/1331677X.2018.1438910
    View in Google Scholar
32. Wagner, J. (2008). Export entry, export exit and productivity in German manufacturing industries. International Journal of the Economics of Business, 15(2). doi: 10.1080/13571510802134270. DOI: https://doi.org/10.1080/13571510802134270
    View in Google Scholar
33. Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics, 69(6). doi: 10.1111/j.1468-0084. 2007.00477.x. DOI: https://doi.org/10.1111/j.1468-0084.2007.00477.x
    View in Google Scholar
34. Young, A. (1991). Learning by doing and the dynamic effects of international trade. Quarterly Journal of Economics, 106(2). doi: 10.2307/2937942. DOI: https://doi.org/10.2307/2937942
    View in Google Scholar