© Iwona Skrodzka. Article available under the CC BY-SA 4.0 licence
ARTICLE
ABSTRACT
The purpose of the paper is to empirically determine the impact of human capital on the innovation performance of EU economies. Currently, most researchers consider human capital a significant factor of economic growth based on knowledge and innovation. Depending on the amount and quality of the available resources, human capital can play various parts in an economy, e.g. that of a user of existing knowledge and technology (general human capital), an implementer of new solutions, or a creator of previously undiscovered knowledge (specialised human capital). However, there is a gap in the literature regarding empirical research into the influence of human capital on the innovativeness of economies. This is related to the difficulties associated with the measurement of the two categories, as well as the limited number of methods to study the relationships between unobservable variables. The research described in the paper fills this gap. In order to study the relationship between human capital (general and specialised) and the innovation performance of economies, the partial least squares structural equation modelling (PLS-SEM) was used. The research spanned the years 2014-2020. Four PLS-SEM models were estimated based on cross-sectional data for the EU economies. The results showed that human capital significantly boosts the innovation performance of EU economies. Both general human capital and specific human capital had a significant positive impact on the innovation performance of these countries in the analysed years. The results can have a practical application and serve as an instrument of innovation policies or as a tool helpful in creating conditions for innovation systems.
KEYWORDS
human capital, innovativeness, innovation performance, structural equation modeling, PLS-SEM.
REFERENCES
Aghion, P., Howitt, P., (1992). A model of growth through creative destruction. Econometrica, 60(2), pp. 323–351. doi: 10.2307/2951599.
Aleknavičiute, R., Skvarciany, V. and Survilaite, S., (2016). The role of human capital for national innovation capability in EU countries. Economics and Culture, 13(1), pp. 114–125. doi: 10.1515/jec-2016-0014.
Ang, J. B., Madsen, J. B. and Rabiul Islam, Md., (2011). The effects of human capital composition on technological convergence. Journal of Macroeconomics, 33(3), pp. 465–476. doi: 10.1016/j.jmacro.2011.03.001.
Azariadis, C., Drazen, A., (1990). Threshold externalities in economic development. The Quarterly Journal of Economics, 105(2), pp. 501–526. doi: 10.2307/2937797.
Balcerzak, A. P., Pietrzak, M. B., (2016). Structural equation modeling in evaluation of technological potential of European Union Countries in the years 2008–2012. In M. Papież and S. Śmiech (Eds.). The 10th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena. Conference Proceedings (pp. 9–18). Cracow: Foundation of the Cracow University of Economics.
Barro, Robert, J., (2001). Human capital and growth. The American Economic Review, 91(2), pp. 12–17, doi: 10.1257/aer.91.2.12.
Benhabib, J., Spiegel, M. M., (1994). The role of human capital in economic development evidence from aggregate cross-country data. Journal of Monetary Economics, 34(2), pp. 143–173. doi: 10.1016/0304-3932(94)90047-7.
Benhabib, J., Spiegel, M. M., (2005). Human capital and technology diffusion. In P. Aghion and S. Durlauf (Eds.). Handbook of economic growth (pp. 935–966). Elsevier. doi: 10.1016/S1574-0684(05)01013-0.
Chin, W. W., (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.). Modern methods for business research (pp. 295–336). Mahwah: Lawrence Erlbaum.
Dakhli, M., Clercq, D. D., (2004). Human capital, social capital, and innovation: a multi-country study. Entrepreneurship & Regional Development, 16(2), pp. 107–128. doi: 10.1080/08985620410001677835.
Danquah, M., Ouattara, B., (2014). Productivity growth, human capital and distance to frontier in Sub-Saharan Africa. Journal of Economic Development. pp. 39(4), pp. 27–48.
Grossman, G., Helpman, E., (1991). Trade, knowledge spillovers, and growth. European Economic Review, 35(2-3), pp. 517–526. doi: 10.1016/0014-2921(91)90153-A.
Hair, J. F., Hult, G. T. M., Ringle, C. M. and Sarstedt, M., (2022). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks, CA: Sage.
Hair, J. F., Sarstedt, M., Ringle, C. M. and Gudergan, S. P., (2018). Advanced Issues in Partial Least Squares Structural Equation Modeling. Thousand Oaks, CA: Sage.
Kaasa, A., Parts, E. and Kaldaru, H., (2012). The role of human and social capital for innovation in catching-up economies. In E. G. Carayannis, U. Varblane and T. Roolaht (Eds.). Innovation systems in small catching-up economies (pp. 259– 276). Berlin, Heidelberg: Springer. doi: 10.1007/978-1-4614-1548-0_14.
Jones, C. I., (2003). Human capital, ideas, and economic growth. In L. Paganetto and E. S. Phelps (Eds.). Finance, research, education and growth (pp. 51–74). London: Palgrave Macmillan. doi: 10.1057/9781403920232_4.
Mankiw, N.G., Weil, D. and Romer, D., (1992). A contribution to the empirics of economic growth. The Quarterly Journal of Economics, 107, pp. 407–437. doi: 10.2307/2118477.
Nelson, R. R., Phelps, E. S., (1966). Investment in humans, technological diffusion, and economic growth. The American Economic Review, 56(1/2), pp. 69–75.
OECD, (1998). Human capital investment: an international comparison. Paris: OECD Publishing. doi: 10.1787/9789264162891-en.
Rogowski, J., (1990). Soft models. Theory and application in economic research. Białystok: Wydawnictwo Filii UW w Białymstoku.
Romer, P. M., (1990). Endogenous technological change. Journal of Political Economics, 98(5), pp. S71–S102.
Sarstedt, M., Hair, J. F., Cheah, J.-H., Becker, J.-M. and Ringle, C. M., (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian Marketing Journal, 27(3), pp. 197–211. doi: 10.1016/j.ausmj.2019.05.003.
Skrodzka, I., (2021). Human capital and the innovative performance of Central and Eastern European countries - PLS-SEM modelling. Warszawa: CeDeWu.
Vandenbussche, J., Aghion, P. and Meghir, C., (2006). Growth, distance to frontier and composition of human capital. Journal of Economic Growth, 11(2), pp. 97–127. doi: 10.1007/s10887-006-9002-y.
Weresa, M. A., (2014). Innovation policy. Warszawa: PWN.
Wetzels, M., Odekerken-Schröder, G. and van Oppen, C., (2009). Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical illustration. MIS Quarterly, 33(1), pp. 177–195. doi: 10.2307/20650284.
Wold, H., (1980). Soft modelling: Intermediate between traditional model building and data analysis. Banach Center Publications, 6(1), pp. 333–346.