Exploring efficiency growth of advanced technology-generating sectors in the European Union: a stochastic frontier analysis
Abstract
This study investigates the efficiency growth of advanced technology-generating sectors within the European Union (EU). Using a stochastic frontier analysis of annual sector-level panel data from 2000 to 2019, we examine sectoral (NACE two-digit level) and territorial implications. Our findings indicate that technological change was more intense in advanced technology-generating sectors than in other economic sectors, primarily driven by fixed capital investments. However, the impact of in-house research and development varied. Economic sectors such as pharmaceuticals and motor vehicles struggled to improve their production efficiency due to high competition and market specificity. A comparative analysis of EU economies showed a lower level of production efficiency in catching-up economies. Nevertheless, these economies contributed to the shift of the production possibility frontier in certain sectors on the EU level. Therefore, this study contributes to the ongoing scientific discussion on technological innovations in diverse territories, suggesting that less-developed economies could generate technological advancements in specific areas. We also discuss the implications for innovation and industrial policy actions.
First published online 09 January 2024
Keyword : production efficiency, economic sectors, advanced technologies, technological progress, technical efficiency, stochastic frontier analysis, R&D, smart specialization
How to Cite
Dzemydaitė, G., & Naruševičius, L. (2023). Exploring efficiency growth of advanced technology-generating sectors in the European Union: a stochastic frontier analysis. Journal of Business Economics and Management, 24(6), 976–995. https://doi.org/10.3846/jbem.2023.20688
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Fu, X., & Yang, Q. G., (2009). Exploring the cross-country gap in patenting: A stochastic frontier approach. Research Policy, 38(7), 1203–1213. https://doi.org/10.1016/j.respol.2009.05.005
Ghobakhloo, M., & Ching, N. T. (2019). Adoption of digital technologies of smart manufacturing in SMEs. Journal of Industrial Information Integration, 16, Article 100107. https://doi.org/10.1016/j.jii.2019.100107
Griliches, Z. (1979). Issues in assessing the contribution of R&D to productivity growth. The Bell Journal of Economics, 10(1), 92–116. https://doi.org/10.2307/3003321
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Haschka, R. E., & Herwartz, H. (2020). Innovation efficiency in European high-tech industries: Evidence from a Bayesian stochastic frontier approach. Research Policy, 49(8), Article 104054. https://doi.org/10.1016/j.respol.2020.104054
König, M. D., Lorenz, J., & Zilibotti, F. (2016). Innovation vs. imitation and the evolution of productivity distributions. Theoretical Economics, 11(3), 1053–1102. https://doi.org/10.3982/TE1437
Krammer, M. S. (2017). Science, technology, and innovation for economic competitiveness: The role of smart specialization in less-developed countries. Technological Forecasting and Social Change, 123, 95–107. https://doi.org/10.1016/j.techfore.2017.06.028
Kumbhakar, S. C., Ortega-Argilés, R., Potters, L., Vivarelli, M., & Voigt, P. (2012). Corporate R&D and firm efficiency: Evidence from Europe’s top R&D investors. Journal of Productivity Analysis, 37, 125–140. https://doi.org/10.1007/s11123-011-0223-5
Li, H., He, H., Shan, J., & Cai, J. (2019). Innovation efficiency of semiconductor industry in China: A new framework based on generalized three-stage DEA analysis. Socio-Economic Planning Sciences, 66, 136–148. https://doi.org/10.1016/j.seps.2018.07.007
Liik, M., Masso, J., & Ukrainski, K. (2014). The contribution of R&D to production efficiency in OECD countries: Econometric analysis of industry-level panel data. Baltic Journal of Economics, 14(1–2), 78–100. https://doi.org/10.1080/1406099X.2014.981105
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Novotná, M., Volek, T., Rost, M., & Vrchota, J. (2021). Impact of technology investment on firm’s production efficiency factor in manufacturing. Journal of Business Economics and Management, 22(1), 135–155. https://doi.org/10.3846/jbem.2020.13635
OECD. (2022). Investment (GFCF) (indicator). https://doi.org/10.1787/b6793677-en
Overbeek, H. (2012). Sovereign debt crisis in Euroland: Root causes and implications for European integration. The International Spectator, 47(1), 30–48. https://doi.org/10.1080/03932729.2012.655006
Piesse, J., & Thirtle, C. (2000). A stochastic frontier approach to firm level efficiency, technological change, and productivity during the early transition in Hungary. Journal of Comparative Economics, 28(3), 473–501. https://doi.org/10.1006/jcec.2000.1672
Sanchez, M. (2021). What drives euro area labour productivity growth? An international production-frontier examination. In P. C. Kostis (Ed.), Bridging microeconomics and macroeconomics and the effects on economic development and growth (pp. 231–258). IGI Global. https://doi.org/10.4018/978-1-7998-4933-9.ch012
Schaffer, A., Simar, L., & Rauland, J. (2011). Decomposing regional efficiency. Journal of Regional Science, 51(5), 931–947. https://doi.org/10.1111/j.1467-9787.2011.00731.x
Schwab, K. (2017). The fourth industrial revolution. Currency.
Severgnini, H. B. (2009). Essays in total factor productivity measurement [Dissertation]. Retrieved August 23, 2021, from https://d-nb.info/1010221167/34
Sickles, R., & Zelenyuk, V. (2019). Measurement of productivity and efficiency: Theory and practice. Cambridge University Press. https://doi.org/10.1017/9781139565981
Stead, A. D., Wheat, P., & Greene, W. H. (2023). Robustness in stochastic frontier analysis. In P. Macedo, V. Moutinho, & M. Madaleno (Eds.), Lecture notes in economics and mathematical systems: Vol. 692. Advanced mathematical methods for economic efficiency analysis (pp. 197–228). Springer, Cham. https://doi.org/10.1007/978-3-031-29583-6_12
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Teirlinck, P., & Khoshnevis, P. (2022). SME efficiency in transforming regional business research and innovation investments into innovative sales output. Regional Studies, 56(12), 2147–2163. https://doi.org/10.1080/00343404.2022.2046263
Toufaily, E., Zalan, T., & Dhaou, S. B. (2021). A framework of blockchain technology adoption: An investigation of challenges and expected value. Information & Management, 58(3), Article 103444. https://doi.org/10.1016/j.im.2021.103444
Yang, L., & Wang, S. (2022). Do fintech applications promote regional innovation efficiency? Empirical evidence from China. Socio-Economic Planning Sciences, 83, Article 101258. https://doi.org/10.1016/j.seps.2022.101258
Battese, G. E., & Coelli, T. J. (1992). Frontier production functions, technical efficiency and panel data: With application to paddy farmers in India. Journal of Productivity Analysis, 3(1/2), 153–169. https://doi.org/10.1007/BF00158774
Bender, M., Henke, N., & Lamarre, E. (2018). The cornerstones of large-scale technology transformation. McKinsey Quarterly. Retrieved August 29, 2021, from https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/the-cornerstones-of-large-scale-technology-transformation
Bresnahan, T. F., & Trajtenberg, M. (1995). General purpose technologies “Engines of growth”? Journal of Econometrics, 65(1), 83–108. https://doi.org/10.1016/0304-4076(94)01598-T
Burger, M. J., Kounetas, K., Napolitano, O., & Stavropoulos, S. (2022). Do innovation and human capital actually narrow the technology gap? Champions and laggards of European regional productive performance. Regional Studies, 556(10), 1655–1700. https://doi.org/10.1080/00343404.2021.2000596
Capello, R., & Lenzi, C. (2021). Industry 4.0 and servitisation: Regional patterns of 4.0 technological transformations in Europe. Technological Forecasting and Social Change, 173, Article 121164. https://doi.org/10.1016/j.techfore.2021.121164
Coelli, T. J., Rao, D. S. P., O’Donnell, C. J., & Battese, G. E. (2005). An introduction to efficiency and productivity analysis (2nd ed.). Springer. https://doi.org/10.1007/b136381
Crowley, F., & McCann, P. (2018). Firm innovation and productivity in Europe: Evidence from innovation-driven and transition-driven economies. Applied Economics, 50(11), 1203–1221. https://doi.org/10.1080/00036846.2017.1355543
Culot, G., Nassimbeni, G., Orzes, G., & Sartor, M. (2020). Behind the definition of Industry 4.0: Analysis and open questions. International Journal of Production Economics, 226, Article 107617. https://doi.org/10.1016/j.ijpe.2020.107617
Dzemydaitė, G. (2021). The impact of economic specialization on regional economic development in the European Union: Insights for formation of smart specialization strategy. Economies, 9(2), Article 76. https://doi.org/10.3390/economies9020076
Dzemydaitė, G., Dzemyda, I., & Galinienė, B. (2016). The efficiency of regional innovation systems in new member states of the European Union: A nonparametric DEA approach. Economics and Business, 28(1), 83–89. https://doi.org/10.1515/eb-2016-0012
Dzemydienė, D., Dzemydaitė, G., & Gopisetti, D. (2022). Application of multicriteria decision aid for evaluation of ICT usage in business. Central European Journal of Operational Research, 30, 323–343. https://doi.org/10.1007/s10100-020-00691-9
Esteve, M., Aparicio, J., Rabasa, A., & Rodriguez-Sala, J. J. (2020). Efficiency analysis trees: A new methodology for estimating production frontiers through decision trees. Expert Systems with Applications, 162, Article 113783. https://doi.org/10.1016/j.eswa.2020.113783
European Commission. (2009a). Economic crisis in Europe: Causes, consequences and responses. European Economy 7|2009. Retrieved August 10, 2021, from https://ec.europa.eu/economy_finance/publications/pages/publication15887_en.pdf
European Commission. (2009b). Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions – “Preparing for our future: Developing a common strategy for key enabling technologies in the EU” {SEC(2009) 1257}. COM/2009/0512 final. Brussels.
European Commission. (2015). Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. A digital single market strategy for Europe. COM(2015) 192 final. Brussels.
European Commission. Executive Agency for Small and Medium-sized Enterprises. Heimberger, H., Horvat, D., Kroll, H., Izsak, K., & Shauchuk, P. (2020a). Advanced technologies for industry – Sectoral watch. Technological trends in the automotive industry. Publications Office of the European Union. https://data.europa.eu/doi/10.2826/13579
European Commission. Executive Agency for Small and Medium-sized Enterprises. (2020b). Skills and talent are key to enabling digital and technological transformation and safeguarding the competitiveness of European industry – Policy brief on Meeting the sectoral skills challenge in advanced technologies. Publications Office. https://data.europa.eu/doi/10.2826/30242
European Commission. (2020c). The advanced technologies for industry – ATI dashboard. Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs. Updated: 31.01.2021. Retrieved September 10, 2022, from https://data.europa.eu/data/datasets/advanced-technologies-for-industry-ati?locale=en
European Commission. (2021). Executive Agency for Small and Medium-sized Enterprises by Izsak, K., Kroll, H., Wydra, S., et al. (2021). Advanced technologies for industry – Methodological report. Indicator framework and data calculations. Publications Office of the European Union. https://data.europa.eu/doi/10.2826/911991
European Commission. Joint Research Centre, by Grassano, N., Hernandez Guevara, H., Tübke, A., et al. (2022). The 2021 EU industrial R&D investment scoreboard. Publications Office of the European Union. https://data.europa.eu/doi/10.2760/559391
European Commission. (2023). S3 CoP Observatory. https://ec.europa.eu/regional_policy/assets/s3-observatory/index_en.html
European Communities. (2009). System of National Accounts 2008. International Monetary Fund. Organisation for Economic Co-operation and Development. United Nations & World Bank. Printed at the United Nations.
European Federation of Pharmaceutical Industries and Associations. (2019). The pharmaceutical industry in figures. Key data. 2019. EFPIA. Retrieved July 20, 2022, from https://www.efpia.eu/media/413006/the-pharmaceutical-industry-in-figures.pdf
Foray, D. (2018). Smart specialisation strategies and industrial modernisation in European regions – theory and practice. Cambridge Journal of Economics, 42(6), 1505–1520. https://doi.org/10.1093/cje/bey022
Fu, X., & Yang, Q. G., (2009). Exploring the cross-country gap in patenting: A stochastic frontier approach. Research Policy, 38(7), 1203–1213. https://doi.org/10.1016/j.respol.2009.05.005
Ghobakhloo, M., & Ching, N. T. (2019). Adoption of digital technologies of smart manufacturing in SMEs. Journal of Industrial Information Integration, 16, Article 100107. https://doi.org/10.1016/j.jii.2019.100107
Griliches, Z. (1979). Issues in assessing the contribution of R&D to productivity growth. The Bell Journal of Economics, 10(1), 92–116. https://doi.org/10.2307/3003321
Hall, B. H., Mairesse, J., & Mohnen, P. (2010). Measuring the returns to R&D. In B. H. Hall & N. Rosenberg (Eds.), Handbook of the economics of innovation (vol. 2, pp. 1033–1082). Elsevier. https://doi.org/10.1016/S0169-7218(10)02008-3
Hartmann, D., Zagato, L., Gala, P., & Pinheiro, F. L. (2021). Why did some countries catch-up, while others got stuck in the middle? Stages of productive sophistication and smart industrial policies. Structural Change and Economic Dynamics, 58, 1–13. https://doi.org/10.1016/j.strueco.2021.04.007
Haschka, R. E., & Herwartz, H. (2020). Innovation efficiency in European high-tech industries: Evidence from a Bayesian stochastic frontier approach. Research Policy, 49(8), Article 104054. https://doi.org/10.1016/j.respol.2020.104054
König, M. D., Lorenz, J., & Zilibotti, F. (2016). Innovation vs. imitation and the evolution of productivity distributions. Theoretical Economics, 11(3), 1053–1102. https://doi.org/10.3982/TE1437
Krammer, M. S. (2017). Science, technology, and innovation for economic competitiveness: The role of smart specialization in less-developed countries. Technological Forecasting and Social Change, 123, 95–107. https://doi.org/10.1016/j.techfore.2017.06.028
Kumbhakar, S. C., Ortega-Argilés, R., Potters, L., Vivarelli, M., & Voigt, P. (2012). Corporate R&D and firm efficiency: Evidence from Europe’s top R&D investors. Journal of Productivity Analysis, 37, 125–140. https://doi.org/10.1007/s11123-011-0223-5
Li, H., He, H., Shan, J., & Cai, J. (2019). Innovation efficiency of semiconductor industry in China: A new framework based on generalized three-stage DEA analysis. Socio-Economic Planning Sciences, 66, 136–148. https://doi.org/10.1016/j.seps.2018.07.007
Liik, M., Masso, J., & Ukrainski, K. (2014). The contribution of R&D to production efficiency in OECD countries: Econometric analysis of industry-level panel data. Baltic Journal of Economics, 14(1–2), 78–100. https://doi.org/10.1080/1406099X.2014.981105
Mandl, U., Dierx, A., & Ilzkovitz, F. (2008). The effectiveness and efficiency of public spending (Economic Papers No 301). European Commission. Retrieved September 17, 2022, from http://ec.europa.eu/economy_finance/publications/publication11902_en.pdf
Masso, J., Karma, K., & Pavlenkova, I. (2022). Estonia. In B. Larsson & B. Rolandsson (Eds.), The digital transformation of financial services markets and industrial relations – exploring FinTech development in Denmark, Estonia, the Netherlands and Sweden (Working papers – Department of Sociology and Work Science, No 1).
Novotná, M., Volek, T., Rost, M., & Vrchota, J. (2021). Impact of technology investment on firm’s production efficiency factor in manufacturing. Journal of Business Economics and Management, 22(1), 135–155. https://doi.org/10.3846/jbem.2020.13635
OECD. (2022). Investment (GFCF) (indicator). https://doi.org/10.1787/b6793677-en
Overbeek, H. (2012). Sovereign debt crisis in Euroland: Root causes and implications for European integration. The International Spectator, 47(1), 30–48. https://doi.org/10.1080/03932729.2012.655006
Piesse, J., & Thirtle, C. (2000). A stochastic frontier approach to firm level efficiency, technological change, and productivity during the early transition in Hungary. Journal of Comparative Economics, 28(3), 473–501. https://doi.org/10.1006/jcec.2000.1672
Sanchez, M. (2021). What drives euro area labour productivity growth? An international production-frontier examination. In P. C. Kostis (Ed.), Bridging microeconomics and macroeconomics and the effects on economic development and growth (pp. 231–258). IGI Global. https://doi.org/10.4018/978-1-7998-4933-9.ch012
Schaffer, A., Simar, L., & Rauland, J. (2011). Decomposing regional efficiency. Journal of Regional Science, 51(5), 931–947. https://doi.org/10.1111/j.1467-9787.2011.00731.x
Schwab, K. (2017). The fourth industrial revolution. Currency.
Severgnini, H. B. (2009). Essays in total factor productivity measurement [Dissertation]. Retrieved August 23, 2021, from https://d-nb.info/1010221167/34
Sickles, R., & Zelenyuk, V. (2019). Measurement of productivity and efficiency: Theory and practice. Cambridge University Press. https://doi.org/10.1017/9781139565981
Stead, A. D., Wheat, P., & Greene, W. H. (2023). Robustness in stochastic frontier analysis. In P. Macedo, V. Moutinho, & M. Madaleno (Eds.), Lecture notes in economics and mathematical systems: Vol. 692. Advanced mathematical methods for economic efficiency analysis (pp. 197–228). Springer, Cham. https://doi.org/10.1007/978-3-031-29583-6_12
Stornelli, A., Ozcan, S., & Simms, C. (2021). Advanced manufacturing technology adoption and innovation: A systematic literature review on barriers, enablers, and innovation types. Research Policy, 50(6), Article 104229. https://doi.org/10.1016/j.respol.2021.104229
Teirlinck, P., & Khoshnevis, P. (2022). SME efficiency in transforming regional business research and innovation investments into innovative sales output. Regional Studies, 56(12), 2147–2163. https://doi.org/10.1080/00343404.2022.2046263
Toufaily, E., Zalan, T., & Dhaou, S. B. (2021). A framework of blockchain technology adoption: An investigation of challenges and expected value. Information & Management, 58(3), Article 103444. https://doi.org/10.1016/j.im.2021.103444
Yang, L., & Wang, S. (2022). Do fintech applications promote regional innovation efficiency? Empirical evidence from China. Socio-Economic Planning Sciences, 83, Article 101258. https://doi.org/10.1016/j.seps.2022.101258