Digitalisation and income inequality in Central and Eastern European countries
DOI:
https://doi.org/10.18559/ref.2024.1.946Keywords:
income inequality, digitalisation, canonical correlation, Central and Eastern Europe countriesAbstract
The COVID-19 pandemic has highlighted the importance of digital technologies in business and daily life. The paper aims to explore the theoretical and empirical aspects of the relation between digitalisation and income inequality in Central and Eastern European (CEE) countries between the years 2000-2020. It contributes to existing research on determinants of income inequality, focussing on the potential negative role of digitalisation as an unnoticeable driver of income inequality in CEE countries. To investigate the potential impact of digitalisation on income inequality, empirical analysis was performed for the sample of 10 CEE countries, namely Bulgaria, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, the Slovak Republic and Slovenia. The results of canonical correlation analysis indicated that the sets of variables related to digitalisation and inequality as a group are significantly related to each other and a strong correlation exists between them. The relative contribution of each indicator to each standardised function showed that the highest values of significant standardised coefficients were observed for income inequality indicators such as the top 10% share, the Gini coefficient, and the top 1% share, while in digitalisation measures, the highest value was observed for Internet users and fixed and mobile broadband subscriptions.
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References
Acemoglu, D. (2002). Technical change, inequality, and the labor market. Journal of Economic Literature, 40(1), 7–72. https://doi.org/10.1257/jel.40.1.7
View in Google Scholar
Acemoglu, D., & Restrepo, P. (2022). Tasks, automation, and the rise in US wage inequality. Econometrica, 90(5), 1973–2016.
View in Google Scholar
Alvaredo, F., & Gasparini, L. (2015). Recent trends in inequality and poverty in developing countries. Handbook of Income Distribution, 2, 697–805. https://doi.org/10.1016/B978-0-444-59428-0.00010-2
View in Google Scholar
Antonczyk, D., Fitzenberger, B., & Leuschner, U. (2009). Can a task-based approach explain the recent changes in the German wage structure? Jahrbucher fur Nationalokonomie und Statistik, 229(2–3), 214–238. https://doi.org/10.1515/jbnst-2009-2-309
View in Google Scholar
Arendt, Ł. (2015). The digital economy, ICT and economic growth in the CEE countries. Olsztyn Economic Journal, 10(3), 247–262. https://doi.org/10.31648/oej.3150
View in Google Scholar
Autor, D. H., Katz, L. F., & Krueger, A. B. (1998). Computing inequality: Have computers changed the labor market? Quarterly Journal of Economics, 113(4), 1169–1213.
View in Google Scholar
Berg, M. (1980). The Machinery Question and the Making of Political Economy 1815–1848. Cambridge University Press.
View in Google Scholar
Brzeziński, M., & Sałach, K. (2022). Determinants of inequality in transition countries. IZA World of Labor, 496, 1–11. https://doi.org/10.15185/izawol.496
View in Google Scholar
Bukowski, P., & Novokmet, F. (2017). Inequality in Poland: Estimating the whole distribution by g-percentile 1983–2015. WID.world Working Paper Series, 21.
View in Google Scholar
Butryn, B. (2020). Digitalization in the transformation of the business environment. Informatyka Ekonomiczna. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, 4(58), 67–79. https://doi.org/10.15611/ie.2020.4.05
View in Google Scholar
Card, D., & DiNardo, J. E. (2002). Skill-biased technological change and rising wage inequality. Journal of Labor Economics, 20(4), 733–783.
View in Google Scholar
Dahlman, C., Mealy, S., & Wermelinger, M. (2016). Harnessing the digital economy for developing countries. OECD Development Centre Working Papers, 334. https://www.oecd-ilibrary.org/development/harnessing-the-digital-economy-for-developing-countries_4adffb24-en
View in Google Scholar
Dattalo, P. (2014). A demonstration of canonical correlation analysis with orthogonal rotation to facilitate interpretation [unpublished manuscript]. School of Social Work, Virginia Commonwealth University, Richmond.
View in Google Scholar
Deaton, A. (2013). The great escape. Health, wealth, and the origins of inequality. Princeton University Press.
View in Google Scholar
Di, Y., Zhi, R., Song, H., & Zhang, L. (2022). Development and influencing factors of international trade in digitally deliverable services. Frontiers in Psychology, 13, 1–13. https://doi.org/10.3389/fpsyg.2022.908420
View in Google Scholar
Fan, M., Yang, A. C., Fuh, J.-L., & Chou, C.-A. (2018). Topological pattern recognition of severe alzheimer’s disease via regularized supervised learning of EEG complexity. Frontiers in Neuroscience, 12, article 685. https://doi.org/10.3389/fnins.2018.00685
View in Google Scholar
Fiedler, P., Fidrmuc, J., & Reck, F. (2021). Automation, digitalization, and income inequality in Europe. Finance a úvěr / Czech Journal of Economics and Finance, 71(3), 203–219. https://doi.org/10.32065/CJEF.2021.03.01
View in Google Scholar
Flemming, J. S., & Micklewright, J. (2000). Income distribution, economic systems and transition. Handbook of Income Distribution, 1, 843–918. https://doi.org/10.1016/S1574-0056(00)80017-2
View in Google Scholar
Frey, C. B., & Osborne, M. A. (2017). The future of employment: how susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019
View in Google Scholar
Gal, P., Nicoletti, G., Renault, T., Sorbe, S., & Timiliotis, C. (2019). Digitalisation and productivity: In search of the holy grail – Firm-level empirical evidence from EU countries. OECD Economics Department Working Papers, 1533. https://doi.org/10.1787/5080f4b6-en
View in Google Scholar
Götz, M., Bartosik-Purgat, M., & Jankowska, B. (2018). International aspects and challenges of digital transformation. Gospodarka Narodowa, 1(293), 87–102.
View in Google Scholar
Griliches, Z. (1969). Capital-skill complementarity. The Review of Economics and Statistics, 51(4), 465–468. http://www.jstor.org/stable/1926439
View in Google Scholar
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (7th ed.). Pearson Education.
View in Google Scholar
Katz, L. F., & Murphy, K. M. (1992). Changes in relative wages, 1963–1987: Supply and demand factors. The Quarterly Journal of Economics, 107(1), 35–78.
View in Google Scholar
Keister, R., & Lewandowski, P. (2017). A routine transition in the digital era? The rise of routine work in Central and Eastern Europe. Transfer: European Review of Labour and Research, 23(3), 263–279.
View in Google Scholar
Keynes, J. M. (1963). Essays in Persuasion. W.W. Norton & Company.
View in Google Scholar
Kraus, S., Jones, P., Kailer, N., Weinmann, A., Chaparro-Banegas, N., & Roig-Tierno, N. (2021). Digital transformation: An overview of the current state of the art of research. SAGE Open, 11(3), 1–15. https://doi.org/10.1177/21582440211047576
View in Google Scholar
Kuznets, S. (1955). Economic growth and income inequality. The American Economic Review, 45(1), 1–28.
View in Google Scholar
Magda, I., Gromadzki, J., & Moriconi, S. (2021). Firms and wage inequality in Central and Eastern Europe. Journal of Comparative Economics, 49(2), 499–552. https://doi.org/10.1016/j.jce.2020.08.002
View in Google Scholar
Milanovic, B. (2001). Inequality during the transition: Why did it increase? In: O. Havrylyshyn,
View in Google Scholar
S. M. Nsouli (Eds.), A Decade of Transition. Achievements and Challenges. International Monetary Fund. https://www.elibrary.imf.org/display/book/9781589060135/ch12.xml
View in Google Scholar
Moll, B., Rachel, L., & Restrepo, P. (2022). Uneven growth: Automation’s impact on income and wealth inequality. Econometrica, 90(6), 2645–2683.
View in Google Scholar
Mönnig, A., Maier, T., & Zika, G. (2019). Economy 4.0 – Digitalisation and its effect on wage inequality. Jahrbucher fur Nationalokonomie und Statistik, 239(3), 363–398. https://doi.org/10.1515/jbnst-2017-0151
View in Google Scholar
Myovella, G., Karacuka, M., & Haucap, J. (2020). Digitalization and economic growth: A comparative analysis of Sub-Saharan Africa and OECD economies. Telecommunications Policy, 44(2). https://doi.org/10.1016/j.telpol.2019.101856
View in Google Scholar
Novokmet, F. (2017). Between communism and capitalism: essays on the evolution of in- come and wealth inequality in Eastern Europe 1890–2015 (Czech Republic, Poland, Bulgaria, Croatia, Slovenia, Russia) [unpublished PhD thesis]. Paris School of Economics.
View in Google Scholar
Piketty, T. (2014). Capital in the twenty-first century. The Belknap Press of Harvard University Press.
View in Google Scholar
Qureshi, Z. (2021). Technology, growth, and inequality. Changing Dynamics in the Digital Era, Global Working Paper #152. https://www.brookings.edu/wp-content/uploads/2021/02/Technology-growth-inequality_final.pdf
View in Google Scholar
Roine, J., & Waldenström, D. (2015). Chapter 7. Long-run trends in the distribution of income and wealth. Handbook of Income Distribution, 2, 469–592. https://doi.org/10.1016/B978-0-444-59428-0.00008-4
View in Google Scholar
Song, J., Price, D. J., Guvenen, F., Bloom, N., & Wachter, T. (2019). Firming up inequality. Quarterly Journal of Economics, 134(1), 1–50. https://doi.org/10.1093/QJE/QJY025
View in Google Scholar
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Qi Dong, J., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
View in Google Scholar
Vial, G., (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
View in Google Scholar
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