VSTE
Littera Scripta

ISSN (online): 1805-9112

Research ArticleOpen access

Development and Forecast of Unemployment in the Czech Republic

Tereza Kalinová1*, Vilém Kovač1

  1. Institute of Technology and Business, School of Expertness and Valuation, České Budějovice, Czechia

* Corresponding author.

Abstract

Unemployment is one of the key indicators of the state of the economy and labor market stability, and its development is sensitive to economic cycles and extraordinary economic shocks. The aim of this study was to evaluate the development of unemployment in the Czech Republic over the last ten years, identify the key factors influencing its dynamics, and propose a predictive model for estimating future developments. To achieve this goal, time series analysis, multivariate regression analysis, and the ARIMA seasonal model were used. The results showed significant seasonality in unemployment and its decline to historically low levels in 2017 2019. The impact of the COVID-19 pandemic was only a temporary disruption of the long-term trend, followed by a stabilization of the unemployment rate. The number of registered job seekers and the number of job vacancies had a significant impact on the development of unemployment. The prediction indicated a slight increase in the unemployment rate in 2026 without any indication of a significant structural break. The paper provides a comprehensive view of unemployment trends and, with the proposed model, offers a tool for further research and decision-making in the labor market. However, the scope of available data is a limitation.

Keywords:Unemploymenttime seriesregression modelARIMA modellabour marketforecastingeconomic trends

References

  1. Ahmad, M., Khan, Y. A., Jiang, C. H., Kazmi, S. J. H., & Abbas, S. Z. (2023). The impact of COVID-19 on unemployment rate: An intelligent based unemployment rate prediction in selected countries of Europe. International Journal of Finance & Economics, 28(1), 528–543. https://doi.org/10.1002/ijfe.2434
  2. Bachmann, R., et al. (2024). The impact of robots on labour market transitions in Europe. Structural Change and Economic Dynamics, 70, 422–441. https://doi.org/10.1016/j.strueco.2024.05.005
  3. Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2016). Time series analysis: Forecasting and control (5th ed.). Wiley.
  4. Bradley, J., & Mann, L. (2024). A general equilibrium model of the labor market with learning and misallocation. Journal of Monetary Economics, 148, 103612. https://doi.org/10.1016/j.jmoneco.2024.103612
  5. Český statistický úřad [Czech Statistical Office]. (n.d.). Míra nezaměstnanosti podle pohlaví a věkových skupin [Unemployment rate by sex and age groups]. https://vdb.czso.cz/vdbvo2/faces/cs/index.jsf?page=vystup-objekt-parametry&z=T&f=TABULKA&katalog=30853&pvo=ZAMD002
  6. Český statistický úřad [Czech Statistical Office]. (n.d.). Trh práce – základní ukazatele [Labour market – basic indicators]. https://csu.gov.cz/produkty/zam_cr
  7. Český statistický úřad [Czech Statistical Office]. (n.d.). Zaměstnanost a nezaměstnanost – regionální data [Employment and unemployment – regional data]. https://vdb.czso.cz/vdbvo2/faces/cs/index.jsf?page=vystup-objekt&pvo=ZAMD006
  8. Český statistický úřad [Czech Statistical Office]. (n.d.). Veřejná databáze – zaměstnanost a nezaměstnanost [Public database – employment and unemployment]. https://vdb.czso.cz
  9. Eeckhout, J., & Lindenlaub, I. (2019). Search behavior, multiple equilibria, and cyclical outcomes in the labor market. American Economic Journal: Macroeconomics, 11(4), 175–234. https://doi.org/10.1257/mac.20180105
  10. Fan, X., Xu, Z., Skare, M., & Wang, X. (2025). The role of entrepreneurship and management in economic systems. International Entrepreneurship and Management Journal, 21(1), Article 71. https://doi.org/10.1007/s11365-025-01095-4
  11. Fronckova, K., Prazak, P., & Soukal, I. (2019). Review of Kalman filter employment in the NAIRU estimation. Systems, 7(3), 33. https://doi.org/10.3390/systems7030033
  12. Gujarati, D. N., & Porter, D. C. (2015). Basic econometrics (6th ed.). McGraw-Hill Education.
  13. Kapas, J. (2022). Has COVID-19 caused a change in the dynamics of the unemployment rate? The case of North America and continental Europe. Regional Statistics, 12(1), 3–26. https://doi.org/10.15196/RS120107
  14. Kapicka, M., & Rupert, P. (2022). Labor market dynamics during COVID-19: SIR epidemic model and frictional labor market. Journal of Economic Theory, 204, 105520. https://doi.org/10.1016/j.jet.2022.105520
  15. Kiley, M. T. (2022). Fluctuations in the risk of a large increase in unemployment. Journal of Money, Credit and Banking, 54(5), 1407–1424. https://doi.org/10.1111/jmcb.12888
  16. Kurzy.cz. (n.d.). Nezaměstnanost – dlouhodobý vývoj. https://www.kurzy.cz/makroekonomika/nezamestnanost/
  17. Lacy, S., Watson, B. R., Riffe, D., & Lovejoy, J. (2015). Issues and best practices in content analysis. Journalism & Mass Communication Quarterly, 92(4), 791–811. https://doi.org/10.1177/1077699015607338
  18. Latner, J. P. (2022). Temporary employment in Europe: Stagnating rates and rising risks. European Societies, 24(4), 383–408. https://doi.org/10.1080/14616696.2022.2072930
  19. Martín-Román, A. L., Cuéllar-Martín, J., & Moral, A. (2023). Effective unemployment: A stochastic cost frontier approach. Bulletin of Economic Research, 75(1), 5–39. https://doi.org/10.1111/boer.12335
  20. Ministerstvo práce a sociálních věcí [Ministry of Labour and Social Affairs]. (n.d.). MPSV data – databáze nezaměstnanosti. https://data.mpsv.cz
  21. Nicoli, F., et al. (2024). Labour market risks and preferences for EU unemployment insurance: The effect of automation, globalization and migration concerns. European Political Science Review. Advance online publication. https://doi.org/10.1017/S1755773924000316
  22. Petrúsek, I., & Basna, K. (2025). Structural and cyclical unemployment and redistribution support in Europe: The moderating role of welfare state size. West European Politics. Advance online publication. https://doi.org/10.1080/01402382.2025.2556601
  23. Pi, J., & Duan, S. X. (2023). Appropriation, rural-urban migration, minimum wage and unemployment: A general equilibrium approach. Australian Economic Papers, 62(3), 430–456. https://doi.org/10.1111/1467-8454.12300
  24. Posta, V. (2023). The disaggregation of the projected impacts of automation in the regional labour markets between 2019 and 2030: Case of the Czech Republic. Regional Statistics, 13(3), 487–509. https://doi.org/10.15196/RS130305
  25. Priede, J. (2023). Productivity challenges in Europe during the COVID-19 pandemic. European Integration Studies, 17, 99–107. https://doi.org/10.5755/j01.eis.1.17.34019
  26. Rolník, O. (2023). The influence of the economic disparities between regions on political polarisation in the Czech Republic. Scientific Papers of the University of Pardubice, Series D: Faculty of Economics and Administration, 31(1), Article 1614. https://doi.org/10.46585/sp31011614
  27. Zubíková, A., Veselá, K., & Smolák, P. (2023). Evaluation of the Antivirus A programme in the Czech Republic during the COVID-19 pandemic. International Journal of Economic Sciences, 12(1), 178–205. https://doi.org/10.52950/ES.2023.12.1.009