The Covid-19 disease and policy response to mitigate the economic impact in the EU

    Marek Zinecker   Affiliation
    ; Karel Doubravský   Affiliation
    ; Adam P. Balcerzak   Affiliation
    ; Michał Bernard Pietrzak   Affiliation
    ; Mirko Dohnal Affiliation


This study aims to understand how Covid-19 contagious disease and the EU’s policy response may affect macroeconomic performance. Previous studies on this topic have used historical data sets on “rare macroeconomic disasters” such as Great Influenza to assess the impact of the current pandemic on the global economy. The authors examine the main channels of transmission and targeted policy response to mitigate crisis qualitatively. The authors use heuristics and apply qualitative trend-based analysis because the current pandemic is a unique event for which accurate quantitative data are not currently available. Researchers first identify a set of eight variables based on previous academic theories. They then express each variable as a trend: ascending, descending, and constant. The numerical calculations consist of 17 scenarios, supplemented by 24 transitions and a transition graph. Besides, the article proposes a graphical solution to examine the change in GDP that is too small. The results of the study should be understood as a reference point to allow both private and public stakeholders to understand better the relationship between the observed variables and their dynamics. The research provides a comprehensive list of future events to examine further the implications for the economy as a whole and each individual.

First published online 26 April 2021

Keyword : Covid-19, economic impact, GDP, qualitative trend-based analysis, model, scenarios

How to Cite
Zinecker, M., Doubravský, K., Balcerzak, A. P., Pietrzak, M. B., & Dohnal, M. (2021). The Covid-19 disease and policy response to mitigate the economic impact in the EU. Technological and Economic Development of Economy, 27(3), 742-762.
Published in Issue
May 25, 2021
Abstract Views
PDF Downloads
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Barro, R. J., & Ursúa, J. F. (2008). Macroeconomic crises since 1870. Brookings Papers on Economic Activity, 2008, 255–335.

Barro, R. J., Ursúa, J., F., & Weng, J. (2020). The coronavirus and the great influenza pandemic: Lessons from the “Spanish Flu” for the coronavirus’s potential effects on mortality and economic activity. (Working paper). National Bureau of Economic Research.

Boissay, F., & Rungcharoenkitkul, P. (2020). Macroeconomic effects of Covid-19: an early review. Bank for International Settlements, Basel.

Bredeweg, B., Liem, J., & Nicolaou, C. (2016). Assessing learner-constructed conceptual models and simulations of dynamic systems. In K. Verbert, M. Sharples, & T. Klobučar (Eds.), Lecture notes in computer science: Vol. 9891. Adaptive and adaptable learning (pp. 357–362). Springer Verlag.

Cahuc, P. (2019). Short-time work compensation schemes and employment. IZA World of Labor, 11(2), 1.

Correia, S., Luck, S., & Verner, E. (2020). Pandemics depress the economy, public health interventions do not: Evidence from the 1918 flu. SSRN.

Dias, R., Teixeira, N., Machova, V., Pardal, P., Horak, J., & Vochozka, M. (2020). Random walks and market efficiency tests: evidence on US, Chinese and European capital markets within the context of the global Covid-19 pandemic. Oeconomia Copernicana, 11(4), 585–608.

Dohnal, M. (1991). A methodology for common-sense model development. Computers in Industry, 16(2), 141–158.

Dosi, G., Napoletano, M., Roventini, A., Stiglitz, J. E., & Treibich, T. (2020). Rational heuristics? Expectations and behaviors in evolving economies with heterogeneous interacting agents. Economic Inquiry, 58(3), 1487–1516.

Doubravský, K., & Dohnal, M. (2015). Reconciliation of decision-making heuristics based on decision trees topologies and incomplete fuzzy probabilities sets. Plos One, 7(10), 1–18.

Doubravský, K., & Dohnal, M. (2018). Qualitative equationless macroeconomic models as generators of all possible forecasts based on three trend values – Increasing, constant, decreasing. Structural Change and Economic Dynamics, 45, 30–36.

Doubravský, K., Doskocil, R., & Dohnal, M. (2020). A dynamic knowledge model of project time-cost analysis based on trend modelling. Periodica Povlytechnica Social and Management Sciences, 28(1), 18–28.

Eichenbaum, M. S., Rebelo, S., & Trabandt, M. (2020). The macroeconomics of epidemics. (NBER Working Paper Series).

Eriksson von Allmen, U., Jeasakul, P., Kang, H., & Khera, P. (2020). Macrofinancial considerations for assessing the impact of the COVID-19 pandemic. International Monetary Fund
European Commission. (2020). Coordinated economic response to the COVID-19 Outbreak. COM(2020) 112 final. Brussels.

Gigerenzer, G., & Gaissmaier, G. (2011). Heuristic decision making. Annual Review of Psychology, 62, 451–482.

Gopinath, G. (2020, April 14). The Great Lockdown: Worst economic downturn since the Great Depression. IMFBlog. International Monetary Fund, New York.

Guerrieri, V., Lorenzoni, G., Straub, L., & Werning, I. (2020). Macroeconomic implications of Covid-19: Can negative supply shocks cause demand shortages? (NBER Working Paper Series).

Huterski, R., Huterska, A. A., Łapińska, J., & Zdunek-Rosa, E. (2020). The problem of savings exclusion and gross savings in the new European Union member states. Entrepreneurship and Sustainability Issues, 7(3), 2470–2480.

Kermack, W. O., & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London, series A 115(772), 700–721.

Korzeb, Z., & Niedziółka, P. (2020). Resistance of commercial banks to the crisis caused by the COVID-19 pandemic: the case of Poland. Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(2), 205–234.

Kufel, T. (2020). ARIMA-based forecasting of the dynamics of confirmed Covid-19 cases for selected European countries. Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(2), 181– 204.

Kuc-Czarnecka, M. (2020). COVID-19 and digital deprivation in Poland. Oeconomia Copernicana, 11(3), 415–431.

Lagarde, C. (2020, April 9). How the ECB is helping firms and households. The ECB Blog.

McKibbin, W. J., & Fernando, R. (2020). The global macroeconomic impacts of COVID-19: Seven scenarios. SSRN.

Nakamura, E., Steinsson, J., Barro, R., & Ursúa, J. (2010). Crises and recoveries in an empirical model of consumption disasters (NBER Working Paper Series, 15920).

OECD. (2020). Evaluating the initial impact of COVID-19 containment measures on economic activity.

Pardal, P., Dias, R., Šuleř, P., Teixeira, N., & Krulický, T. (2020). Integration in Central European capital markets in the context of the global COVID-19 pandemic. Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(4), 627–650.

Ramsden, D. (2020). The potential long-term economic effects of Covid. Institute for Policy and Engagement, University of Nottingham.

UNCTAD. (2020). Global trade impact of the Corona Virus (Covid-19) epidemic.

Vicha, T., & Dohnal, M. (2008). Qualitative identification of chaotic systems behaviours. Chaos, Solutions and Fractals, 38(1), 70–78.

Villez, K. (2015). Qualitative path estimation: A fast and reliable algorithm for qualitative trend analysis. AIChE Journal, 61(5), 1535–1546.

Yan, X., Zhou, Y., Wen, Y., & Chai, X. (2013). Qualitative and quantitative integrated modeling for stochastic simulation and optimization. Journal of Applied Mathematics, 2013, 831273.