Monetary Policy Response During COVID-19 and the Russia-Ukraine War: Evidence from Euro and Non-Euro Area

Florin Aliu et al.

Studies in Business and Economics2025https://doi.org/10.2478/sbe-2025-0001article
ABDC C
Weight
0.41

What the paper says

Abstract The outbreak of the COVID-19 pandemic activated the European Central Bank (ECB) to maintain financial stability. Two years later, the Russian-Ukraine war accelerated commodity prices and set inflation at unprecedented levels. The conflict in Ukraine once again tested the managerial capacities of the ECB and Non-Euro area central banks to control inflation. Considering these two non-economic shocks for the European economy, we analyze the monetary policy actions toward inflation and unemployment rate. The Panel Vector Autoregression (VAR) was used standing on the two-step generalized method of moments (GMM). The series covers the period from January 1, 2014, to August 1, 2023, through three independent panels. Panel A is the eurozone member states, Panel B the non-euro area, and Panel C the Scandinavian countries. The results show that Scandinavian and non-Eurozone countries have been much more effective in mitigating inflation than the ECB. The monetary policy in these countries had a significant influence on unemployment as well. On the other hand, the ECB has stayed within its mandate even during this period, targeting only inflation. The results interest policymakers in terms of monetary efficiency and response speed.

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https://doi.org/https://doi.org/10.2478/sbe-2025-0001

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@article{florin2025,
  title        = {{Monetary Policy Response During COVID-19 and the Russia-Ukraine War: Evidence from Euro and Non-Euro Area}},
  author       = {Florin Aliu et al.},
  journal      = {Studies in Business and Economics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.2478/sbe-2025-0001},
}

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.