This paper investigates the effects of the COVID-19 pandemic on the bilateral trade between Germany and the Visegrad Four (V4) countries—Czechia, Hungary, Poland, and Slovakia. The focus on Germany is due to its significant role as the V4's strongest and geographically closest trading partner. Germany's powerful economy and its extensive involvement in regional industrial production value chains create strong economic ties with its neighboring V4 nations. The pandemic severely disrupted these value chains, particularly in the manufacturing sector, which is dominant in the region. The research aims to quantify the impact of COVID-19 on both exports and imports between Germany and each V4 country, providing insights into the pandemic's disruption of this vital trade relationship. The V4 countries, while located in Central Europe and sharing geographical and geological similarities, exhibit variations in size, foreign trade volume, and economic development levels. While they contribute significantly to the EU's population, their combined GDP remains below the EU average, highlighting economic disparities within the group. Previous research has already established that COVID-19 had a statistically significant, yet country-specific impact on V4 internal trade.

The literature review examines existing research on the multifaceted impacts of COVID-19 on various aspects of global and regional economies. Studies highlighted the short-term and long-term effects on global trade, labor markets, and supply chains, with some suggesting that while disruptions occurred, the overall adverse effects were manageable. Other research focuses on specific country pairs like China and the USA, revealing initial supply-side disruptions in China that reduced demand and consumer income, subsequently negatively affecting bilateral trade. The vulnerability of lower-income countries and labor-intensive industries in exporting nations to the pandemic's economic shocks has been consistently emphasized. The role of trade policy responses, varying across different income groups, has also been investigated, with a conclusion that most trade restrictions were justified. Studies also address specific aspects of the COVID-19 impact on the V4 region, including health policy responses, labor market effects, and the challenging business environment faced by exporting firms. Research on the pre-pandemic economic situation of the V4 countries and their trading partners is also reviewed to provide a context for understanding the impact of COVID-19. Specific data on trade maturity, measured by per capita trade volume, shows differences among the V4 countries and their neighbors. The impact of public institutions in influencing citizen behavior during the pandemic in Germany and other countries is also considered, highlighting the interconnectedness of health policies and economic outcomes. Finally, the review touches on the impact of COVID-19 on the structure of international energy trade, noting that while new communities emerged, the overall networks remained largely unaffected.

To analyze the impact of COVID-19 on trade between Germany and the V4 countries, the study utilizes monthly data from 2010M1 to 2021M4. The choice of monthly data, instead of annual or quarterly data, allows for a higher frequency of observations and a more accurate assessment of the pandemic's effects. Data on trade and GDP were collected from Eurostat, representing EU trade since 1988 using the SITC classification and GDP in current prices. Quarterly GDP data was converted to monthly data using linear interpolation in EViews 10. Real exchange rate data, obtained from FRED (Federal Reserve Economic Data), was used as the real broad effective exchange rate (indexed to 2010=100). Since Slovakia uses the Euro while other V4 countries have their own currencies, USD was selected as a common currency for analysis. An impulse dummy variable (D) was used to capture the impact of COVID-19, taking a value of 1 for 2020M03 and 0 otherwise. The ARDL bounds test for cointegration was employed, which is suitable even when variables have different integration levels. This is a key advantage over the Johansen-Juselius cointegration test, which requires all variables to be at the same integration level. The ARDL model is suitable for small sample sizes, making it appropriate for the dataset in this study. The model specifications for exports and imports include lagged values of the dependent variables (logarithms of seasonally adjusted exports and imports), lagged values of the GDP of both the V4 country (host country) and Germany (partner country), and lagged values of the real broad exchange rate. All data was initially seasonally adjusted before being used in the model. Diagnostic tests were conducted, including the Breusch-Godfrey LM test for autocorrelation, the Ramsey RESET test for specification error, and the CUSUM and CUSUMSQ tests for model stability. The variance inflation factor (VIF) was used to check for multicollinearity. The ARDL model was estimated using EViews 12.

The unit root tests indicated mixed results regarding the order of integration of the variables. Some variables were I(0) and others were I(1), further justifying the choice of the ARDL bounds testing approach. The bounds tests showed that the null hypothesis of no cointegration was rejected for all V4 countries, signifying a long-run relationship between the variables. In the long-run export models, the GDP of Germany was a significant driver of exports for Czechia, Hungary, and Poland, except for Slovakia. As expected, the host country's GDP was not significant, suggesting the significant influence of Germany's economic activity. The exchange rate variable for Hungary was found to have a negative impact on exports. For short-run analysis, the error correction term (ECT) was significant and negatively signed for Czechia, Hungary, and Slovakia, implying a short-run adjustment towards long-run equilibrium. However, the ECT was insignificant in the Polish model. Notably, in all export models, the COVID-19 dummy variable was significant and negative, indicating a negative effect of the pandemic on trade. The long-run import models revealed that for Czechia and Slovakia, the GDP of Germany had a positive and significant effect on imports, while in Poland and Slovakia, the host country's GDP also had a significant positive effect (though negative in Slovakia). Slovakia's exchange rate was significantly and positively related to imports, which is what is expected. In the short-run import models, the COVID-19 dummy variable was again significant and negative for all V4 countries, indicating that the pandemic had a negative effect on imports. Diagnostic tests showed that the models generally performed well except for issues with autocorrelation and model stability in some instances. The high VIF values for the GDP variables were noted but were not viewed as highly problematic given the overall results.

The findings confirm a strong long-run relationship between trade (both exports and imports) and the economic activity of Germany for the V4 countries, highlighting the importance of Germany as their primary trading partner. The impact of COVID-19 was consistent across all V4 countries, with the pandemic causing a significant and negative impact on both exports and imports. The transient nature of this impact, with trade generally returning to its previous trend after the initial shock, suggests that while the pandemic caused a disruption, the long-term structural relationships between Germany and the V4 countries remained relatively robust. These findings have implications for policymakers and businesses, emphasizing the need for preparedness for future disruptions by focusing on health system resilience and enhancing the flexibility and adaptability of production chains. The importance of the EU's economic framework in maintaining stability and facilitating trade is also underlined. The significance of Germany's role in the region's economic development is reinforced.

This study offers valuable insights into the impact of COVID-19 on the trade relationships between Germany and the V4 countries. The ARDL model effectively captures the short-run and long-run effects of the pandemic, demonstrating a significant negative short-term impact while highlighting the relative resilience of the long-term trade relationships. Future research could benefit from using a longer historical dataset to confirm the findings and explore the potential impacts of other macroeconomic factors like inflation and energy prices.

The primary limitation of this study stems from the relatively short time frame of the available monthly data. The observed effects of COVID-19 might evolve over time with a longer-term perspective. It will be important to monitor whether trade volumes return to pre-pandemic levels and assess the duration of the recovery. Furthermore, it is acknowledged that other significant factors, such as the ongoing geopolitical situation and inflationary pressures, could influence trade dynamics between Germany and the V4 countries. A longer time series analysis would be beneficial to better understand the long-term impacts and to separate the effects of COVID-19 from other confounding variables.