VoxEU Column COVID-19 International trade

The 2020 trade impact of the Covid-19 pandemic

Worldwide merchandise trade flows decreased significantly in 2020, as Covid-19 disrupted economic activity across the globe. This column analyses how various pandemic-related factors shaped international trade flows. Specifically, it estimates how Covid-19 incidence and lockdown restrictions affected the monthly year-over-year growth of imports from China for all destinations to which China exported goods in 2019–2020. It finds that government measures to curb economic activities had a larger impact on a country’s imports than the direct health and behavioural effects of the pandemic itself.

The Covid-19 pandemic has drastically affected lives and livelihoods. In the process, it has also disrupted economic activities throughout the world. In particular, worldwide merchandise trade flows decreased by 7% in 2020. There are several dimensions to the pandemic that are likely to affect international trade: its direct health impact and associated behavioural changes; the consequences of governments’ actions to prevent the spread of the virus; and the impact of the pandemic in third countries. 

Although it seems intuitive to expect negative trade effects due to the pandemic, at the country level the effect could go in either direction. As Baldwin (2020) pointed out at its onset, the pandemic delivered a shock from both the supply and demand sides. Since both are negative, the resulting impact on a country’s import demand – defined as the difference between its domestic demand and domestic supply – is a priori ambiguous. The repercussions of the pandemic on other trading partners of a country, and on its own demand for imports from a specific country, are also ambiguous, depending on how third-country demand and supply factors are affected.

In a new paper (Liu et al. 2021), we resolve these ambiguities and provide what we believe are the first estimates of how each of these channels affected international trade flows in 2020, viewed through their impact on imports from China. Specifically, we estimate how Covid-19 incidence and lockdown restrictions, within a country and on its trading partners, affected the monthly year-over-year growth of imports from China for all destinations to which China exported in 2019–2020, at the product (HS 6-digit) level.

One advantage of using China as a ‘hub’ is that China’s monthly trade data up to December 2020 is already available. To the best of our knowledge, this makes our analysis the first to evaluate the trade effects of the pandemic for 2020 as a whole. Another advantage is that China has trade relationships with every other economy and is the largest exporter in the world. Furthermore, China suffered the most from Covid-19 in the first quarter of 2020, when the rest of the world was only starting to experience the consequences of the virus. From the second quarter onwards, which is when our variables of interest start to vary more significantly, the situation reversed, and China’s economy recovered swiftly, growing 2.3% in 2020. Thus, in the more relevant period for our estimation, between April and December, the main covid-related impediments of trade with China stemmed mostly from the pandemic’s influence on China’s trading partners. This avoids mixing pandemic-related factors in exporting and importing countries.

The average trade effects of the pandemic 

We find that the direct effects of Covid-19 incidence (expressed by the number of deaths per capita) and of covid-induced government measures (expressed by an index of the stringency of lockdowns)1 are clearly negative, indicating that the negative own-demand effect on countries’ imports from China prevails over the negative own-supply effect. As Table 1 shows, relative to pre-pandemic conditions, a country with the highest level of deaths per thousand people in a month in our sample (Slovenia in December 2020) would experience a reduction of 13% in imports from China for that month. Similarly, moving from no lockdowns to the maximum level of lockdown stringency in the sample (Honduras in April and May; the Philippines in April) would generate a reduction of 17.6% in imports from China. This reveals that government measures to curb economic activities tend to have a larger effect on a country’s imports than the direct health and behavioural impacts of the pandemic. If we consider an increase of one standard deviation in each of these variables, the reduction in imports would be, respectively, 1.5 and 4.2%.

Table 1 Economic significance of the estimates


Conversely, although on average lockdowns in third countries do not have a significant effect on a country’s imports from China, the direct effect of Covid-19 in third countries does. Specifically, more deaths in the main trading partners of a country (excluding China) induces that country to import significantly more from China than it otherwise would. Interestingly, as Table 1 shows, the positive effect of Covid-19 incidence in the main trading partners more than offsets the own negative Covid-19 incidence effect. Putting this all together, moving each of the three variables from zero (as in 2019) to their 2020 average would imply a reduction of nearly 10% of imports from China.

The trade effects of the pandemic vary across several dimensions

Those are average effects, and there are important sources of heterogeneity across products and countries. Here is a summary of our findings:

  • The negative trade effects of the pandemic vanish when we restrict the sample to ‘medical goods’, highlighting the idiosyncratic dynamic they followed during the pandemic.
  • The negative effects are significantly mitigated for products with a higher ‘work-from-home’ share, for which a higher share of their value can be produced remotely. 
  • A weaker effect is also present for goods with a high ‘contract intensity’ – for which long-term relationships are more important – and for goods exported under ‘processing trade’.
  • The negative effects are more pronounced for ‘durable consumption goods’, but are weaker for ‘capital goods’, for which long-term planning implies a different reaction to the temporary shock due to the pandemic.
  • In ‘OECD members’, the impact of lockdown stringency reverses, indicating that it induced a smaller reduction in domestic demand than in domestic supply. 
  • The ‘fiscal policies’ that governments used to compensate workers and firms affected by the pandemic had no meaningful effect on their imports from China. 
  • There is an important ‘path-dependence’: while the trade effect of the pandemic in a country in a month is negative, incidence of the shock in previous months has a positive effect on current trade volumes. Thus, over time, contemporaneous negative effects are partially reversed. 
  • The effects were concentrated on the ‘intensive margin’. This pattern mirrors what has been found for the “great trade collapse” that followed the Global Crisis of 2008 (e.g. Behrens et al. 2013, Bricongne et al. 2012).

Other approaches

Naturally, the Covid-19 pandemic has spurred a torrent of research on its various consequences, and trade is no exception (see Liu et al. 2021 for a discussion of the main studies). A common finding is that the pandemic has negatively affected international trade flows, although the details of the results vary significantly across studies due to differences in the empirical approach, including the level of aggregation, the types of goods studied, and the data coverage.

An important distinction between our analysis and the existing empirical literature is that we consider both Covid-19 death cases and lockdown policies, while most existing research focuses on one or the other. While the Covid-19 death measure is an intuitive proxy for the impact of the pandemic, lockdowns (of various degrees of stringency) are implemented as a reaction to the pandemic, often exactly when the number of deaths is high or expected to rise soon. As a result, studying either variable in isolation can lead to misleading results. Bas et al. (2021) also use Covid-19 deaths and lockdown stringency throughout their analysis.

Another key contribution of our research is to take explicitly into account the influence of the pandemic in the rest of world on bilateral trade flows. Most existing empirical research has not considered such effects,2 but we show that they are quantitatively very important.

Going forward

The Covid-19 pandemic remains in progress and its trade impacts during 2021 and beyond may differ from its more immediate impact, as workers, firms, and governments learn how to deal with and adapt to it, and as vaccinations start to allow societies to return to their pre-pandemic modes. How these changes will affect the trade impact of the pandemic is an interesting question for future research. Another interesting extension is the study of the possible interaction between covid-related effects in importing and exporting countries.


Baldwin, R (2020), “The Greater Trade Collapse of 2020: Learnings from the 2008-09 Great Trade Collapse”,, 7 April.

Bas, M, A Fernandes and C Paunov (2021), “The Resilience of Trade to COVID-19”, mimeo.

Behrens, K, G Corcos and G Mion (2013), “Trade Crisis? What Trade Crisis?”, The Review of Economics and Statistics 95(2): 702–709.

Berthou, A and S Stumpner (2021), “Trade Under Lockdown”, mimeo.

Bricongne, J-C, L Fontagné, G Gaulier, D Taglioni and V Vicard (2012), “Firms and the Global Crisis: French Exports in the Turmoil”, Journal of international Economics 87(1): 134–146.

Espitia, A, A Mattoo, N Rocba, M Ruta and D Winkler (2021), “Trade and Covid-19: Lessons from the First Wave,”, 18 January.

Liu, X, E Ornelas and H Shi (2021), “The Trade Impact of the Covid-19 Pandemic”, CEPR Discussion Paper 16201.


1 The pandemic-related data are from the Oxford Covid-19 Government Response Tracker (OxCGRT).

2 An exception is Berthou and Stumpner (2021), who construct a similar measure for third-country stringency in a robustness specification, though not for Covid-19 incidence variables. Espitia et al. (2021) consider a different type of third-country effect, without using Covid-19 variables. 

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