Covid travel restrictions limited movement of people but also made cross-border goods trade more difficult. Did this contribute to the fall in global goods trade during the pandemic (Ornelas et al. 2021), and if so by how much? In a recent paper (Lewis 2026) using a structural gravity model (Yotov et al. 2016) on global trade flows with domestic trade, I show that a full closure reduced trade for a typical country pair by around 19%, implying a peak hit to global trade of about 23% in 2020Q2. Hits were larger for nearby partners, and were concentrated in road and air freight, with seaborne trade unaffected. These differences explain why some countries could close borders with smaller trade hits than others. Trade rebounded as restrictions eased, suggesting no lasting scarring.

In the first quarter of 2020, governments tightened borders at unprecedented speed, introducing testing, quarantine, and, in some cases, full closures. Global goods trade also fell sharply (IMF 2022). Was that fall purely down to contracting global activity, or did border frictions rise, making it more costly to trade internationally? In a recent paper, I answer this using a gravity framework that includes domestic trade flows and time-varying exporter and importer controls, allowing me to isolate the role of the ‘extra’ cost of selling abroad versus at home: the so-called ‘border friction’, which controls for the effect of reduced supply capacity in the exporting country and reduced demand in the importing country. I find that the rise in border frictions was substantial, and implied a significant hit to global trade, over and above that which the generalised contraction in economic activity would have implied. To my knowledge, this is the first attempt to explore this issue on cross-country data over the full pandemic period (and beyond) using a multi-country gravity model.

Why might travel restrictions affect goods trade?

Travel restrictions target people, but goods trade depends on people crossing borders too. Testing, quarantine, and entry bans add paperwork, cause delays, and increase uncertainty, all of which might raise the cost of trading across borders relative to selling domestically and thus reduce cross-border trade (OECD 2020). Effects also differ by transport mode: road freight is exposed to queues (Financial Times 2020) and checks at crossings (WTO 2021); air freight lost capacity when passenger flights were cancelled, reducing ‘belly cargo’ (USITC 2020); and shipping faced stricter port and crew protocols, though containerised cargo could often keep moving with limited contact (UNCTAD 2020).

To quantify the trade impact, I adopt a key innovation from the recent gravity literature — including domestic trade, that is, goods produced at home which are consumed domestically (proxied by GDP minus exports) alongside international trade — to uncover changes in frictions to moving goods across borders (Yotov 2012, Yotov et al. 2016). By comparing how a country’s cross-border trade moved relative to its domestic trade, I can isolate changes in the extra costs of trading across borders.

Econometrically, the model is estimated with the standard Poisson pseudo-maximum likelihood (PPML) estimator (Santos Silva and Tenreyro 2006) and a rich set of fixed effects. Exporter-by-quarter and importer-by-quarter fixed effects absorb country-specific shocks to supply and demand (including domestic lockdown effects). Country-pair fixed effects capture time-invariant bilateral factors (distance, common language, and so on). Finally, seasonal border-by-quarter-of-year dummies remove regular seasonality in cross-border relative to domestic trade. The resulting border coefficients can be read as changes in border frictions relative to 2019.

How did border frictions evolve during the pandemic?

To estimate how border frictions moved through the pandemic, I allow the ‘border effect’, the gap between trading domestically and trading across an international border, to vary quarter by quarter by interacting a cross-border indicator with time dummies. These time-specific border coefficients are plotted in Figure 1 below.

Figure 1 Border coefficients over time

Before Covid, estimated border frictions were broadly stable. When the pandemic hit, the model identifies a sharp, temporary increase in the ‘border cost’ for selling abroad rather than domestically. At its trough in 2020 Q2, the estimated border effect implies around a 27% decline in international trade over and above what would be predicted by the collapse in economic activity. The border friction then fell back as restrictions were relaxed, and the estimates turned temporarily positive in late 2021, implying an ‘overshoot’, as firms caught up on delayed shipments and rebuilt inventories.

How big was the trade impact of travel restrictions?

I then relate this time variation in border frictions to international travel restrictions, as captured by the Oxford Covid-19 Government Response Tracker (Hale et al. 2021), which ranges from no travel restrictions up to full border closure. Including this as an explanatory variable in the gravity equation shows that even after controlling for the broader pandemic shock, tighter travel restrictions are associated with lower international trade.

I then interact travel restrictions with bilateral distance. This tests whether restrictions change trade costs mainly through a distance-invariant ‘border’ component (paperwork, checks, and uncertainty at the border) rather than the per-kilometre cost of moving goods. If so, we would expect larger percentage trade losses for nearby partners, which is exactly what the estimates show. The central estimate implies that moving to a full closure for an entire quarter reduced trade between a typical country pair by around 19%.

Importantly, the effect varies strongly across distance. The trade hit is larger for geographically closer trading relationships. That pattern fits a simple intuition that border frictions are distance-invariant, while transport costs rise with kilometres travelled. When two countries are close, distance-related costs are small, so any increase in border friction is a large percentage increase in total trade costs, and trade falls by more. In the estimates, a full closure reduces trade by roughly 27% at the 10th percentile of trading distances (around 450 km), but by around 11% at the 90th percentile (around 11,500 km).

Figure 2 Effect of border closures by distance

How did transport mode shape the trade hit?

Distance is only part of the story: how goods travel also matters. To explore this, I draw on UNCTAD data on the value of trade carried by sea, air, road, rail, and other modes. Because the transport data are annual and do not cover domestic trade, I calculate a pre-pandemic exposure measure: for each country pair, how intensively their 2019 trade relied on each mode.

The results are striking. Once I allow the effect of restrictions to vary with transport exposure, the trade impacts are concentrated in road and air (and the small ‘other’ category). In contrast, there is no evidence that seaborne trade was significantly reduced by travel restrictions, and rail effects are also insignificant. This helps reconcile seemingly different national experiences during Covid: for an island economy where most trade arrives by ship, even strict border measures need not translate into a large hit to goods trade, while land-transport-based economies heavily reliant on trucking can face much larger disruption.

Putting distance and transport exposure together generates large cross-country differences in the implied trade cost of closing borders. The paper calculates the hit at country level (Figure 3). The blue dots below show the hit to air, road, and other flows given by applying the coefficients on travel restrictions and the interaction between travel restrictions and distance. By definition, the only source of heterogeneity here is differences in average distance travelled. The red dots then show the hit to total flows: this is the hit in blue dots times exposure to air, road, and other flows, which allows differences in transport mode to play a role. This shows that the implied hit to total trade from a full closure ranges from low single digits for some sea-reliant economies with distant partners, such as Australia and New Zealand, to close to 30% for the most exposed countries, such as Slovakia or Bosnia. This demonstrates how some countries were able to close their borders at a much lower cost than others.

Figure 3 Estimated hit from border closures by country

Did restrictions leave lasting scars on trade?

Did temporary border disruptions permanently reshape trade relationships, for example by causing firms to switch suppliers or breaking logistics links? I test this by including backlog variables that capture earlier restrictions. The evidence points away from long-run scarring. Instead, once restrictions begin to ease, trade tends to rebound strongly and temporarily overshoot, consistent with catch-up trade that makes up for earlier shortfalls. Aggregating the estimates across country pairs implies a peak hit to global goods trade of around 23% in 2020 Q2.

Figure 4 Dynamic effects

What are the broader conclusions?

Three broad lessons stand out. First, even when goods are formally exempt, restricting cross-border movement of people can raise the relative cost of selling abroad. This can happen in ways that look like a classic border friction. Second, incidence is uneven. The same policy can have very different trade consequences depending on geography and logistics: restrictions matter more for nearby trading partners, consistent with a distance-invariant border cost making up a larger share of total trade costs at short distances, and road- and air-reliant supply chains are particularly exposed. Third, temporary disruption need not mean permanent damage. Trade recovered strongly once restrictions eased, with evidence of catch-up rather than scarring.

References

Financial Times (2020), “Europe’s borders clog up as coronavirus tests supply chains”, 17 March.

Hale, T, N Angrist, R Goldszmidt, B Kira, A Petherick, T Phillips, S Webster, E Cameron-Blake, L Hallas, S Majumdar and H Tatlow (2021), “A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)”, Nature Human Behaviour 5: 529–538.

IMF – International Monetary Fund (2022), World Economic Outlook, April 2022.

Lewis, J (2026), “Travel Restrictions are Border Frictions”, Bank of England Staff Working Paper 1191.

Ornelas, E, H Shi and X Liu (2021), “The 2020 trade impact of the COVID-19 pandemic”, VoxEU.org, 9 June.

OECD – Organisation for Economic Co-operation and Development (2020), “Trade facilitation in the time of COVID-19: The challenges and opportunities for international trade”, 18 November.

Santos Silva, J M C and S Tenreyro (2006), “The log of gravity”, Review of Economics and Statistics 88(4): 641–658.

UNCTAD – United Nations Conference on Trade and Development (2020), “COVID-19 and maritime transport: Impact and responses”.

USITC – United States International Trade Commission (2020), “Air freight and the COVID-19 pandemic”.

WTO – World Trade Organization (2021), “Improving trade outcomes for landlocked developing countries”, Chapter 2.

Yotov, Y V (2012), “A simple solution to the distance puzzle in international trade”, Economics Letters 117(3): 794–798.

Yotov, Y V, R Piermartini, J-A Monteiro and M Larch (2016), An advanced guide to trade policy analysis: The structural gravity model, Geneva: World Trade Organization and United Nations Conference on Trade and Development.