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Supply chain disruptions have been a defining feature of the global economy since 2020. Geopolitical risks, diplomatic tensions, regional instability, and environmental risks are exposing critical vulnerabilities in global sourcing models. These crises underscore that import dependencies, especially on a single partner, can be a major source of fragility and lead to large macroeconomic effects through supply chains (Alessandria et al. 2023). In response, major economies have implemented strategic resilience frameworks, such as the US Inflation Reduction Act, the EU’s Net-Zero Industry Act, and the upcoming Industrial Accelerator Act. The relevance and design of such economic policies require identifying trade vulnerabilities and a deeper understanding of how firms hedge against supply-chain risk.

In response to this supply risk, firms primarily adopt two main strategies: building strategic buffer stocks and diversifying sourcing origins. There is mounting empirical evidence that these strategies are often adopted ex-post. Firms exposed to supply chain shocks adapt by revising their inventory strategies (Zhang and Doan 2023), diversifying their supply sources (Castro-Vincenzi et al. 2024), or even relocating production (Castro-Vincenzi 2024, Balboni et al. 2025).

In turn, documenting the recourse to those strategies ex-ante informs about the exposure and robustness of sourcing. In a recent paper (Lafrogne-Joussier 2025), I use comprehensive firm-level data on stockpiling and sourcing diversification to document the extent to which French manufacturing firms utilise both strategies. By focusing on importers — where direct exposure to international shocks is most acute — this research demonstrates that accounting for inventories significantly alters our assessment of trade vulnerabilities.

Inventories and diversification practices differ widely across firms

In the manufacturing industry, the median firm holds enough stock to sustain production for over two months (63 days) in the event of a total supply cutoff. This median masks vast disparities: the top 10% of firms hold at least five months of stock, compared to a maximum of six days for the bottom 10% — a significant 7.5% of importing firms report zero inventories of inputs.

Practices vary by sector, with a median stock of nearly 114 days in pharmaceuticals versus 37 days in the agri-food sector (Figure 1a). These disparities are not merely a function of input perishability; even within narrowly defined industries, firm-level idiosyncrasies remain considerable.

Consistent with previous literature, I show that the level of inventories at the firm-level is increasing in the share of imported inputs (Alessandria et al. 2010) and the geographical distance inputs travel to reach France (Carreras-Valle 2024). While the former is typically attributed to fixed costs per shipment, the latter is intrinsically linked to delivery-time volatility. This reinforces the conceptualisation of inventories as a critical buffer against exogenous supply risk.

Figure 1 Inventories and diversification across and within industries

A) Inventory ratio

B) Diversification

Note: This figure displays the median, p25, and p75 within two-digit industries of the number of days of inventories of inputs (Panel A) and of the average number of sourcing countries per product, called diversification (Panel B). The sample contains one data point per importing manufacturing firm in France, per year, between 2012 and 2023.

Using individual customs data, I measure the diversification of sourcing of French importers as the (weighted) average number of origin countries per imported input.

Much like inventory management, diversification strategies exhibit significant variance across firms: a quarter of manufacturing importers source each product from a single foreign origin on average, whereas the most diversified decile sources from more than four countries. The automotive industry appears as the most diversified sector, with the median firm importing inputs from an average of over 2.3 countries (Figure 1b). In contrast, in the metallurgy and apparel sectors, the median firm relies on a single foreign source for its entire imported input basket.

Two factors influencing this variability across firms are worth discussing. First, some of these differences are due to economies of scale in importing: diversification increases with the number of imported inputs. Second, diversification is constrained by the underlying supply architecture of specific inputs. Firms are significantly more likely to diversify when the product in question is supplied by a larger number of countries globally.

Building up inventories and diversifying supply sources are substitute strategies

A central finding of this paper is that diversification and stockpiling are substitutes. While both aim to reduce production volatility, they operate through distinct mechanisms: diversification mitigates upstream risk, while inventories buffer against realised shocks.

Empirically, geographic diversification significantly stabilises import flows. Firms sourcing from a single country exhibit a dispersion of monthly imports almost three times higher than that of those sourcing from over eight countries. Conversely, inventories preserve operational continuity during acute supply stress. For instance, the shortage of Chinese inputs due to the early lockdown in 2020 did not significantly affect French firms sourcing from China that held high levels of inventories (Lafrogne-Joussier et al. 2022).

A robust negative correlation emerges: as inventory intensity increases, geographic diversification declines. Firms with one month of stock average 2.5 origin countries, whereas the top 5% (with 240 days of autonomy) average fewer than two. This trade-off persists when controlling for sectoral fixed effects and within-firm longitudinal variation.

The substitutability between these strategies is partly driven by diverging cost structures.

Diversification entails significant fixed costs — such as supplier identification and contract negotiation — which are proportionally lower for larger firms. Furthermore, greater market power allows large firms to secure higher supplier reliability, reducing the need for precautionary holdings. Empirically, diversification scales with firm size: the smallest firms average approximately one origin country per product, whereas the top 5% source from more than five (Figure 2).

Conversely, stockpiling intensity decreases with firm size. While the smallest 5% of firms maintain an average of 96 days of inventory, the largest 5% hold only 53 days. This is consistent with the theory that inventory costs — including storage and management — are convex (Ramey and West, 1999), making large-scale stockpiling disproportionately expensive for high-volume firms.

Figure 2 Inventories and diversification along firm size

Note: This figure displays a binscatter of the number of days of inventories of inputs on firms’ (log of) annual sales, in black, and a binscatter of diversification on firms’ (log of) annual sales, in grey. The pattern also holds after removing industry-year and firm fixed effects, and for various measures of firm size (number of employees, value-added, labour productivity). The sample contains one data point per importing manufacturing firm in France, per year, between 2012 and 2023.

Refining trade vulnerabilities assessments: The role of stocks

Securing international supply chains is a major economic policy goal, requiring the identification of ‘vulnerable’ products whose supply is particularly fragile. Existing analyses often retain the concentration of sourcing origins as a measure of exposure to international supply shocks. As less diversified firms may compensate with sufficient inventory to manage short-term disruptions, taking inventories into account may reduce the number of vulnerable products.

I consider an input as vulnerable if it exhibits three combined characteristics: low diversification, low diversifiability, and low stocking.

1. Low diversification: Imported from a small number of countries. Out of 3,175 inputs, 62 are imported from just one country, 624 from two countries or less.
2. Low diversifiability: Global production is highly concentrated (e.g. HHI > 0.25), limiting alternatives (the case for 496 inputs).
3. Low stocking: Imported by firms with low average stock levels. Out of 3,175 inputs, 1,839 are imported by firms with less than one month of inventories of inputs, meaning that any disruption exceeding one month would immediately propagate through the domestic economy.

By combining the first two criteria (low diversification and concentrated global supply), 174 inputs appear at risk. However, accounting for inventory buffers reduces this figure to 79 highly vulnerable products. Changing the thresholds on the first two criteria does not change the effect of taking inventories into account: around half of them are sufficiently stockpiled (more than one month). 

These highly vulnerable products account for only 0.2% of the total value of input imports, but a supply disruption of some of them may have larger effects. Some of the 79 vulnerable products are upstream inputs, like several minerals such as cobalt (essential for battery manufacturing), whose disruption may ripple downstream along the supply chain. A shortage of some others may create large non-economic effects, as the largest group of inputs among the 79 is chemical products, including organic chemical products vital for the pharmaceutical and cosmetic industries.

Figure 3 Number of trade vulnerabilities

Note: This figure displays the number of imported inputs according to the vulnerability criteria described in the text. Statistics are computed on imports over the five years between 2015 and 2019, at the HS6-level, and restricted to intermediate products, according to the BEC classification.

Towards resilience policies

Integrating inventory data significantly refines trade vulnerability assessments. However, while stockpiling mitigates transitory shocks, it is an ineffective hedge against protracted disruptions, such as permanent shifts in trade policy or geopolitical alignments.

More generally, it remains unclear whether current private incentives for supply resilience levels align with public resilience goals. Since there is no established benchmark for optimal stocks or optimal diversification, further research is required to quantify the wedge between private incentives and public welfare. Last, the high heterogeneity in supply-chain risk management practices uncovered in this column suggests that effective resilience policies will not be uniform across firms.

References

Alessandria, G, J P Kaboski and V Midrigan (2010), “Inventories, lumpy trade, and large devaluations”, American Economic Review 100(5): 2304-2339.

Alessandria, G, S Y Khan, A Khederlarian, C Mix and K Ruhl (2023), “The aggregate effects of local and global supply chain disruptions, 2020-2022”, VoxEU.org, 12 March.

Balboni, C, J Boehm and M Waseem (2025), “Firm adaptation and production networks: Structural evidence from extreme weather events in Pakistan”, Mimeo.

Carreras-Valle, M-J (2024), “Increasing inventories: The role of delivery times”, Technical report, Penn State University.

Castro-Vincenzi, J (2024), “Climate hazards and resilience in the global car industry”, Mimeo.

Castro-Vincenzi, J, G Khanna, N Morales and N Pandalai-Nayar (2024), “Weathering the storm: Supply chains and climate risk”, NBER Working Paper 32218.

Lafrogne-Joussier, R (2025), “Inventories, Diversification, and Trade Vulnerabilities”, Insee Working Paper 2025-22.

Lafrogne-Joussier, R, J Martin and I Mejean (2022), “Supply chain disruptions and mitigation strategies”, VoxEU.org, 5 February.

Ramey, V A and K D West (1999), “Inventories”, Handbook of Macroeconomics 1: 863-923.

Zhang, H and T T H Doan (2023), “From just-in-time to just-in-case: Global sourcing and firm inventory after the pandemic”, VoxEU.org, 1 September.

Since the rise of US–China trade tensions, there has been a growing debate on the impact of rising trade barriers on global and bilateral trade patterns (Aiyar and Ilyina 2023, Aiyar et al. 2023, Alfaro and Chor 2023, Freund et al. 2023, Freund et al. 2024) against a backdrop of the public debate on deglobalisation (Baldwin 2022). Geoeconomic fragmentation poses losses to all countries in the medium-to-long term, but may lead to different trade dynamics among countries in the short term. It has been argued that ‘connector’ countries benefit from bridging the gap between trade blocs – for example, by increasing exports to the US as they substitute for declining US sourcing from China while at the same time increasing imports from China (Fajgelbaum et al. 2023, Fajgelbaum et al. 2024, Freund et al. 2023, Freund et al. 2024, Gopinath et al. 2025). However, it is not clear (a) whether such connector countries do indeed serve as bridges, as the increasing imports from China may reflect other factors; and (b) even if such ‘bridging the gap’ effects exist, through which channels they operate. Two possible channels are:

• Trade reallocation: connector countries produce more goods domestically to export to the US – with rising domestic value added – as the US shifts away from China, likely using intermediate inputs imported from China.
• Trade rerouting: connector countries serve as a one‑stop place for Chinese exports to the US – with minimal to no domestic value added, in the extreme case through transshipment – to circumvent trade barriers.

Separating these channels is important. Trade reallocation could benefit the domestic economy at least in the short term as it increases domestic production for exports. Conversely, trade rerouting involves minimal or no domestic production activities and may result in harmful countervailing trade restrictions. In a recent paper (Schulze and Xin 2025), we provide a nuanced assessment of the changing trade patterns during 2018 and 2022 by disentangling these two channels and examining the spillover consequences of the higher US tariffs on China in 2018 for a sample of six Asian emerging markets (India, Indonesia, Malaysia, Philippines, Thailand, and Vietnam).

Trade reallocation in some countries, but no evidence of trade rerouting on a significant scale

We first document that the positive correlation between these countries’ imports from China and exports to the US may reflect other forces at play, such as Chinese supply chain reconfiguration and growing domestic markets, and not necessarily their connector roles in bridging the gap between China and the US.

We then leverage the Eora global supply chain database, which captures global production linkages, to construct two value-added measures of each country’s exports to the US between 1990 and 2022: (1) the share of domestic value added, and (2) the share of Chinese value added. We use a synthetic control approach to estimate the effect of US-China trade tensions on these measures, especially for strategic sectors that have been most affected by the US tariffs on Chinese exports.
Compared to the synthetic counterfactual, a higher share of domestic value added in a country’s exports to the US would suggest evidence of trade reallocation, i.e. domestic production expanding and more domestic content being embedded in the country’s exports to the US. On the other hand, a lower share of Chinese value added in a country’s exports to the US would suggest no evidence of trade rerouting on a significant scale.

Vietnam appears to have benefited from the trade reallocation effect during 2018-2022 – significantly increasing its domestic value added (Figure 1) and reducing Chinese value added in its strategic sector exports to the US – rather than trade rerouting from China. Specifically, Vietnam saw statistically significant increases in the share of domestic value added in its exports to the US (6 and 7 percentage points higher than its synthetic counterfactual in 2018 for the “electrical and machinery” sector and “petroleum, chemical and non-metallic mineral products” sectors, respectively, and 10 and 12 percentage points higher in 2022). This suggests that Vietnam has increased domestic production for its strategic sectors’ exports and has thus been able to embed more domestic content in its exports to the US. On the other hand, Vietnam saw a statistically significant decline in the share of Chinese value added in its strategic sectors’ exports to the US, suggesting no evidence of trade rerouting from China to the US on a significant scale.

Figure 1 Estimated effect on the share of domestic value added in the country’s exports to the US: Electrical and machinery (percentage points)

Notes: For each country, the figure plots the estimated effect on the share of domestic value added in the country’s exports to the US (the blue lines) and the 10th − 90th percentile range of the placebo test distribution (the grey areas).
Sources: The Eora Global Supply Chain Database (Lenzen et al. 2012, 2013); Aslam et al. (2017); authors’ calculations.

Moreover, Vietnam has been able to export more domestic content not only to the US but also globally (Figure 2), though the effects on the latter are slightly smaller and take longer to become statistically significant. This suggests that, beyond increasing its domestic content in bilateral exports to the US, Vietnam managed to expand its domestic production capacity to capture a larger share in the global market.

Figure 2 Share of domestic value added in Vietnam’s exports to the world: Electrical and machinery (percentage points)

Notes: Panel (a) plot the actual (the blue line) and the synthetic counterfactual (the grey line) share of domestic value added in Vietnam’s exports to the world, and Panel (b) plots the estimated effect (the blue lines) and the 10th − 90th percentile range of the placebo test distribution (the grey areas).
Sources: The Eora Global Supply Chain Database (Lenzen et al. 2012, 2013); Aslam et al. (2017); authors’ calculations.

Trade reallocation in Vietnam is partly linked to Chinese firms relocating through FDI

We extend our analysis to foreign direct investment (FDI) by examining the cumulative number of greenfield FDI projects that commit Chinese capital to Vietnam. Vietnam attracted more greenfield FDI projects in strategic sectors from China after 2018 (Figure 3), which has likely contributed to the scaling up of domestic production of its exports: Chinese firms have relocated their production – or accelerated a relocation process that started before due to higher domestic labour costs – to Vietnam against the backdrop of increasing US tariffs on China.

Figure 3 Cumulative number of greenfield FDI projects that commit Chinese capital to Vietnam: Electrical and machinery  

Notes: Panel (a) plot the actual (the blue line) and the synthetic counterfactual (the grey line) of the cumulative number of greenfield FDI projects that commit Chinese capital to Vietnam. Panel (b) plots the estimated effect on the cumulative number of greenfield FDI projects that commit Chinese capital to Vietnam for electrical and machinery sector since 2003 (the blue lines) and the 10th − 90th percentile range of the placebo test distribution (the grey areas).
Sources: The Orbis Cross-border Investment Database and authors’ calculations.

Taken together, Vietnam appears to have benefited from the trade reallocation effect by increasing its domestic production – partly supported by Chinese FDI but also by its favourable structural characteristics – and embedding more domestic content in its exports to the US and the rest of the world. Meanwhile, the evidence suggests that Vietnam has not served as a one‑stop place allowing China to reroute its exports to the US on a significant scale. As for the other five Asian countries, the impacts of the US–China trade tensions are elusive.

Conclusion

We provide a nuanced assessment of changing global trade patterns against the backdrop of increasing geoeconomic fragmentation, by zooming in on connector countries, delving into the value‑added trade, and distinguishing between trade reallocation and trade rerouting effects. Some countries, such as Vietnam, have experienced trade reallocation rather than trade rerouting, supported by rising domestic production and stronger inward FDI. Despite potential short-term gains, trade reallocation increases connector countries’ vulnerability to geoeconomic fragmentation, with losses for all countries in the long run.

Authors’ note: The views expressed in this column are entirely those of the authors and do not necessarily represent the views of the IMF, its Executive Board, or IMF management. 

References

Alfaro, L, and D Chor (2023), “A perspective on the great reallocation of global supply chains”, VoxEU.org, September.

Alfaro, L and D Chor (2023), “Global Supply Chains: The Looming ‘Great Reallocation’”, NBER Working Paper No. 31661.

Aiyar, S and A Ilyina (2023), “Geo-economic fragmentation: What it means for multilateralism”, VoxEU.org, March.

Aiyar, S, J Chen, C Ebeke, R Garcia-Saltos, T Gudmundsson, A Ilyina, A Kangur, S Rodriguez, M Ruta, T Schulze, J Trevino, T Kunaratskul and G Soderberg (2023), “Geoeconomic Fragmentation and the Future of Multilateralism”, IMF Staff Discussion Note No. SDN/2023/01.

Aslam, A, N Novta, and F Rodrigues-Bastos (2017), “Calculating Trade in Value Added”, IMF Working Paper No. 2017/178.

Baldwin, R (2022), “The Peak Globalisation Myth,” VoxEU.org.

Fajgelbaum, P, P Goldberg, P Kennedy, A Khandelwal, and D Taglioni (2023), “The ‘bystander effect’ of the US-China trade war”, VoxEU.org, June.

Fajgelbaum, P, P Goldberg, P Kennedy, A Khandelwal, and D Taglioni (2024), “The US-China trade war and global reallocations”, American Economic Review: Insights 6(2): 295-312.

Freund, C, A Mattoo, A Mulabdic, and M Ruta (2023), “US-China decoupling: Rhetoric and reality”, VoxEU.org, August.

Freund, C, A Mattoo, A Mulabdic, and M Ruta (2024), “Is US trade policy reshaping global supply chains?”, Journal of International Economics 152, 104011.

Gaulier, G and S Zignago (2010), “Baci: international trade database at the product-level (the 1994-2007 version)”.

Gopinath, G, P Gourinchas, A Presbitero, and P Topalova (2025), “Changing global linkages: A new Cold War?”, Journal of International Economics 153, 104042.

IMF – International Monetary Fund (2023), 2023 April World Economic Outlook.

Lenzen, M, K Kanemoto, D Moran, and A Geschke (2012), “Mapping the structure of the world economy”, Environmental Science & Technology 46(15): 8374-8381.

Lenzen, M, D Moran, K Kanemoto, and A Geschke (2013), “Building Eora: a global multi-region input–output database at high country and sector resolution”, Economic Systems Research 25(1): 20-49.

Schulze, T and W Xin (2025). “Demystifying Trade Patterns in a Fragmenting World”, IMF Working Paper No. 2025/129.