## wpiea2022059-print-pdf

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---

### Key findings on delays and welfare costs
- Shipping times jumped upwards as soon as the COVID crisis hit; after a marked acceleration from end-2020, delays surpassed 1.5 days on average by December 2021.
- Global average travel times consistently hovered between 6 and 6.5 days from 2016 to 2019; the additional port delays by end-2021 amounted to a roughly 25 percent increase.
- Using estimates from the literature, the estimated additional time in transit for the average shipment in December 2021 is comparable to an ad-valorem tariff of 0.9 to 3.1 percent.
  - The midpoint of this range is approximately equal, in absolute value, to the global applied tariff reduction achieved over the 14-year period from 2003 to 2017.
- The slowdown around ports decomposes into two components:
  - About two-thirds is attributable to ships waiting longer at anchor before entering the port.
  - One-third is caused by slower cargo processing at the berths.
- There is substantial geographical variation in port delays; China and the U.S. are noted as among the most affected.

### Data and scope
- The analysis leverages a granular AIS-based seaborne trade dataset building on Cerdeiro, Komaromi, Liu and Saeed (2020).
- Raw AIS messages used: over two billion messages collected between January 1st 2015 and December 31st 2021.
- Filtered dataset coverage:
  - 1,634 seaports in 183 countries and territories.
  - 4.5 percent of all origin-destination port pairs showed direct trade activity in the 2016-2021 period.
  - Trade observed for about 28 percent of the possible bilateral country pairs.
- Port and country concentration:
  - The top 30 ports account for more than half of total ship capacity.
  - The top 100 ports manage over 75 percent of total ship capacity.
  - The top 10 countries are responsible for processing almost half of seaborne trade; the top 25 approaches 75 percent.
  - Major sea-trader countries highlighted: China, Korea, Malaysia, the US, UK, Netherlands, Germany and Belgium; Taiwan Province of China and the United Arab Emirates also host one port each among the top 10.

### Methodology for measuring port congestion
- Travel time definition:
  - Measured as the elapsed time between leaving the polygon of the origin port and leaving the polygon of the destination port.
  - Includes three components: sailing between ports, waiting at anchorage before entering the destination port, and cargo processing time at the berth.
- Aggregation and weighting:
  - Weighted average travel time between origin-destination pairs calculated monthly using ships’ deadweight tonnage as weights.
  - The weighted average interpretable as the expected time to transport a random unit of cargo between two ports in a given month, including handling at the destination.
- Baseline and delay calculation:
  - Pre-pandemic baseline travel time for each port pair defined as the 2019 average (weighted by ship capacity).
  - Additional delays are computed as deviations from the 2019 baseline and interpreted as port congestion (longer wait times at anchorage and slower cargo handling at berth).
- Decomposition:
  - Additional delays split into waiting at anchor and processing time within ports by using observed time ships spend inside port polygons to back out anchorage time (noting delineation caveats).
- Caveats and interpretation limits:
  - Indicator should be treated as a lower bound of port-level disruptions because changes in average travel times incorporate optimizing responses (e.g., rerouting to less crowded ports).
  - Limits to substitution exist for larger ships that require specific infrastructure and water depth.

### Stylized facts and interpretation
- The entire distribution of international travel times shifted right compared to pre-pandemic 2019, consistent with longer trips becoming the norm.
- Comparing travel times on the same origin-destination routes confirms that ports became more congested and ships faced more delays.
- Port congestion results from a complex combination of demand pressures (e.g., rapid demand recovery in the U.S. and other advanced economies) and supply factors (e.g., infrastructure constraints, labor shortages).
  - Many ports, especially since mid-2021, show longer wait times despite handling less cargo than pre-pandemic—suggesting supply bottlenecks beyond demand-driven congestion.
- Infrastructure upgrading is likely a necessary, but not sufficient, condition for building resilience during crises where other factors (such as labor shortages) may become binding.

### Port congestion patterns (global and country-level)
- Most severe port congestion is concentrated in the U.S. and China.
- Port congestion deteriorated and became more widespread in the second half of 2021.
- At the world level, shipping times "jumped upwards as soon as the COVID crisis hit," and after a marked acceleration from end-2020, the delays surpassed 1.5 days on average by December 2021 — or roughly a 25 percent increase.
- The estimated additional days in transit for the average shipment in December 2021 can be interpreted as a global ad-valorem tariff of 0.9 to 3.1 percent under some assumptions. The midpoint of this range is approximately equal, in absolute value, to the global applied tariff reduction achieved over the 14-year period from 2003 to 2017.

### Port-level variability and notable outliers
- Variability in delays is evident at the port level.
- The Los Angeles port is an outlier among major seaports in terms of longer wait times at anchorage and slower processing times at the berths.
- Slower turnaround times on the docks suggest not only more ships are arriving, but that supply bottlenecks, such as the stacking up of empty containers, prevent efficient processing of incoming cargo.
- Footnote evidence: the American Society of Civil Engineers assigned a B- rating to US port infrastructure and the Global Infrastructure Outlook (A G20 Initiative) estimates a $168 billion investment gap for US port infrastructure in the years to 2040.

### Supply- versus demand-driven congestion
- Port congestion is driven by a complex combination of demand pressures and supply factors.
- Most of the largest U.S. container ports show similar patterns of delays, suggesting the rebound of consumer spending is a common factor behind the congestion.
- Whether rising demand translates into congestion depends on the ports’ pre-pandemic capacity utilization rate: ports with excess capacity may accommodate more cargo without increasing wait times; ports handling less cargo with longer delays are suggestive of supply disruptions.
- For many ports, labor shortages, infrastructure weaknesses and backlogs from current or past covid restrictions likely play the decisive role.
- The measure of supply disruptions shows a deteriorating trend in the second half of 2021, with more cargo captured by the group of less productive and more congested ports.

### Port-level evidence and metrics
- Analysis based on the 150 largest seaports compares change in travel times and processed cargo to the same quarter in 2019 at the port level.
- Bubble-size in the referenced figure is proportional to the total processed cargo in each quadrant; location of bubbles within each quadrant is fixed and independent of underlying growth rates.

### Conclusion and policy implications
- Two main features emerge:
  - First, global shipping times increased sharply with the COVID crisis, with delays surpassing 1.5 days on average by December 2021 (roughly a 25 percent increase).
  - Second, not all congestion appears related to increased demand; many ports, especially since mid-2021, exhibit longer wait times despite handling less cargo than pre-pandemic.
- Infrastructure upgrading is likely a necessary, but not sufficient, condition for building resilience during a crisis where other factors (such as labor shortages) may also become binding.

*Prepared by Andras Komaromi, Diego A. Cerdeiro and Yang Liu (Section 1 of WP/22/59).*

### Section 1

### Supply Chains and Port Congestion Around the World

### Key findings on delays and welfare costs
- Shipping times jumped upwards as soon as the COVID crisis hit; after a marked acceleration from end-2020, delays surpassed 1.5 days on average by December 2021.
- Global average travel times consistently hovered between 6 and 6.5 days from 2016 to 2019; the additional port delays by end-2021 amounted to a roughly 25 percent increase.
- Using estimates from the literature, the estimated additional time in transit for the average shipment in December 2021 is comparable to an ad-valorem tariff of 0.9 to 3.1 percent.
  - The midpoint of this range is approximately equal, in absolute value, to the global applied tariff reduction achieved over the 14-year period from 2003 to 2017.
- The slowdown around ports decomposes into two components:
  - About two-thirds is attributable to ships waiting longer at anchor before entering the port.
  - One-third is caused by slower cargo processing at the berths.
- There is substantial geographical variation in port delays; China and the U.S. are noted as among the most affected.

### Data and scope
- The analysis leverages a granular AIS-based seaborne trade dataset building on Cerdeiro, Komaromi, Liu and Saeed (2020).
- Raw AIS messages used: over two billion messages collected between January 1st 2015 and December 31st 2021.
- Filtered dataset coverage:
  - 1,634 seaports in 183 countries and territories.
  - 4.5 percent of all origin-destination port pairs showed direct trade activity in the 2016-2021 period.
  - Trade observed for about 28 percent of the possible bilateral country pairs.
- Port and country concentration:
  - The top 30 ports account for more than half of total ship capacity.
  - The top 100 ports manage over 75 percent of total ship capacity.
  - The top 10 countries are responsible for processing almost half of seaborne trade; the top 25 approaches 75 percent.
  - Major sea-trader countries highlighted: China, Korea, Malaysia, the US, UK, Netherlands, Germany and Belgium; Taiwan Province of China and the United Arab Emirates also host one port each among the top 10.

### Methodology for measuring port congestion
- Travel time definition:
  - Measured as the elapsed time between leaving the polygon of the origin port and leaving the polygon of the destination port.
  - Includes three components: sailing between ports, waiting at anchorage before entering the destination port, and cargo processing time at the berth.
- Aggregation and weighting:
  - Weighted average travel time between origin-destination pairs calculated monthly using ships’ deadweight tonnage as weights.
  - The weighted average interpretable as the expected time to transport a random unit of cargo between two ports in a given month, including handling at the destination.
- Baseline and delay calculation:
  - Pre-pandemic baseline travel time for each port pair defined as the 2019 average (weighted by ship capacity).
  - Additional delays are computed as deviations from the 2019 baseline and interpreted as port congestion (longer wait times at anchorage and slower cargo handling at berth).
- Decomposition:
  - Additional delays split into waiting at anchor and processing time within ports by using observed time ships spend inside port polygons to back out anchorage time (noting delineation caveats).
- Caveats and interpretation limits:
  - Indicator should be treated as a lower bound of port-level disruptions because changes in average travel times incorporate optimizing responses (e.g., rerouting to less crowded ports).
  - Limits to substitution exist for larger ships that require specific infrastructure and water depth.

### Stylized facts and interpretation
- The entire distribution of international travel times shifted right compared to pre-pandemic 2019, consistent with longer trips becoming the norm.
- Comparing travel times on the same origin-destination routes confirms that ports became more congested and ships faced more delays.
- Port congestion results from a complex combination of demand pressures (e.g., rapid demand recovery in the U.S. and other advanced economies) and supply factors (e.g., infrastructure constraints, labor shortages).
  - Many ports, especially since mid-2021, show longer wait times despite handling less cargo than pre-pandemic—suggesting supply bottlenecks beyond demand-driven congestion.
- Infrastructure upgrading is likely a necessary, but not sufficient, condition for building resilience during crises where other factors (such as labor shortages) may become binding.

*Prepared by Andras Komaromi, Diego A. Cerdeiro and Yang Liu (Section 1 of WP/22/59).*

### Section 2

### wpiea2022059-print-pdf - Section 2

### Port congestion patterns (global and country-level)
- Most severe port congestion is concentrated in the U.S. and China.
- Port congestion deteriorated and became more widespread in the second half of 2021.
- At the world level, shipping times "jumped upwards as soon as the COVID crisis hit," and after a marked acceleration from end-2020, the delays surpassed 1.5 days on average by December 2021 — or roughly a 25 percent increase.
- The estimated additional days in transit for the average shipment in December 2021 can be interpreted as a global ad-valorem tariff of 0.9 to 3.1 percent under some assumptions. The midpoint of this range is approximately equal, in absolute value, to the global applied tariff reduction achieved over the 14-year period from 2003 to 2017.

### Port-level variability and notable outliers
- Variability in delays is evident at the port level.
- The Los Angeles port is an outlier among major seaports in terms of longer wait times at anchorage and slower processing times at the berths.
- Slower turnaround times on the docks suggest not only more ships are arriving, but that supply bottlenecks, such as the stacking up of empty containers, prevent efficient processing of incoming cargo.
- Footnote evidence: the American Society of Civil Engineers assigned a B- rating to US port infrastructure and the Global Infrastructure Outlook (A G20 Initiative) estimates a $168 billion investment gap for US port infrastructure in the years to 2040.

### Supply- versus demand-driven congestion
- Port congestion is driven by a complex combination of demand pressures and supply factors.
- Most of the largest U.S. container ports show similar patterns of delays, suggesting the rebound of consumer spending is a common factor behind the congestion.
- Whether rising demand translates into congestion depends on the ports’ pre-pandemic capacity utilization rate: ports with excess capacity may accommodate more cargo without increasing wait times; ports handling less cargo with longer delays are suggestive of supply disruptions.
- For many ports, labor shortages, infrastructure weaknesses and backlogs from current or past covid restrictions likely play the decisive role.
- The measure of supply disruptions shows a deteriorating trend in the second half of 2021, with more cargo captured by the group of less productive and more congested ports.

### Port-level evidence and metrics
- Analysis based on the 150 largest seaports compares change in travel times and processed cargo to the same quarter in 2019 at the port level.
- Bubble-size in the referenced figure is proportional to the total processed cargo in each quadrant; location of bubbles within each quadrant is fixed and independent of underlying growth rates.

### Conclusion and policy implications
- Two main features emerge:
  - First, global shipping times increased sharply with the COVID crisis, with delays surpassing 1.5 days on average by December 2021 (roughly a 25 percent increase).
  - Second, not all congestion appears related to increased demand; many ports, especially since mid-2021, exhibit longer wait times despite handling less cargo than pre-pandemic.
- Infrastructure upgrading is likely a necessary, but not sufficient, condition for building resilience during a crisis where other factors (such as labor shortages) may also become binding.

*IMF WORKING PAPERS Supply Chains and Port Congestion Around the World, Working Paper No. WP/2022/059 — Section 2*

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_Source: https://www.imf.org/-/media/files/publications/wp/2022/english/wpiea2022059-print-pdf.pdf_
