News# 53 - bongdaso v causal effects and policy implications of global supply chain disruptions

Supply chain disruptions cause large macroeconomic adjustments and challenge bongdaso v effectiveness of stabilisation policies. This column provides a new index of global supply chain disruption, presents a new model to identify bongdaso v causal effect of global supply chain shocks on aggregate variables, and analyses bongdaso v implications for bongdaso v effectiveness of monetary policy. bongdaso v authors document how supply chain shocks drove inflation during 2021 but, in 2022, traditional demand and supply shocks also played an important role in explaining inflation. Monetary policy is more effective in taming inflation after a global supply chain shock than in regular circumstances.

bongdaso v world economy is organised around an intricate global supply chain. Any sudden disturbance to it, such as those triggered by war, geopolitical conflicts, or bongdaso v recent COVID-19 pandemic, might have large consequences for output, inflation, and unemployment (Pandalai-Nayar et al. 2020, Alessandria et al. 2023, di Giovanni et al. 2023, Clayton et al. 2024). Furthermore, global supply chain shocks might also change bongdaso v trade-offs faced by stabilisation policies (Benigno and Eggertsson 2023).

Measuring bongdaso v causal effect of a global supply chain shock, and designing optimal policy responses to it, is challenging. Traditional metrics based on shipping costs or information from surveys are problematic since they reflect endogenous movements in bongdaso v demand for goods or expectations that might be unrelated to supply chain disruptions. Besides, even after measuring bongdaso v shock, researchers need a theoretical framework to formulate compelling identification assumptions required for causal analysis. Unfortunately, there is no standard theory that encompasses bongdaso v simultaneous rise in spare productive capacity – resulting from disruptions to bongdaso v supply chain – along with bongdaso v shortage of goods and bongdaso v scarcity of supply in bongdaso v retail market that exerts upward pressure on prices.

In a recent paper (Bai et al. 2024), we address those issues by developing a new index of global supply-chain disturbances using real-time satellite data of container ships at major ports worldwide collected by bongdaso v Automatic Identification System (AIS) mandated by bongdaso v International Maritime Organization. Together with a novel theoretical model, we link spare productive capacity with shortages in retail supplies, as well as bongdaso v responses of output and prices to supply chain disturbances. Using our new data and guided by our theory, we shed light on bongdaso v causal effects of supply chain disruptions on aggregate outcomes and bongdaso v implications for bongdaso v effectiveness of monetary policy.

Measuring global supply chain disruptions

Building on established results in maritime economics (Transportation Research Board Executive Committee 2006), we measure global supply chain disruptions by congestion at ports. Since container shipping accounts for approximately 60% of bongdaso v value of seaborne trade, even minor congestion, as limited to one or two days delay, cause significant disruption (UNCTAD 2019).

bongdaso v organisation of container shipping, based on fixed routes and predetermined timetables regulated by long-term contracts, 1 allows us to achieve a powerful identification of supply chain disturbances. Since bongdaso v terms and timing of container ships are fixed several months in advance and independent from standard demand and supply forces, any substantial delay – and bongdaso v resulting congestion at ports – is evidence of genuine shocks to bongdaso v supply chain. Thus, our new measure provides an accurate measurement of supply-chain disturbances.

We quantify congestion at ports by developing a machine-learning algorithm that processes bongdaso v location, speed, and heading of containers at ports. This algorithm enables us to accurately quantify bongdaso v congestion and delays at different ports around bongdaso v globe and construct bongdaso v average congestion rate (ACR) index, our new metric for recording bongdaso v scale of global supply chain disruptions.

Figure 1 shows bongdaso v ACR index for bongdaso v period January 2017-2024. Despite bongdaso v outset of bongdaso v COVID-19 pandemic in February 2020, bongdaso v delays of container ships at ports increased notably only in bongdaso v second half of 2020. bongdaso v ACR index increased from 25% to 37% approximately, and bongdaso v average duration of these delays escalated from 5.5 to 13.5 hours. Thus, contrary to several commentaries, supply chain disturbances materialised well after bongdaso v outset of bongdaso v COVID-19 pandemic.

Figure 1 ACR index of global supply chain disruptions

A model of congestion and spare capacity

Next, we develop a new model to study bongdaso v causal effect of global supply chain disturbances and their implications for monetary policy. Our model is based on bongdaso v disequilibrium models of bongdaso v 1970s (Barro and Grossman 1971) but with a microfounded approach that considers bongdaso v frictions between buyers and sellers of goods (Michaillat and Saez 2015, Ghassibe and Zanetti 2022). This framework helps to identify bongdaso v causal effect of supply chain shocks in bongdaso v data.

Our model demonstrates that supply chain disturbances, generated by either an increase in transportation costs or a decrease in bongdaso v meetings between buyers and sellers, raise bongdaso v spare capacity in bongdaso v production markets while increasing bongdaso v scarcity of goods, and therefore bongdaso v prices in bongdaso v retail market. Disruptions to bongdaso v supply chain result in negative co-movements between output and bongdaso v price of goods, like supply shocks. However, they increase spare capacity for producers due to bongdaso v reduction in bongdaso v shipment of goods, whereas traditional supply shocks decrease spare capacity. Hence, an increase in spare capacity, coupled with a rise in prices and a decline in output, identifies bongdaso v causal effect of supply chain disturbances.

What drove US inflation since 2020?

We use our new identification scheme to constrain bongdaso v responses of key macroeconomic variables to a supply-chain disturbance in a structural vector autoregression (SVAR) estimated using our ACR index and US data. Our findings reveal an immediate and significant effect of supply chain disruptions, leading to a notable decline in real GDP and an increase in unemployment and inflation. 2

We decompose bongdaso v separate contributions of bongdaso v distinct shocks to bongdaso v productive capacity, aggregate demand, and bongdaso v supply chain to inflation. Figure 2 shows bongdaso v result of bongdaso v exercise. Before 2020, supply chain disturbances had a negative impact on inflation, highlighting bongdaso v effectiveness of strategic supply chain improvements and infrastructure upgrades at bongdaso v port of Los Angeles that eased inflationary pressures. bongdaso v early 2020 drop in inflation at bongdaso v onset of bongdaso v COVID-19 recession primarily resulted from a sharp fall in aggregate demand, likely linked to mobility restrictions and increased uncertainty at bongdaso v early phase of bongdaso v pandemic. On bongdaso v other hand, supply chain disturbances were bongdaso v main drivers of inflation in 2021. By early 2022, shocks to bongdaso v productive capacity and aggregate supply primarily contributed to bongdaso v surge in inflation, likely related to bongdaso v shift in preferences of workers towards flexible work arrangements and bongdaso v increase of unemployment benefits brought by bongdaso v CARES Act. Notably, aggregate demand played a minor role in bongdaso v movements of inflation post-2022, suggesting that monetary and fiscal policies were not excessively expansionary. From mid-2022 onward, a combination of weakening demand, strengthening productive capacity, and recovering supply chains contributed to lower inflation.

Figure 2 Drivers of US goods inflation

Notes: bongdaso v solid line represents bongdaso v standardised US goods inflation rate, calculated as bongdaso v quarter-on-quarter growth of bongdaso v PCE goods price index. bongdaso v shaded bars depict bongdaso v corresponding standardized cumulative historical contributions of shocks to aggregate demand, productive capacity, and bongdaso v supply chain to goods inflation.

A more aggressive, yet less contractionary, monetary policy tightening

Finally, our model allows us to study bongdaso v implications for bongdaso v effectiveness of monetary policy. Our theory shows that supply chain disruptions generate stagflation while increasing producers' spare capacity, generating scarcity of goods in bongdaso v retail market, and increasing prices. In this situation, prices become highly sensitive to changes in demand, while output remains relatively inelastic. In other words, disruptions to bongdaso v supply chain enhance bongdaso v effectiveness of contractionary monetary policy in taming inflation while reducing bongdaso v sensitivity of output to bongdaso v policy.

We empirically test this theoretical prediction using a threshold vector autoregression model. We find that an exogenous tightening of monetary policy leads to a significantly larger and more persistent decline in inflation for a given decrease in output during periods of supply chain disruptions. Our results support a more aggressive, yet less contractionary, approach to tightening monetary policy in response to bongdaso v elevated inflation consequent to supply chain disturbances.

Our study provides an initial step toward a full understanding of bongdaso v macroeconomic consequences and policy responses to supply chain disturbances, which will remain critical to bongdaso v modern economy, which revolves around an intricate global supply chain.

Source: https://cepr.org/voxeu/columns/causal-effects-and-policy-implications-global-supply-chain-disruptions

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