Today’s TextileFuture Newsletter is bringing to you again an item by the Boston Consulting Group and is entitled “Designing Resilience into Global Supply Chains”. Since it looks like Covid-19 is demanding for a new design and resilience into the Global Supply Chains, we pick-up the subject again, and from a different angle than before.
The second feature shows you all statistical and scientific methods and figures that can now be concluded from the development of the pandemic and the possible solutions deriving. The item is entitled “IMF: The great Lockdown – Dissecting the Economic Effects” and it is based upon the second chapter of the latest IMF World Economic Outlook, published on October 7, 2020.
Both items are a sort of a direction finder for all of us and our businesses. We hope you do find your own ways to master the challenges ahead.
Here starts the first feature:
Designing Resilience into Global Supply Chains
By guests authors By Ben Aylor, Bitan Datta, Megan DeFauw, Marc Gilbert, Claudio Knizek, and Michael McAdoo from Boston Consulting Group.
After decades of refinement, it seemed that global companies had gotten supply chain management down to a science. By orchestrating complex, international networks of suppliers, factories, and logistics providers, companies had been able to squeeze out cost, get goods to distant markets with remarkable efficiency, and keep inventory to a minimum.
Companies had already begun rethinking their far-flung supply chains in response to changing labor costs, advances in automation, rising protectionism, and external shocks, such as natural disasters. But it took the COVID-19 pandemic to more fully expose structural flaws that have prompted organizations to fundamentally reassess their approach to global manufacturing and sourcing. Factory lockdowns, transportation disruptions, and panic buying led to shortages of everything from medical supplies and household necessities to critical automotive and electronics components. The crisis also heightened geopolitical tensions, trade restrictions, and nationalist policies aimed at promoting domestic industry that are likely to continue reshaping the global business landscape.
Now, companies are exploring various ways to build more resilience into their manufacturing and supply networks—even if that resilience leads to extra costs. With massive value at stake, global enterprises are seeking to mitigate risk and secure better access to supplies and markets. They are exploring options for diversifying and regionalizing their manufacturing and supply networks, adding backup production and distribution capacity, and reoptimizing inventory. Companies are also seeking to improve their supply chain flexibility, risk-monitoring capabilities, and capacity to respond rapidly to new shocks.
Exactly what a future resilient supply chain looks like will vary by industrial sector, location, and the type of sourcing and manufacturing network that best fits each organization’s strategic objectives. Company decisions will largely be influenced by two key factors—what we call the “impetus to change,” such as economic and political pressures, and “the ease of adjustment,” such as the difficulty of replacing certain suppliers and the capital costs associated with moving to new locations. Companies that make the right adjustments will create supply chains that put them in the best position as they shift from fighting the pandemic to winning the post-COVID-19 future. Below, we offer a six-step approach to adapting supply chains and establishing competitive advantage.
A Shifting Global Sourcing Landscape
Many of today’s worldwide supply chains were developed during the high tide of globalization from the late 1980s through the first decade of the 2000s, when falling trade barriers and transportation costs removed friction in international commerce. Traditionally, supply chains were designed primarily to meet two overarching objectives: cost efficiency and optimal service levels. Manufacturing footprints and sourcing networks have been built largely to take advantage of differences around the world in factor costs—such as labor, materials, and energy—and on the ability to fulfill customer needs within a particular time and at a specified quality standard in given markets. Over the past few years, concerns over market access, resilience, and environmental sustainability have gained in importance in some sectors.
Well before the COVID-19 outbreak, however, geopolitical, technological, and economic forces had begun to redefine globalization. Companies have been realigning global supply chains in response to shifting manufacturing cost structures, improvements in advanced manufacturing technologies, tariff wars, and rising protectionism. Many global enterprises have been moving toward regional manufacturing and sourcing footprints in order to be closer to end markets. Their factories in China are increasingly targeting the huge, still growing domestic market and nearby countries, while factories in North America and Europe concentrate on local markets.
The trade war between the US and China accelerated shifts in procurement. Trade between the two economies dropped by 16% in 2019. US auto-part imports from China fell by 17%, but rose by 10% from Turkey and 24% from Southeast Asia. And while US imports of consumer durables from China shrank by 19%, they increased sharply from Japan, South Korea, India, Brazil, and Southeast Asia. Samsung moved smartphone manufacturing from China to India and Vietnam, for example, while LG Electronics shifted refrigerator production for the US market to South Korea.
Even larger production changes have been announced since the outbreak of the pandemic. Taiwan Semiconductor Manufacturing, the world’s leading silicon wafer foundry, said it plans to build a USD 12 billion plant in Arizona in order to serve its many US customers, for example, and Mazda has shifted manufacturing of some auto components from China to Mexico.
At the same time, governments have started to intervene more aggressively in order to promote domestic manufacturing. German economic minister Peter Altmaier has called for localizing production of medicines, while the US government is investing directly in companies developing vaccines and medical supplies. The US announced it will invest USD 138 million in a partnership with ApiJect Systems, for example, to produce hundreds of millions of inexpensive, prefilled plastic syringes that could be used to inject possible COVID-19 vaccines. Bipartisan support is also growing in the US Congress for billions of dollars in federal subsidies for domestic semiconductor manufacturing. India has launched Atmanirbhar Bharat Abhiyan (Self-Reliant India Mission), an initiative that seeks to make the nation more self-sufficient in key economic sectors.
As a result of these geopolitical, economic, and technological forces—as well as shocks such as pandemics—resilience and access to critical supplies and markets are emerging as rising priorities.
Which Sectors Are Most at Risk
These pressures will not affect all industrial sectors equally. In some segments of the biopharmaceutical and medical device and equipment sectors, for example, changes in supply chains may be needed if governments mandate local production in the wake of COVID-19. In many other sectors, adjustments will require balancing a number of tradeoffs.
To understand which supply chains are likely to experience the most significant change, we created a matrix that plots 16 industrial sectors along two axes. The first is impetus to change, an index of supply chain risk. Factors include a high dependence on imports, the reliability of key supplier countries, and exposure to potential government trade restrictions.
The second axis is ease of adjustment, a measure of how easily companies can adapt their supply chains. Factors include the sector’s capital intensity, the level of regulatory challenges that could constrain adjustments, and the availability of alternative suppliers. (See Exhibit 1.) In some sectors and product categories, for example, China is virtually irreplaceable because it enjoys an overwhelming advantage in terms of the scale and depth of its capabilities—or because capacity is limited in other nations. An upcoming Boston Consulting Group article will explore more deeply the high reliance of key US industries on China for critical components and raw materials.
Where individual companies and products within each industry segment land on the impetus to change/ease of adjustment matrix will vary, of course, depending on the markets they serve or their supply chain configurations.
The semiconductor sector illustrates some of the tradeoffs companies will need to consider. Relocating production is constrained by the immense capital costs of building state-of-the-art silicon-wafer fabrication plants and requirements for highly skilled workers. In both the US and China, however, there is strong impetus for change. Although US companies dominate most segments of the industry, the US imports about 65% of its semiconductors, primarily from foundries in Asia where they are fabricated and from US firms’ own offshore plants. The risks to US industries and national security from supply disruption are high. Therefore, pressure is mounting to increase domestic production. The impetus to change is also high in China: its manufacturers import 86 % of the semiconductors they use to make electronic devices—at a time when the US government is exploring tougher technology trade restrictions.
In other industries in which countries depend heavily on imports, supply chains are less likely to see major changes because the impetus to change is low, even if the ease of adjustment is favorable. The US imports most of its luxury goods and apparel from the EU and Asia, for example. But governments do not regard these sectors as strategically important, and overconcentration is not a major risk because supply chains are fairly simple and there are many potential source countries for products.
Defining and Measuring Resilience
The first step to improving resilience is to gain a clear view of supply chain risks at the company, business segment, or product level, depending on which level is like to be actionable for a given organization. Companies should measure their exposure to disruption on an absolute basis and against their competitors. Supply chain resilience should be measured for all three portions of the value chain:
- Source. Key metrics for gauging the resilience of a company’s supply ecosystem include the degree to which goods are imported, the percentage of suppliers that are concentrated in certain countries, the share of supplies that are sourced regionally and are close to end customers, the availability of backup suppliers for critical components, and the inventory levels of key inputs.
- Make. Companies can evaluate their manufacturing resilience by looking at the percentage of capacity concentrated in certain countries, the amount of production that is outsourced, and whether they have backup production capacity at existing locations in case of contingencies or qualified backup facilities in different locations.
- Deliver. Metrics for assessing the resilience of downstream channels that get products to customers include the share of revenues coming from markets that could be affected by sharp tariff hikes, how much of the distribution network is covered by a single partner, the average lead time for moving a product from a factory to a customer, and inventory levels in the end market.
Options for Achieving Resilience
If the supply chain risk is deemed to be high, an array of remedies is available for companies to improve resilience along each of the three value chain dimensions. (See Exhibit 2) Where a business sector and specific product sit on the impetus to change and ease of adjustment matrix will likely influence the levers that companies deploy to achiever their ultimate supply chain configuration. In particular, a company may conclude that it can best meet its strategic objectives by revising, migrating, or regionalising its supply chain. (See Exhibit 3)
To illustrate how companies can deploy different strategies, we provide a few examples. A company that makes low-value motors in a highly automated plant in China may find that it needs to make only small, but strategically important, adjustments. To increase its resilience, the motor manufacturer might add redundant capacity and qualify parts suppliers in more locations while also maintaining production in China in order to keep costs low and serve the Chinese market. It could also take actions to improve real-time visibility into its supply chain and strengthen its risk management.
An apparel or consumer electronics manufacturer, on the other hand, may decide the best approach is to migrate its supply chain by shifting a portion of production to Vietnam, India, or other countries that are not the target of high tariffs or trade uncertainty, although it would still have to weigh this against the cost, capacity, and efficiency advantages of keeping production in China.
A biopharma company that supplies the world from Asia may conclude it needs to regionalize its manufacturing footprint in order to mitigate the risk of supply disruptions. Production capacity in Asia would concentrate on serving regional markets, while plants in North America and Europe would focus on demand in those regions.
There are many ways companies can improve resilience in each dimension of the value chain. In terms of sourcing, for example, they can reduce the risk of geographical overconcentration of their supply base by reallocating procurement within their existing global supplier networks in order to be closer to end markets. They can also convince vendors to shift all or some of their production to alternative locations. Manufacturing networks can be made more resilient by expanding capabilities at existing factories and adopting a contingency strategy that prequalifies other factories within their networks and backup contract manufacturers that can quickly take on work if some facilities experience disruptions. To improve delivery resilience, companies can reoptimize inventories and stock goods closer to end markets.
Adapting Supply Chains
Even for companies with extensive experience in global manufacturing and sourcing, the COVID-19 crisis has created a need to restructure supply chains. We suggest companies take the following steps to assess and adjust their supply chains:
- Align design principles with the new reality. Begin by assessing whether your supply chain is adequate given the new economic and geopolitical realities. Identify exposure to high-level risks and the tradeoffs involved in optimizing the supply chain.
- Segment the portfolio by supply chain risk and understand performance drivers. Define key segments within your business portfolio and assess supply chain risks on the basis of many factors, including product, geographical footprint, technology, and exposure to potential policy change. Gauge the current performance of your supplier and manufacturing networks on dimensions such as cost and service levels.
- Identify levers and options at the segment level. Evaluate all applicable levers for supply chain optimization according to the profile of each segment and where in the supply chain the largest risks lie. Determine the level of effort required for each action and the impact it is likely to have on supply chain capabilities.
- Evaluate supply chain design options for each segment. For each potential lever, analyze the tradeoffs between geopolitical risk and factors such as production costs, logistics, duties, market access, and resilience. Then select an appropriate approach to supply chain optimization. Identify key KPIs for resilience: a company could, for example, decide it wants at least 30% of key products or inputs to come from three or more qualified manufacturing sites in different geographic areas and would like to keep its capacity utilization under 85%.
- Pressure test design choices across the company. Aggregate contemplated changes at the segment level and evaluate the resulting internal and external network at a company level. Then analyze what would happen to the redesigned supply chain under a set of scenarios—such as an escalating US-China trade war, a financial crisis that bankrupts key suppliers, or another pandemic—that could lead to business disruptions.
- Put the network redesign in place and monitor performance. Draw up a plan for implementing the new supply chain design and a system for monitoring the performance of the enterprise-to-enterprise network as the macroeconomic and geopolitical environment evolves.
The global supply and manufacturing networks that have served multinational enterprises well for decades have required substantial investments, hard-earned experience, and relationships that took years to build. But they have also been premised on many assumptions of the way the world works that are fast becoming outdated. To thrive and win in the post-COVID-19 global economy and beyond will require building supply chains that are resilient to disruption and flexible enough to capture new sources of competitive advantage.
Here starts the second item:
IMF: The great Lockdown – Dissecting the Economic Effects
To contain the coronavirus (COVID-19) pandemic and protect susceptible populations, most countries imposed stringent lockdown measures in the first half of 2020. Meanwhile, economic activity contracted dramatically on a global scale. This chapter aims to dissect the nature of the economic crisis in the first seven months of the pandemic. It finds that the adoption of lockdowns was an important factor in the recession, but voluntary social distancing in response to rising infections also contributed very substantially to the economic contraction. Therefore, although easing lockdowns can lead to a partial recovery, economic activity is likely to remain subdued until health risks abate. Meanwhile, countries should protect the most vulnerable and find ways to support economic activity compatible with social distancing, for example, by reducing contact intensity in the workplace and enhancing work from home where possible. This chapter also provides new evidence of the uneven effects of lockdowns, which are found to have a larger impact on the mobility of women and younger cohorts. This calls for targeted policy action to prevent a widening of inequality. Finally, the analysis shows that lockdowns can substantially reduce COVID-19 infections, especially if they are introduced early in a country’s epidemic and are sufficiently tight. Thus, despite involving short-term economic costs, lockdowns may pave the way to a faster recovery by containing the spreadof the virus and reducing the need for voluntary social distancing over time, possibly having positive overall effects on the economy. This remains an important area for future research as new data become available.
The COVID-19 pandemic has raised unprece- dented health challenges on a global scale. To contain the spread of the virus, most countries have resorted to stringent lockdown measures, closing schools and business activities and sometimes even preventing
The authors of this chapter are Francesca Caselli, Francesco Grigoli (co-lead), Weicheng Lian, and Damiano Sandri (co-lead), with support from Jungjin Lee and Xiaohui Sun. The chapter benefited from insightful comments by Yuriy Gorodnichenko and internal seminar participants.
This chapter’s first goal is to shed light on the extent to which the economic contraction was driven by the adoption of government lockdowns instead of by people voluntarily reducing social interactions for fear of contracting or spreading the virus. This issue is important to understand retrospectively the nature of the recession and to provide insights into the strength of the upcoming recovery. If lockdowns were largely responsible for the economic contraction, it would be reasonable to expect a quick economic rebound when they are lifted. But if voluntary social distancing played a predominant role, then economic activity would likely remain subdued until health risks recede.
The analysis starts by examining the cross-country association between lockdowns and economic activ- ity across a broad sample of countries. It finds that countries that endured more stringent lockdowns experienced larger growth declines relative to pre–COVID-19 forecasts, even after controlling for the severity of the local epidemic. The chapter then assesses the impact of lockdowns using high-frequency proxies for economic activity, namely mobility indica- tors provided by Google and job postings provided by the website Indeed.1 Regression results show that lock- downs have a considerable negative effect on economic activity. Nonetheless, voluntary social distancing in response to rising COVID-19 infections can also have strong detrimental effects on the economy. In fact, the analysis suggests that lockdowns and voluntary social distancing played a near comparable role in 1Google Community Mobility Reports provide information on daily attendance rates at various locations relative to precrisis levels. Data are available at a national level for a large set of advanced, emerging market, and developing economies. For various countries, mobility information is also available at a subnational level. Data can be downloaded at https://www.google.com/covid19/mobility/. The job site Indeed provided the IMF with anonymized informa- tion about daily job postings in 22 countries, disaggregated by job categories driving the economic recession. The contribution of voluntary distancing in reducing mobility was stronger in advanced economies, where people can work from home more easily and sustain periods of temporary unemployment because of personal savings and government benefits.
When looking at the recovery path ahead, the importance of voluntary social distancing as a con- tributing factor to the downturn suggests that lifting lockdowns is unlikely to rapidly bring economic activity back to potential if health risks remain. This is true especially if lockdowns are lifted when infec- tions are still relatively high because, in those cases, the impact on mobility appears more modest. Further tempering the expectations of a quick economic rebound, the analysis documents that easing lock- downs tends to have a positive effect on mobility, but the impact is weaker than that of tightening lock- downs. These findings suggest that economies will continue to operate below potential while health risks persist, even if lockdowns are lifted. Therefore, policy- makers should be wary of removing policy support too quickly and consider ways to protect the most vulnerable and support economic activity consistent with social distancing. These may include measures to reduce contact intensity and make the workplace safer, for example by promoting contactless payments; facilitating a gradual reallocation of resources toward less-contact-intensive sectors; and enhancing work from home, for example, by improving internet con- nectivity and supporting investment in information technology.
The chapter also contributes to the growing empirical evidence on the uneven effects of the crisis, with particularly acute impacts on more economi- cally vulnerable people. Using novel anonymised and aggregated mobility indicators provided by Vodafone for some European countries, the analysis shows that lockdowns tend to have a larger effect on women’s mobility than on men’s, especially at the time of school closures.2 This suggests that women carry a disproportionate burden in caring for children, which2These indicators were prepared by Vodafone’s Big Data and Artificial Intelligence team and were provided for the analysis in an anomymized format through a confidential agreement. To protect the privacy of individuals and minority groups, mobility indices were aggregated at the provincial level, including at least 50 customers.
The data sharing protocol was subject to technical and organizational controls, including an ethical assessment of the analysis prior to its implementation may jeopardize their employment opportunities. Vodafone data also show that lockdowns tend to have a stronger impact on the mobility of younger cohorts, who are economically more vulnerable because they generally rely on labor income and have less stable jobs. Thus, targeted policy intervention is needed to protect the employment prospects of women and younger cohorts and prevent a widening of income inequality.
Finally, the chapter finds that lockdowns can reduce infections substantially. The effects of lock- downs on confirmed COVID-19 cases tend to materialize after a few weeks of delay, given the incubation period of the virus and testing times. This underscores the importance of early intervention, also because lockdowns are more effective in curbing infections if they are introduced early in the stage of a country’s epidemic. The analysis also suggests that lockdowns must be sufficiently stringent to reduce infections significantly.
The effectiveness of lockdowns in reducing infec- tions suggests that lockdowns may pave the way to a faster economic recovery if they succeed in containing the epidemic and thus limit the extent of voluntary social distancing. Therefore, the short-term economic costs of lockdowns could be compensated by stronger medium-term growth, possibly leading to positive overall effects on the economy. This is an important area for future research. Meanwhile, policymakers should also pursue alternative ways to contain infec- tions that may involve lower short-term economic costs than lockdowns, such as expanding testing and contact tracing, promoting the use of face masks, and encouraging work from home. As the understanding of the virus transmission improves, countries may also be able to deploy targeted measures rather than blunt lockdowns, for example by focusing on pro- tecting vulnerable people and restricting large indoor gatherings.
The analysis contributes to a rapidly growing liter- ature on the pandemic and the effects of lockdowns, which is reviewed in Box 2.1. The understanding of the crisis is still evolving—some papers detect consid- erable effects of lockdowns while others emphasize the role of voluntary social distancing. The literature also documents the pandemic’s uneven effect on vulnerable segments of the population and provides evidence of the effectiveness of lockdowns and face masks in containing infections.
Cross-Country Evidence on Lockdowns and Economic Activity
The analysis starts by presenting cross-country evidence on the association between lockdowns and economic activity over a sample of up to 52 advanced, emerging market, and developing economies. Panel 1 of Figure 2.1 shows the correla- tion between the stringency of lockdowns during the first half of 2020 and the decline in GDP relative to pre-pandemic forecasts.3 The figure illustrates that countries that implemented more stringent lock- downs experienced sharper GDP contractions.
Panel 2 of Figure 2.1 shows that the negative association between lockdowns and economic activ- ity is robust to using other indicators besides GDP. For example, more stringent lockdowns are associ- ated with lower consumption, investment, indus- trial production, retail sales, purchasing managers’ indices for the manufacturing and service sectors, and higher unemployment rates.4 These correla- tions persist with and without controlling for the strength of each country’s epidemic based on the total number of confirmed COVID-19 cases scaled by population.
Figure 2.1 thus provides suggestive evidence that lockdowns tend to have a negative short-termeconomic impact. Nonetheless, these findings should be interpreted with caution given omitted variable concerns that affect cross-country analyses and endogeneity concerns about lockdowns. The decision to deploy lockdowns is indeed not random; rather, it may reflect time-invariant country characteristics that also affect economic outcomes. For example, countries with higher social capital may not require stringent lockdowns—as people take greater precautions against infecting others—and could also better withstand the economic impact of the crisis. This may generate a spurious negative correlation between the stringency of lockdowns and economic activity. To strengthen identification by controlling for such time-invariant country characteristics, the next section reexamines the economic impact of lockdowns using time-series variation in high-frequency data.
3The analysis uses a lockdown stringency index that averages several subindicators—school closures, workplace closures, cancellations of public events, restrictions on gatherings, public transportation closures, stay-at-home requirements, restrictions on internal movement, and controls on international travel— provided by the University of Oxford’s Coronavirus Government Response Tracker.
4Data for GDP, consumption, and investment refer to the first half of 2020. For the other indicators that are available at monthly frequency, the analysis considers the first three months after thefirst 100 confirmed COVID-19 cases in each country to compare economic outcomes during the same phase of a country’s epidemic.
See Online Annex 2.2 for additional details. All annexes are available at www.imf.org/en/Publications/WEO
Assessing the Impact of Lockdowns Using High-Frequency Data
Two types of daily data are used to proxy for economic activity at high frequency. First, the analysis uses mobility data provided by Google, which reports the attendance rate at various locations relative to precrisis levels.5 These data have the key advantages of covering a large set of countries and being available also at thesubnational level. The findings based on mobility data are corroborated using job posting data reported by Indeed, an online job search engine. Indeed data are available for fewer countries, but capture labour market conditions more directly.
Lockdowns and Mobility
To assess the impact of lockdowns on mobility, the analysis uses local projections that include country fixed effects and time dummies to control for time-invariant country characteristics and global shocks, respectively. It is important to note that lockdowns are endogenous policy choices that depend on the stage of the epidemic and the degree of mobility. For example, governments are more likely to impose lockdowns when health risks become more acute. At the same time, people tend to reduce mobility because they fear contracting the virus, independent of lockdowns. This may lead to a spurious negative correlation between lockdowns and mobility. To alleviate these endogeneity concerns, the regression framework controls for the number of COVID-19 cases and includes lags of the mobility indicator. In other words, the empirical analysis tries to measurethe impact on mobility from a lockdown tightening at a given stage of the country’s epidemic. Online Annex 2.3 provides additional details.
The regression is estimated using national-level data for 128 countries. Panel 1 of Figure 2.2 shows that lockdowns tend to have a statistically significant negative effect on mobility. A full lockdown that includes all measures that governments have used during the pandemic— for example, school closures, travel restrictions, business closures, and stay-at-home requirements—tends to generate a reduction in mobility of about 25 percent within a week.
Mobility starts to resume gradually after that as the lockdown tightening shock dissipates, as illustrated in Online Annex 2.3.6
To address endogeneity concerns further, the impact of lockdowns is also estimated using subnational data.
The analysis considers 15 Group of Twenty countries that imposed national lockdowns in response to severe localized outbreaks and examines the impact on mobility in regions with a relatively low number of COVID-19 cases. This approach strengthens the identification because the adoption of the national lockdown was largely exogenous for regions less affected by the epidemic. As reported in Online Annex 2.3, the results confirm that lockdowns tend to have a strong negative impact on mobility. These findings are robust to controlling for COVID-19 cases at both the regional and national levels.
However, lockdowns are not the only contributing factor to the decline in mobility. During a pandemic, people also voluntarily reduce exposure to one another as infections increase and they fear becoming sick. Several papers document this aspect by showing that mobility has been tightly correlated with the spread of COVID-19, even after controlling for government lockdowns, especially in advanced economies (Aum, Lee, and Shin 2020; Goolsbee and Syverson 2020; Maloney and Taskin 2020). In line with this literature, the regression framework used in the analysis can shed light on the strength of voluntary social distancing by capturing the response of mobility to rising COVID-19 infections for a given lockdown stringency.7 Panel 2 of Figure 2.2 shows that an increase in COVID-19 cases tends to have a considerable negative effect on mobility.
A doubling of daily cases leads to a contraction in mobility by about 2 percent. Online Annex 2.3 also shows that the results are robust to controlling for COVID-19 deaths instead of cases; using subindicators of mobility provided by Google; controlling for testing, contact tracing, and public information campaigns; and accounting for possible cross-country heterogeneity in the mobility response depending on population density and indicators of governance and social capital. 7Besides reacting to the spread of COVID-19, people may voluntarily opt for social distancing also in response to other factors, such as announcements by public health officials, news about celebrities being infected, or even the adoption of government lockdowns. Therefore, the analysis may underestimate the extent of voluntary social distancing. The results are robust to controlling for COVID-19 deaths instead of cases. Normalising COVID-19 cases or deaths by population is irrelevant, given that the regressions include country fixed effects and population does not vary during the period of analysis. To gain further insights into the relative importance of lockdowns and voluntary social distancing tied to rising COVID-19 cases, panel 3 of Figure 2.2 shows their contribution in reducing mobility duringthe first three months of each country’s epidemic.
Both lockdowns and voluntary social distancing had a large impact on mobility, playing a roughly similar role in emerging markets. The contribution of voluntary social distancing was smaller in low-income countries and larger in advanced economies. These differences likely reflect that people in more economically developed countries can work from home more easily and can even afford to stop working temporarily by relying on personal savings or socialsecurity benefits. Conversely, people in low-income countries are often unable to opt for voluntary social distancing as they do not have the financial means to cope with a temporary income loss. This underscores the importance of international support to ensure that low-income countries have budgetary room for expanding safety nets.
The large contribution of voluntary social distancing in reducing mobility suggests that lifting lockdowns can lead to only a partial rebound in economic activity if health risks persist. In line with this implication, panel 1 in Figure 2.3 shows that the impact of lockdowns on mobility is smaller when infections are relatively high. A likely reason is that people feel uncomfortable with resuming mobility when lockdowns are lifted if they still perceive a considerable risk of contracting or spreading the virus. This insight warns against lifting lockdowns prematurely in hope of jump-starting economic activity. Panel 2 of Figure 2.3 provides additional evidence against expecting a sharp economic recovery just from easing lockdowns. It showsthat easing lockdowns tends to have a positive effect on mobility but the magnitude is weaker compared with the impact from a lockdown tightening. As documented in Online Annex 2.3, this difference is statistically significant.
The importance of voluntary social distancing coupled with the modest boost to mobility from easinglockdowns suggest that economies will likely operate below potential as long as health concerns persist.8 A first implication is that policymakers should be 8Given the severity of the downturn, the crisis may have alsoreduced the level of potential output, thus leading to permanentlosses even after the pandemic is over. This is an important issue for future research.
The impact of lockdowns on mobility is weaker when COVID-19 cases are higher. Furthermore, a lockdown easing tends to have a smaller impact on mobility relative to a lockdown tightening, of removing policy support too hastily to avoid precipitating a further downturn and should continue to protect the most vulnerable through social safety net spending. Second, it is important to find ways to support economic activity consistent with persistent social distancing. These may include measures to reduce contact intensity and make the workplace safer—for example by promoting contactless payments—and facilitate the reallocation of resources toward less-contact-intensive sectors. Policymakers should also enhance working from home, for example by improving internet access and supporting firm investment in information technology, which, as shown in Box 2.2, can protect employment during the pandemic.
Lockdowns and Job Postings
The importance of lockdowns and voluntary social distancing in the ongoing crisis can also be examined using the daily number of job postings provided by Indeed for 22 countries. The analysis uses a local projection framework that mimics the one used for the analysis of mobility. Panels 1 and 2 of Figure 2.4 show that a lockdown tightening and an increase in COVID-19 cases both lead to a statistically significant negative effect on job postings, corroborating the findings based on mobility. Both lockdowns and voluntary social distancing in response to higher infections appear to have played an important role in driving the reduction in job postings during the first three months of each country’s epidemic (panel 3). Consistent with the analysis of mobility, the contribution of voluntary social distancing is relatively higher because the country sample includes mostly advanced economies.
Data from Indeed can also be disaggregated by job categories, providing additional insights consistent with the results presented so far. First, panel 1 of Figure 2.5 suggests that both lockdowns and voluntary social distancing contributed to the reduction in job postings. Contact-intensive jobs—such as those in the hospitality, personal care, and food sectors—declined before stay-at-home orders, likely because of voluntary social distancing as customers grew wary of infection risks. Job postings in the manufacturing sector—that do not involve personal contacts with customers—instead started to decline closer to the adoption of stay-at-home orders, reflecting the impact of lockdown measures. The figure also shows that job postings incontact-intensive sectors declined more than in the manufacturing sector, likely reflecting a larger drop in aggregate demand because of voluntary social distancing.
Second, panel 2 provides evidence consistent with the notion that easing lockdowns is unlikely to generate a sharp rebound in economic activity. The
removal of stay-at-home orders has coincided with only a marginal increase in job postings, even in the less-contact-intensive manufacturing sector.
The Unequal Effects of Lockdowns across Gender and Age Groups
The pandemic is having disproportional effects on the most economically vulnerable segments of the population. As reviewed in Box 2.1, the literature documents strong negative effects on lower-income The pandemic is having disproportional effects on the most economically vulnerable segments of the population. As reviewed in Box 2.1, the literature documents strong negative effects on lower-incomehouseholds, workers with lower educational attainment, minorities, immigrants, and women. For example, unlike during previous recessions, women’s employment has generally declined more than men’s has. This section provides additional insights on the uneven impact on women using novel mobility data provided by Vodafone for Italy, Portugal, and Spain. By analysing connections across cell towers, Vodafone can create mobility indices by gender based on the information customers provide when subscribing to a phone plan. Data are aggregated at the provincial level to protect customers’ privacy. Vodafone data also differentiate mobility indices by age groups, thus providing novel important perspectives on the mobility patterns during the COVID-19 pandemic. Panel 1 of Figure 2.6 shows mobility levels for menand women 30 days before and after the adoption of stay-at-home orders for people aged 25 to 44. These orders coincided with a large drop in mobility for both men and women, leading to a drop of about 20 % in the number of people who leave their homes on a given day. However, the effect on women was stronger by about 2 %, a modest. but statistically significant difference. Because stay-at-home orders
in Italy, Portugal, and Spain coincided with school closures for almost all regions, the higher reduction in women’s mobility may reflect that women are more likely to care for children when schools are closed. Consistent with this hypothesis, data show a smaller difference between men and women for people aged 45 to 64, who are less likely to have young children who require supervision at home.
Panel 2 provides additional evidence on women’s role in caring for children. Focusing on a few regions in Northern Italy that closed schools two weeks before the national lockdown, mobility data show that the gender gap already widened at the time of school closures. The national stay-at-home order increased the gap further, possibly reflecting higher female employment in contact-intensive sectors (such as retail, tourism, and hospitality) that were closed during the national lockdown. The evidence provided in panels 1 and 2 thus points to a disproportionate effect of lockdown measures on women, calling for targeted policy intervention to support women (by offering parental leave, for example) and to avoid long-lasting effects on their employment opportunities.9
Vodafone data also reveal uneven effects of lockdowns across age groups. Panel 3 shows that the adoption of stay-at-home orders led to a considerable reduction in mobility across all age categories.
The evidence provided in panels 1 and 2 thus points to a disproportionate effect of lockdown measures on women, calling for targeted policy intervention to support women (by offering parental leave, for example) and to avoid long-lasting effects on their employment opportunities.9
Panel 3 shows that the adoption of stay-at-home orders led to a considerable reduction in mobility across all age categories. Nonetheless, the effects were considerably stronger for younger cohorts. Starting from a higher level of mobility consistent with the need to go to work, working-age people experienced a sharp contraction in mobility around the adoption of stay-at-home orders. The drop was particularly large for people aged 18 to 24 (some of whom, however, are students) and for people aged 25 to 44.
The impact was substantially weaker for people aged 65 and above, who generally no longer work and whose level of mobility was alreadylower before the stay-at-home orders. These findings mobility around the adoption of stay-at-home orders. The drop was particularly large for people aged 18 to 24 (some of whom, however, are students) and for people aged 25 to 44. The impact was substantially weaker for people aged 65 and above, who generally nolonger work and whose level of mobility was alreadylower before the stay-at-home orders. These findings highlight that lockdowns tend to have a disproportionate impact on relatively younger workers and couldthus widen intergenerational inequality.10 While olderpeople can rely on retirement income, especially in advanced economies, younger workers depend on labour income and often have temporary job contracts that are more likely to be terminated during a crisis.
Lockdowns and COVID-19 Infections
Lockdowns engender sizable short-term economic costs, but they are also an investment in public protect susceptible populations from the highly transmissible virus. The analysis now examines the effectiveness of lockdowns in curbing infections. Growth rates of confirmed COVID-19 cases are regressed using local projections over the stringency of lockdowns while controlling for country and time fixed effects as well as other variables that can affect infections, such as outside temperature and humidity, public information campaigns, testing, and contact tracing. Online Annex 2.5 provides additional details.
Panel 1 of Figure 2.7 shows that lockdowns tend to have a negative impact on infections. A stringent lockdown leads to a reduction in cumulated infections of about 40 % after 30 days. Note that the effects of lockdowns on confirmed COVID-19 cases tend to materialise after at least two weeks, consistent with the COVID-19 incubation period and the time required for testing. Acknowledging this aspect is important to properly guide people’s expectations about the effectiveness of lockdowns . Furthermore, the lagged impact on infections points to the need to adopt lockdowns before infection rates increase too rapidly. Panels 2 and 3 of Figure 2.7 provide additional evidence of the benefits of adopting lockdowns early in a country’s epidemic. Panel 2 shows the evolution of infections since the first COVID-19 case, differentiating countries by the number of days between the first case and the day when lockdown measures reached maximum stringency. Countries that imposed lockdowns faster experienced better epidemiological outcomes. The differences are even more striking if countries are divided with respect to the number of
COVID-19 cases at the time of lockdowns (panel 3).
Countries that adopted lockdowns when COVID-19 cases were still low witnessed considerably fewer infections during the first three months of the epidemic compared with countries that introduced lockdowns when cases were already high. The observation that lockdowns can reduce infections but involve short-term economic costs is often used to argue that lockdowns involve a trade-off between saving lives and protecting livelihoods. This narrative should be reconsidered in light of the earlier findings showing that rising infections can also have severe detrimental effects on economic activity. By bringing infections under control, lockdowns may thus pave the way to a faster economic recovery as peoplefeel more comfortable about resuming normal activities.In other words, the short-term economic costs of lockdowns could be compensated through higher future economic activity, possibly even leading to positive net effects on the economy. This remains a crucial area for future research as more data become available.
Individual Lockdown Measures and Nonlinear Effects
So far, the analysis has used a lockdown stringency index that combines a broad range of underlyingmeasures. These include, for example, travel restrictions, school and workplace closures, and stay-at-home orders. Disentangling the effects of these measures is an arduous task because they are highly correlated, as countries often introduced them in rapid succession to contain infections. Furthermore, countries have generally followed a similar sequence, from restrictions on international travel to stay-at-home orders, as illustrated in panel 1 of Figure 2.8. Therefore, the empirical analysis tends to capture the marginal impact of a given measure conditional on those that are already in place. As discussed in Online Annex 2.6, this underestimates the importance of measures that are adopted at a later stage. For example, stay-at-home orders are found to have a modest impact on mobility because various other measures are already in place.
An analytically sounder approach is to examine whether further tightening of lockdown measures continues to have similar economic and epidemiological effects. This can inform policymakers on whetherit is best to rely on protracted mild lockdowns or to opt for more stringent measures. To shed light onthis issue, the analysis uses quadratic terms of thelockdown index in the regression framework. Panel 2 of Figure 2.8 shows that the introduction of additional lockdown measures has a weaker marginal impact on mobility once other measures are already in place—that is, when the lockdown stringency index is already relatively high. This suggests that lockdowns have marginally weaker negative economic effects as they become more and more stringent. For example, stay-at-home orders may have only a modest negative impact on economic activity if governments have already mandated workplace closures.
Conversely, panel 3 shows that lockdowns become progressively more effective in reducing COVID-19 cases when they become sufficiently stringent. Mild lockdowns appear instead ineffective in curbing infections. A possible interpretation is that preventing only a few instances of personal contacts, such as by closing schools alone, is not enough to reduce community spread significantly. Additional measures, such as workplace closures or stay-at-home orders, are neededto effectively bring the virus under control. These results suggest that to achieve a given reduction in infections, policymakers may want to opt for stringent lockdowns over a shorter period rather than prolonged mild lockdowns. Based on past experience,tighter lockdowns appear indeed to entail only modest additional economic costs while leading to a considerably stronger decline in infections. It will be important to reexamine these results as the pandemic progresses because the relative benefits between mild and tight lockdowns may change. For example, if anexpansion of contact tracing and broader use of face masks succeed in limiting infections, mild lockdowns could be sufficient to contain new localised flare-ups of the virus.
This chapter has documented the crucial role that both lockdowns and voluntary social distancing in response to rising infections have played in reducing economic activity during the pandemic. Consistent evidence on the impact of lockdowns is provided by examining cross-country economic indicators and high-frequency proxies for economic activity, such as mobility and job posting data from Google and Indeed. Furthermore, the negative impact of lockdowns on mobility is robust to using subnational data to strengthen identification. Despite lockdowns having negative short-term economiceffects, letting infections grow uncontrolled can also have dire economic consequences. This is because voluntary social distancing in response to rising COVID-19 infections has severe detrimental effects on the economy. The contribution of voluntary social distancing in reducing mobility is particularly high in advanced economies, where people can more easily stay at home thanks to teleworking arrangements, higher personal savings, and more generous social security benefits.
The important contribution of voluntary social distancing to the recession should caution against expecting a quick economic rebound once lockdownsare lifted. This is especially relevant for countries that lift lockdowns prematurely, when infections are still relatively high. In this case, lockdowns tend to have a weaker impact on mobility, likely because people’s decisions are driven by fear of contracting the virus. Further tempering the expectations of a sharp economic rebound, the analysis shows that lifting lockdowns tends to have a more modest impact on mobility compared with the impact of a lockdown tightening.
These findings suggest that, as long as significant health risks persist, economic activity is likely to remain subdued. Therefore, policymakers should refrain from withdrawing policy support too quickly and preserve spending on social safety nets. Furthermore, it is important to support economic activity consistent with persistent social distancing, for example by encouraging work from home, facilitating a reallocation of resources toward less-contact-intensive sectors, and promoting the adoption of new technologies to limit the contact intensity within given sectors. The chapter also provides novel evidence about the unequal effects of lockdowns that severely affect economically vulnerable segments of the population.
Mobility data provided by Vodafone for some European countries show that lockdown measures—especially school closures—tend to generate a larger drop in women’s mobility. This likely reflects women’s disproportionate role in childcare, which could jeopardize their employment opportunities during the crisis. Lockdowns tend to also generate a sharper reduction in the mobility of younger cohorts, a worrisome outcome because younger workers rely on labour income and often have temporary job contracts that are at greater risk of being terminated. Targeted policy intervention, such as strengthening unemployment benefits for vulnerable categories and supporting paid leave for parents, is needed to ensure that the crisisdoes not contribute to widening gender and intergenerational inequality.
The analysis also finds that lockdowns are powerful instruments to reduce infections, especially when they are introduced early in a country’s epidemic and when they are sufficiently stringent. Considering also that lockdowns appear to impose decreasing marginal costs on economic activity as they become more stringent, policymakers may want to lean toward rapidly adopting tight lockdowns when infections increase rather than rely on delayed mild measures. Nonetheless, these recommendations will need to be reassessed as the understanding of the virus and means to counteract it improve. A crucial area of research is to examine the effectiveness of more-targeted instruments compared with blunt lockdowns, for example restrictions ondense indoor gatherings or measures to isolate people who are more vulnerable to the virus.
The effectiveness of lockdowns in reducing infections, coupled with the finding that infections can considerably harm economic activity because of voluntary social distancing, provides an important new perspectiveon the costs of lockdowns. The prevailing narrative often portrays lockdowns as involving a trade-off between saving lives and supporting the economy.
This characterisation neglects the point that, despite imposing short-term economic costs, lockdowns may lead to a faster economic recovery by containing the virus and reducing voluntary social distancing. These medium-term gains may offset the short-term costs of lockdowns, possibly even leading to positive overall effects on the economy. More research is warranted on this important aspect as the crisis evolves and more data become available. Meanwhile, policymakers should also look for alternative ways to contain infections that may have even lower economic costs. In line with the advice of public health experts, these may include expanding testing and contact tracing, promoting the use of face masks, and encouraging working from home.
The analytical results and policy implications presented in this chapter are subject to several caveats. First, the analysis tries to alleviate concerns about the endogeneity of lockdowns by showing that the results hold using cross-sectional and time-series identification and by relying on national and subnational data when available. However, identification concerns cannot be fully dismissed, including regarding the measurement of voluntary social distancing. Second, the analysis relies on short-term indicators, such as mobility and job postings, which provide an imperfect measure ofeconomic activity. The chapter’s findings will need tobe re-examined as more conventional economic indicators become available. Third, the analysis focuses on the economic consequences of lockdowns, neglecting important side effects, for example, on educational attainment and mental health issues. These are crucial areas for future research.
The Newsletter of last Week
Why fashion says ‘vote’ this US election, and the latest McKinsey Report on Accelerating winds of change in global payments https://textile-future.com/archives/58871
The highlights of TextileFuture’s News of last week. For your convenience just click on the feature.
Syngenta Group acquires leading Biologicals company, Valagro https://textile-future.com/archives/58961
UNWTO and IATA Sign Agreement to Restore Confidence in International Aviation https://textile-future.com/archives/59047
ICAC Releases 2020 Annual Report https://textile-future.com/archives/58885
The German Car Industry musters for a New Tech Battle https://textile-future.com/archives/59166
Bolger & O’Hearn named 2020 Manufacturer of the Year by Rep. Alan Silvia on behalf of the Massachusetts Commonwealth’s Legislature, House/Senate Manufacturing Caucus https://textile-future.com/archives/59077
A new level of bike tubes puncture resistance thanks to Elastollan® https://textile-future.com/archives/59170
12 weeks of Christmas: Retailers speed up holiday plans in a daunting year https://textile-future.com/archives/59082
Financing the Circular Economy published by the Ellen MacArthur Foundation https://textile-future.com/archives/59034
Swiss EMS Group third quarter report https://textile-future.com/archives/58903
Inside Levi’s new ‘NextGen’ retail store https://textile-future.com/archives/58910
Mondadori Group Signs Licensing Deal To Launch Grazia USA, Brand Premieres With Exclusive Kim Kardashian-West Digital Cover https://textile-future.com/archives/59085
BASF Group releases preliminary figures for third quarter of 2020 and publishes outlook for full year 2020 https://textile-future.com/archives/59151
Edinburgh Woollen Mill Group calls in administrators, putting 24000 jobs at risk https://textile-future.com/archives/59216
WTO marked the 1st anniversary of World Cotton Day on October 7, 2020 https://textile-future.com/archives/59138
Swissmedic starts rolling review of a COVID-19 vaccine https://textile-future.com/archives/59055
Joining forces to produce high-quality face masks with verifiable authenticity https://textile-future.com/archives/59065
Second quarter of 2020 EU current account surplus EUR 82.9 billion, EUR 24.8 billion surplus for trade in services https://textile-future.com/archives/58931
OECD annual inflation stable at 1.2 % in August 2020 https://textile-future.com/archives/58938
WTO – Trade shows signs of rebound from COVID-19, recovery still uncertain https://textile-future.com/archives/58983
OECD CLIs point to a moderation in growth https://textile-future.com/archives/59103
EU labour market in the second quarter 2020 – Total labour market slack up to 14 %, and sharp drop in hours worked https://textile-future.com/archives/59115
Second quarter of 2020 compared with second quarter of 2019 House prices up by 5.0 % in the Euro Area and in the EU by 5.2 % https://textile-future.com/archives/59127
The Week in Charts by McKinsey https://textile-future.com/archives/59201
Swiss Forecast: 2020 economic slump less serious than feared https://textile-future.com/archives/59223
OECD unemployment rate falls to 7.4 % in August 2020 but remains 2.2 percentage points above February 2020 https://textile-future.com/archives/59237
Visit to Ethiopia by High Representative/Vice-President Josep Borrell and Commissioner Janez Lenarčič to strengthen EU-Africa Partnership https://textile-future.com/archives/59146
2020 Taiwan Fashion Design Award Final Contest https://textile-future.com/archives/58887
Vogue Business and Google Summit https://textile-future.com/archives/58890
Groz-Beckert at the Innovate Textile & Apparel Virtual Trade Show https://textile-future.com/archives/58895
Italy: Virtual Fashion Tour https://textile-future.com/archives/58907
India-EAEU ties to put a nail to China’s future expansion https://textile-future.com/archives/59060
Oerlikon promises for the virtual trade show “Innovate Textile & Apparel”: Enjoy time travel from the home office https://textile-future.com/archives/59192
With Macy’s investment in Klarna, it will offer buy now, pay later option https://textile-future.com/archives/59074
Ann Summers lurches towards CVA https://textile-future.com/archives/58965
Frasers Group urges shareholders to back GBP 100 million staff bonus https://textile-future.com/archives/59071
Solving Plastic Pollution | Narrated by Sir David Attenborough & Dame Ellen MacArthur https://textile-future.com/archives/59049
DyStar releases Integrated Sustainability Report for 2019 – 2020 https://textile-future.com/archives/59063
U.S. NCTO Supports House Resolution Opposing Expansion of Generalised System of Preferences Program (GSP) to Include Apparel, Textiles, Footwear https://textile-future.com/archives/59052
U.S. NCTO welcomes Administration’s Section 301 Investigation into Vietnam’s Currency Practices https://textile-future.com/archives/58968
Asia Edge Webinars https://textile-future.com/archives/58917
WIPO Update on Recent and Future Developments in the PCT System – Virtual Seminar https://textile-future.com/archives/59135
Real Wool News https://textile-future.com/archives/58977
Determining knitted fabric elastane content by Koos Snijders (ex Lycra) https://textile-future.com/archives/58951
WTO launches new import licensing platform https://textile-future.com/archives/59209
WTO: UK to join government procurement pact in its own right in the new year https://textile-future.com/archives/59211