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This paper analyses the costs and benefits of lockdown policies in the face of COVID-19. What matters for people is the quality and length of lives and one should measure costs and benefits in terms of those things. That raises difficulties in measurement, particularly in valuing potential lives saved. We draw upon guidelines used in the UK for public health decisions, as well as other measures, which allow a comparison between health effects and other economic effects. We look at evidence on the effectiveness of past severe restrictions applied in European countries, focusing on the evidence from the UK. The paper considers policy options for the degree to which restrictions are eased. There is a need to normalise how we view COVID because its costs and risks are comparable to other health problems (such as cancer, heart problems, diabetes) where governments have made resource...

We study the impact of non-pharmaceutical policy interventions (NPIs) like “stay-at-home” orders on the spread of infectious disease. NPIs are associated with slower growth of Covid-19 cases. NPIs “spillover” into other jurisdictions. NPIs are not associated with significantly worse economic outcomes measured by job losses. Job losses have been no higher in US states that implemented “stay-at-home” during the Covid-19 pandemic than in states that did not have “stay-at-home”. All of these results demonstrate that the Covid-19 pandemic is a common economic and public health shock. The tradeoff between the economy and public health today depends strongly on what is happening elsewhere. This underscores the importance of coordinated economic and public health responses.

Effects of the COVID-19 shocks in the Japanese labor market vary across people of different age groups, genders, employment types, education levels, occupations, and industries. We document heterogeneous changes in employment and earnings in response to the COVID-19 shocks, observed in various data sources during the initial months after onset of the pandemic in Japan. We then feed these shocks into a life-cycle model of heterogeneous agents to quantify welfare consequences of the COVID-19 shocks. In each dimension of the heterogeneity, the shocks are amplified for those who earned less prior to the crisis. Contingent workers are hit harder than regular workers, younger workers than older workers, females than males, and workers engaged in social and non-flexible jobs than those in ordinary and flexible jobs. The most severely hurt by the COVID-19 shocks has been a group of female,...

The COVID-19 pandemic has a severely negative impact on economic activity. We analyze whether and to what extent mandatory social distancing imposed by lockdown policies and voluntary social distancing triggered by COVID-19 fatality rates have driven growth developments in the first and second quarter of 2020. Based on a sample of 46 countries and making use of OLS, IV and panel fixed effects regressions we find that the stringency of lockdown policies drives growth developments over time, while fatality rates carry an additional weight in explaining cross-country growth differences for each quarter. Finally, vulnerabilities to mandatory and social distancing performed abroad captured by tourism exposure and trade openness, play a non-negligible role in explaining growth differences across countries in the first half of 2020.

Purpose: The purpose of this study is to assess the potential economic cost of the COVID-19 pandemic on China’s macroeconomy and agri-food system and provide policy recommendations to stimulate economic growth and agri-food system development. Design/methodology/approach: An economy-wide multisector multiplier model built on China’s most recent social accounting matrix (SAM) for 2017 with 149 economic sectors is used to assess the impact of COVID-19 on China’s macroeconomy and agri-food system. SAM multiplier analysis focuses on supply chain linkages and captures the complexity of an interconnected economy. Findings: The paper finds that both the macroeconomy and agri-food systems are hit significantly by COVID-19. There are three main findings. First, affected by COVID-19, GDP decreased by 6.8% in the first quarter of 2020 compared with that in 2019, while the economic loss of the...

We construct a quantitative model of an economy hit by an epidemic. People differ by age and skill, and choose occupations and whether to commute to work or work from home, to maximize their income and minimize their fear of infection. Occupations differ by wage, infection risk, and the productivity loss when working from home. By setting the model parameters to replicate the progression of COVID-19 in South Korea and the United Kingdom, we obtain three key results. First, government-imposed lock-downs may not present a clear trade-off between GDP and public health, as commonly believed, even though its immediate effect is to reduce GDP and infections by forcing people to work from home. A premature lifting of the lock-down raises GDP temporarily, but infections rise over the next months to a level at which many people choose to work from home, where they are less productive, driven...

We discuss the impact of a Covid-like shock on a simple toy economy, described by the Mark-0 Agent-Based Model that we developed and discussed in a series of previous papers. We consider a mixed supply and demand shock, and show that depending on the shock parameters (amplitude and duration), our toy economy can display V-shaped, U-shaped or W-shaped recoveries, and even an L-shaped output curve with permanent output loss. This is due to the existence of a self-sustained “bad” state of the economy. We then discuss two policies that attempt to moderate the impact of the shock: giving easy credit to firms, and the so-called helicopter money, i.e. injecting new money into the households savings. We find that both policies are effective if strong enough, and we highlight the potential danger of terminating these policies too early. Interestingly, when policy is successful, inflation...

Understanding the immediate consequences of the COVID-19 pandemic on consumer behaviour is essential for informing the policy makers on the economic cost of strict measures, such as population lockdowns and business shutdowns. Yet, estimating the effect of the health shock on consumption, net of policy restrictions, is challenging because such measures affect consumer choices. South Korea is an interesting case because its policy response in the early stages of the pandemic did not involve such restrictive measures. We exploit this fact to study the consequences of the health shock on consumption. Because the intensity of the pandemic varied greatly across administrative regions, we are able to quantify the direct effect of the health shock on consumption at the epicentre of the pandemic and to compare it with that in locations initially spared from the virus. Further, we quantify...

This paper evaluates the global welfare consequences of increases in mortality and poverty generated by the Covid-19 pandemic. Increases in mortality are measured in terms of the number of years of life lost (LY) to the pandemic. Additional years spent in poverty (PY) are conservatively estimated using growth estimates for 2020 and two different scenarios for its distributional characteristics. Using years of life as a welfare metric yields a single parameter that captures the underlying trade-off between lives and livelihoods: how many PYs have the same welfare cost as one LY. Taking an agnostic view of this parameter, estimates of LYs and PYs are compared across countries for different scenarios. Three main findings arise. First, as of early June 2020, the pandemic (and the observed private and policy responses) has generated at least 68 million additional poverty years and 4.3...

We use high-frequency Google search data, combined with data on the announcement dates of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic in U.S. states, to isolate the impact of NPIs on unemployment in an event-study framework. Exploiting the differential timing of the introduction of restaurant and bar limitations, non-essential business closures, stay-at-home orders, large-gatherings bans, school closures, and emergency declarations, we analyze how Google searches for claiming unemployment insurance (UI) varied from day to day and across states. We describe a set of assumptions under which proxy outcomes (e.g., Google searches) can be used to estimate the causal parameter of interest (e.g., share of UI claims caused by NPIs) when data on the outcome of interest (e.g., daily UI claims) are limited. Using this method, we quantify the share of overall growth in...