Stay-at-home orders feature high in the set of policies used to curb the spread of epidemics such as COVID-19, but are potentially less efficient among poor people who must continue to work during pandemics. We examine how income support programs help poor people comply with stay-at-home order and thereby generate positive health externalities. We use data on work-related mobility in 2020 and on poverty rates for 729 subnational regions of Africa, Latin America and Asia. We focus on within-country differential mobility changes between higher- and lower-poverty regions. Accounting for all time-variant country-level factors, we show that lockdowns have decreased mobility significantly less in poorer regions. In turn, emergency income support programs have helped reduce this difference, mitigating the regional poverty gap in virus exposure through work mobility.

The COVID-19 pandemic crisis and the associated lockdown measures have exerted significantly adverse effects on corporate sectors globally. Archanskaia et al. (2023) provide a novel empirical strategy to timely assess corporate financial distress in the EU. The contribution is two-fold. First, this paper's notion of financial distress considers both the equity position and corporate indebtedness. Second, the methodology proposed in this paper allows the authors to estimate corporate financial distress in the EU at a highly granular level and link micro-level simulations to sectoral macroeconomic outcomes. The methodology employed by Archanskaia et al. (2023) consists of three steps. First, the authors apply a nowcasting model to acquire monthly industrial turnover data. Second, they feed the obtained monthly industrial turnover into a profit-generating process via an accounting identity to estimate monthly firm profits at the firm level. Third, the authors use the estimated firm profits with a snapshot of information on pre-existing liquid assets to deduce the firm-level liquidity needs and the depletion of equity through the focus period during COVID-19. These estimated results on firm equity position and indebtedness enable the authors to quantity corporate financial distress in the EU via various angles (e.g., country-level heterogeneity, industry heterogeneity, and the targeting of COVID support policies). The primary advantage of this approach is that it deals with large datasets at the granular level and produces firm-level results almost in real-time. Therefore, it can help policymaking track the effects of crises over time. However, one can quickly critique this three-step approach for its susceptibility to the usual Lucas critique. That said, since the objective here is to estimate firm-level financial distress, a large structural model being more or less aggregate in nature, though able to mitigate the Lucas critique concern, will encounter significant challenges in estimating firm-level results with the requisite level of granularity offered by the available data. Therefore, I broadly concur with the authors' position that 'the specific contribution of this paper consists in striking a better balance between the need to carry out a multi-country evaluation of the pandemic's effects on industrial activity in a strongly integrated region like the EU and the difficulty of capturing time, industry, and country variation in turnover with sufficient granularity.'

In a representative sample of the U.S. population during the first summer of the COVID-19 pandemic, we investigate how prosociality and ideology interact in their relationship with health-protecting behavior and trust in the government to handle the crisis. We find that an experimental measure of prosociality based on standard economic games positively relates to protective behavior. Conservatives are less compliant with COVID-19-related behavioral restrictions than liberals and evaluate the government's handling of the crisis significantly more positively. We show that prosociality does not mediate the impact of political ideology. This finding means that conservatives are less compliant with protective health guidelines - independent of differences in prosociality between both ideological camps. Behavioral differences between liberals and conservatives are roughly only one-fourth of the size of their differences in judging the government's crisis management. This result suggests that Americans were more polarized in their political views than in their acceptance of public health advice.

We estimate the heterogeneous effect of the global financial cycle on exchange rates and cross-border capital flows during the COVID-19 pandemic, using weekly exchange rate and portfolio flow data for a panel of 59 advanced and emerging market economies. We estimate a global financial cycle (GFC) index at the weekly frequency with data through the end of 2021. We then estimate the country-specific sensitivities of exchange rates and capital flows to fluctuations in the GFC. The ability of the GFC to explain fluctuations in exchange rates and capital flows increased dramatically during the pandemic. There is significant cross-country heterogeneity in the response of exchange rates or capital flows to fluctuations in the GFC. During the pandemic, high-frequency indicators like weekly changes in Covid cases and vaccination rates were just as important as standard macroeconomic fundamentals like the current account, reserves, and net foreign assets in explaining this heterogeneity.

Asymmetric effects across sectors are the distinctive features of the Covid-19 shock. An Epidemiological-Industry Dynamic model with heterogeneous firms and endogenous firms dynamics mimics the deep recession suffered by sectors characterized by high exposure, the reallocation of entry and exit opportunities across sectors, and the dynamics of aggregate productivity during the first wave of the pandemic. The cleansing effect induced by the Covid-19 crisis is sector-specific. Monetary policy and sticky wages are central ingredients to capture reallocation effects. Social distancing, by smoothing out cleansing in the social sector, slows down the reallocation process and prolongs the recession, but saves lives.

Monetary and fiscal authorities reacted swiftly to the COVID-19 pandemic by purchasing assets (or "Wall Street QE") and lending directly to non-financial firms (or "Main Street Lending"). Our paper develops a new framework to compare and contrast these different policies. For the Great Recession, characterized by impaired balance sheets of financial intermediaries, Main Street Lending and Wall Street QE are perfect substitutes and both stimulate aggregate demand. In contrast, for the COVID-19 recession, where non-financial firms faced significant cash flow shortages, Wall Street QE is almost completely ineffective, whereas Main Street Lending can be highly stimulative.

Following the worst of the COVID-19 pandemic, inflation surged to levels last seen in the 1980s. Motivated by vast differences in pandemic support across countries, we investigate the subsequent response of inflation and its feedback to wages. We exploit the differences in pandemic support to identify the effect that these programs had on inflation and the passthrough to wages. Our empirical approach focuses on a novel dynamic difference-in-differences method based on local projections. Our estimates suggest that an increase of 5 percentage points in direct transfers (relative to trend) translates into about a peak 3 percentage points boost to inflation and wage growth. Moreover, higher inflation accentuates the role of inflation expectations on wage-setting dynamics.

This paper assesses corporate financial distress in terms of liquidity and risk of insolvency due to the COVID-19 pandemic. We develop a novel multivariate approach to obtain monthly data on industry turnover, exploiting real time data to capture the atypical character of industry-specific disturbances. By combining the estimated set of industry revenue shocks with pre-pandemic financial statements, we quantify the impact of the pandemic on the risk of insolvency in the EU non-financial corporate sector. Our definition of risk of insolvency takes into account not only the equity position of firms, but also risks relating to overindebtedness. The analysis controls for firms that were financially vulnerable already before the pandemic, thus being prone to become at risk of insolvency also in absence of the COVID-19 turmoil. We find that, for the EU as a whole, 25% of firms exhausted their liquidity buffers by the end of 2021 (a practical cut-off date of the analysis, not an assumed end of the pandemic). Furthermore, 10% of firms which were viable before the pandemic, appear to have shifted into risk of insolvency as a result of the COVID-19 crisis. The magnification of financial vulnerability in the hardest-hit industries mainly occurs among firms with no legacy issues, i.e. firms with positive profitability pre-pandemic. A similar finding is reported for some of the hardest-hit countries, such as Italy and Spain. In other countries, such as Germany or Greece, the magnification of financial vulnerability mainly occurs among firms with negative profitability pre-pandemic.

People's willingness to vaccinate is critical to combating the COVID-19 pandemic. We devise a representative experiment to study how the design of the vaccine approval procedure affects trust in newly developed vaccines and consequently public attitudes towards vaccination. Compared to an , choosing the more thorough approval procedure increases vaccination intentions by 13 percentage points. The effects of the increased duration of the approval procedure are positive and significant only for . Treatment effects do not differ between relevant subgroups, such as respondents who had (did not have) COVID-19, or between vaccinated and unvaccinated respondents. Increased trust in the vaccine is the key mediator of treatment effects on vaccination intentions.

This paper uses the onset of COVID-19 to examine how countries construct their policy packages in response to a severe negative shock. We use several new datasets to track the use of a large variety of policy tools: announced fiscal stimulus (both above- and below-the-line), monetary policy (through interest rates, asset purchases, liquidity support and swap lines), foreign currency intervention, adjustments to macroprudential regulations (including the countercyclical capital buffer) and changes in capital controls (on inflows and outflows). The results suggest that pre-existing policy space was usually more important than other country characteristics and the extent of "stress" (in economic, financial, and health measures) in determining how a country responded to COVID-19. The notable exception is for fiscal stimulus, for which existing policy space did not act as a significant constraint in advanced economies. This is a sharp contrast to results for earlier episodes-although advanced economies with higher debt levels may have been constrained in how they provided stimulus (with more below-the-line commitments). Moreover, the use of (and space available) for each policy tool usually did not affect a country's use of other policies. This suggests that countries are not coordinating their tools optimally in an integrated framework, especially when policy space is limited for certain tools.

This paper studies containment policies for combating a pandemic in an open-economy context. It does so via quantitative analyses using a model that incorporates a standard epidemiological compartmental model in a general equilibrium multi-country, multi-sector Ricardian model of international trade with input-output linkages. We quantitatively evaluate the long-run welfare and real-income losses due to the short-run pandemic shocks, and we study the role of trade in these effects. We devise a novel approach to computing national optimal policies. We find that (1) the long-run welfare and real-income losses due to just two years of pandemic shocks are substantial; (2) international trade helps buffer both the welfare and real-income losses, and it also saves lives; (3) the computed optimal policies indicate that most countries should have tightened their containment measures relative to what was done; and (4) compared to the case of autarky, the optimal policy under trade is generally more stringent.

Governments have implemented school closures and online learning as one of the main tools to reduce the spread of Covid-19. Despite the potential benefits in terms of containment of virus diffusion, the educational costs of these policies may be dramatic. This work identifies these costs, expressed as decrease in test scores, for the whole universe of Italian students attending the 5th, 8th and 13th grade of the school cycle during the 2021/22 school year. The analysis is based on a difference-in-difference model in relative time, where the control group is the closest generation before the Covid-19 pandemic. Results suggest a national average loss between 1.8-4.0% in Mathematics and Italian test scores. After collecting the precise number of school closure days for the universe of students in Sicily, this work also estimates that the average days of closure decrease the test score by 2.4%. In this context, parents appear to have a partial compensatory effect, but only when holding higher levels of education and when their children are attending low and middle schools. This is likely explained by the lower relevance of parental inputs and higher reliance on other inputs, such as peers, for the higher grades. Finally, the effects are also heterogeneous across class size, parents' country of birth and job conditions, pointing towards potential growing inequalities driven by the lack of frontal teaching.

We simulate the fiscal stimulus package set up by the German government to alleviate the costs of the COVID-19 pandemic in a dynamic New Keynesian multi-sector general equilibrium model. We find that, cumulated over 2020-2022, output losses relative to steady state can be reduced by more than 6 PP. On average, welfare costs of the pandemic can be mitigated by 11%, or even by 33% for liquidity-constrained households. The long-run present value multiplier of the package amounts to 0.5. Consumption tax cuts and transfers to households primarily stabilize private consumption, and subsidies prevent firm defaults. The most cost-effective measure is an increase in productivity-enhancing public investment. However, it only fully materializes in the medium to long-term. Relative to the respective pandemic impact, some sectors such as the energy and the manufacturing sector benefit above average from the fiscal package, while the effect for some services sectors turns out to be below average.

The COVID-19 pandemic has led to an increase in public debt in most countries, and the Ukraine war is likely to have similar effects. This will increase fiscal pressure in the future. We study how the shape of the optimal nonlinear income tax schedule is affected by this increase. We calibrate the workhorse optimal income tax model to five European countries: France, Germany, Italy, Spain and the UK. Applying an inverse-optimum approach to the pre COVID-19 economies we obtain the Pareto weights implicitly applied by the different countries. We then ask how the schedule of marginal and average tax rates should be optimally adjusted to the increase in fiscal pressure. For all countries, we find that the increase in fiscal pressure leads to a less progressive optimal tax schedule both in terms of marginal and average tax rates.

We estimate the euro area output gap by applying the Beveridge-Nelson decomposition based on a large Bayesian vector autoregression. Our approach incorporates multivariate information through the inclusion of a wide range of variables in the analysis and addresses data issues associated with the COVID-19 pandemic. The estimated output gap lines up well with the CEPR chronology of the business cycle for the euro area and we find that hours worked, more than the unemployment rate, provides the key source of information about labor utilization in the economy, especially in pinning down the depth of the output gap during the COVID-19 recession when the unemployment rate rose only moderately. Our findings confirm that labor market adjustments to the business cycle in the euro area occur more through the intensive, rather than extensive, margin.

We provide a novel modeling framework to decompose euro area sovereign bond yields into five distinct components: ( ) expected future short-term risk-free rates and a term premium, ( ) a default risk premium, ( ) redenomination risk premium, ( ) liquidity risk premium, and ( ) segmentation (convenience) premium. Identification is achieved by considering sovereign yields jointly with other rates, including sovereign credit default swap spreads with and without redenomination as a credit event trigger. We illustrate our model by studying yield components embedded in German, French, Italian, and Spanish sovereign bonds, before and after the onset of the Covid-19 pandemic in 2020, and by examining the impact of European Central Bank (ECB) monetary policy and European Union (EU) fiscal policy announcements in response to the pandemic. We find that all five risk premia became sizable following the onset of the pandemic, and that both monetary and fiscal policy announcements had a pronounced effect on yields, mostly through default, redenomination, and segmentation (convenience) premia.

Risks related to the coronavirus infection differ significantly across the age and the health status of individuals which suggest lockdowns targeting the unhealthy could reduce the fatalities due to the pandemic. In addition, labor productivities differ significantly across these groups, which suggest the economic consequences of targeted lockdowns could be quite different. Using an overlapping generations model with rich heterogeneity, we show that a targeted lockdown policy based on preexisting health status would have reduced the economic severity of the pandemic by 43% compared to a random lockdown. A simple system where government transfers are paid to those who stay home, financed by lump-sum taxes, could have achieved results similar to this health based lockdown.

This paper investigates the effects of the pandemic containment periods in France on individuals' movements, expenditure and adaptation to the shock, using billions of French bank card transactions measured before and during the COVID-19 pandemic. We measure not only the effect on consumer expenditure, but also on quantities directly related to the containment restrictions, such as consumer mobility, number of retailers visited, and inter-regional purchases. The results show large effects on these measures of consumers' movements, as well as on both online and offline measures of expenditure, particularly in the first containment period. We also find evidence that consumers adjusted rapidly during the first containment period, mitigating the effects of mobility restrictions via an increasing shift toward online purchasing, and that the nature of the adaptation differed for different types of purchase.

We incorporate age-specific socio-economic interactions in a SIR macroeconomic model to study the role of demographic factors for the COVID-19 epidemic evolution, its macroeconomic effects and possible containment measures. We capture the endogenous response of rational individuals who choose to reduce inter- and intra-generational social interactions, consumption- and labor-related personal exposure to the virus, while not internalizing the impact of their actions on others. We find that social distancing measures targeted to the elderly (who face higher mortality risk and are not part of the labor force) are best suited to save lives and mitigate output losses. The optimal economic shutdown generates small gains in terms of lives saved and large output losses, for any given type of social distancing. These results are confirmed by calibrating the model to match real epidemic and economic data in the context of a scenario exercise.

We study the link between the revelation of a hitherto non-existent occupational risk - mortality due to the COVID-19 pandemic in 2020 - and subsequent worker behaviour. We link occupation-specific data on COVID-19 mortality to individual level data sets. We find that wages did not adjust, but workers started leaving high-risk occupations during 2020. These effects are stronger for workers not affected by lockdowns or working from home orders and for those considered to be clinically vulnerable to COVID-19 and are not driven by negative health shocks or employer-initiated separations. Occupation-level results suggest that employment began to rebound in 2021.