Vaccination against infectious disease may be beneficial to reduce illness in vaccinated persons and disease transmission across the population. The welfare-economic practice of specifying a social welfare function and considering a planner who seeks to optimize welfare provides a constructive framework to evaluate vaccination policy. This paper characterizes choice of vaccination policy as a planning problem that aims to minimize the social cost of illness and vaccination. Manski (2010, 2017) studied vaccination as a problem of planning under uncertainty, assuming that a planner can choose any vaccination rate or that the planner has only two options: mandate or decentralize vaccination. The analysis focused on uncertainty regarding the effect of vaccination on disease transmission. Here I weaken the assumptions to recognize multiple uncertainties relevant to evaluation of policy for vaccination against COVID-19. These include uncertainty not only about the effect of vaccination on disease transmission, but also about the fraction of susceptible persons in the population, the effectiveness of vaccination in reducing illness and infectiousness, and the health risks associated with vaccination. The paper considers planning under ambiguity using the minimax and minimax-regret criteria, as well as planning using a subjective probability distribution on unknown quantities. It develops algorithms that may be applied flexibly to determine policy choices with specified degrees and types of uncertainty.
{"title":"Vaccination Planning under Uncertainty, with Application to Covid-19","authors":"C. Manski","doi":"10.3386/W28446","DOIUrl":"https://doi.org/10.3386/W28446","url":null,"abstract":"Vaccination against infectious disease may be beneficial to reduce illness in vaccinated persons and disease transmission across the population. The welfare-economic practice of specifying a social welfare function and considering a planner who seeks to optimize welfare provides a constructive framework to evaluate vaccination policy. This paper characterizes choice of vaccination policy as a planning problem that aims to minimize the social cost of illness and vaccination. Manski (2010, 2017) studied vaccination as a problem of planning under uncertainty, assuming that a planner can choose any vaccination rate or that the planner has only two options: mandate or decentralize vaccination. The analysis focused on uncertainty regarding the effect of vaccination on disease transmission. Here I weaken the assumptions to recognize multiple uncertainties relevant to evaluation of policy for vaccination against COVID-19. These include uncertainty not only about the effect of vaccination on disease transmission, but also about the fraction of susceptible persons in the population, the effectiveness of vaccination in reducing illness and infectiousness, and the health risks associated with vaccination. The paper considers planning under ambiguity using the minimax and minimax-regret criteria, as well as planning using a subjective probability distribution on unknown quantities. It develops algorithms that may be applied flexibly to determine policy choices with specified degrees and types of uncertainty.","PeriodicalId":18934,"journal":{"name":"National Bureau of Economic Research","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83190448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dan Goldhaber, Scott A. Imberman, Katharine O. Strunk, B. Hopkins, Nate Brown, Erica Harbatkin, Tara Kilbride
The decision about how and when to open schools to in-person instruction has been a key question for policymakers throughout the COVID-19 pandemic. The instructional modality of schools has implications not only for the health and safety of students and staff, but also student learning and the degree to which parents can engage in job activities. We consider the role of instructional modality (in-person, hybrid, or remote instruction) in disease spread among the wider community. Using a variety of regression modeling strategies , we find that simple correlations show in-person modalities are correlated with increased COVID cases, but accounting for both pre-existing cases and a richer set of covariates brings estimates close to zero on average. In Ordinary Least Squares (OLS) specifications, in-person modality options are not associated with increased spread of COVID at low levels of pre-existing COVID cases but cases do increase at moderate to high pre-existing COVID rates. A bounding exercise suggests that the OLS findings for in-person modality are likely to represent an upper bound on the true relationship. These findings are robust to the inclusion of county and district fixed effects in terms of the insignificance of the findings, but the models with fixed effects are also somewhat imprecisely estimated.
{"title":"To What Extent Does In-Person Schooling Contribute to the Spread of COVID-19? Evidence from Michigan and Washington","authors":"Dan Goldhaber, Scott A. Imberman, Katharine O. Strunk, B. Hopkins, Nate Brown, Erica Harbatkin, Tara Kilbride","doi":"10.3386/W28455","DOIUrl":"https://doi.org/10.3386/W28455","url":null,"abstract":"The decision about how and when to open schools to in-person instruction has been a key question for policymakers throughout the COVID-19 pandemic. The instructional modality of schools has implications not only for the health and safety of students and staff, but also student learning and the degree to which parents can engage in job activities. We consider the role of instructional modality (in-person, hybrid, or remote instruction) in disease spread among the wider community. Using a variety of regression modeling strategies , we find that simple correlations show in-person modalities are correlated with increased COVID cases, but accounting for both pre-existing cases and a richer set of covariates brings estimates close to zero on average. In Ordinary Least Squares (OLS) specifications, in-person modality options are not associated with increased spread of COVID at low levels of pre-existing COVID cases but cases do increase at moderate to high pre-existing COVID rates. A bounding exercise suggests that the OLS findings for in-person modality are likely to represent an upper bound on the true relationship. These findings are robust to the inclusion of county and district fixed effects in terms of the insignificance of the findings, but the models with fixed effects are also somewhat imprecisely estimated.","PeriodicalId":18934,"journal":{"name":"National Bureau of Economic Research","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86859348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I present a behavioral epidemiological model of the evolution of the COVID epidemic in the United States and the United Kingdom over the past 12 months. The model includes the introduction of a new, more contagious variant in the UK in early fall and the US in mid December. The model is behavioral in that activity, and thus transmission, responds endogenously to the daily death rate. I show that with only seasonal variation in the transmission rate and pandemic fatigue modeled as a one-time reduction in the semi-elasticity of the transmission rate to the daily death rate late in the year, the model can reproduce the evolution of daily and cumulative COVID deaths in the both countries from Feb 15, 2020 to the present remarkably well. I find that most of the end-of-year surge in deaths in both the US and the UK was generated by pandemic fatigue and not the new variant of the virus. I then generate fore- casts for the evolution of the epidemic over the next two years with continuing seasonality, pandemic fatigue, and spread of the new variant.
{"title":"A Parsimonious Behavioral SEIR Model of the 2020 COVID Epidemic in the United States and the United Kingdom","authors":"A. Atkeson","doi":"10.3386/W28434","DOIUrl":"https://doi.org/10.3386/W28434","url":null,"abstract":"I present a behavioral epidemiological model of the evolution of the COVID epidemic in the United States and the United Kingdom over the past 12 months. The model includes the introduction of a new, more contagious variant in the UK in early fall and the US in mid December. The model is behavioral in that activity, and thus transmission, responds endogenously to the daily death rate. I show that with only seasonal variation in the transmission rate and pandemic fatigue modeled as a one-time reduction in the semi-elasticity of the transmission rate to the daily death rate late in the year, the model can reproduce the evolution of daily and cumulative COVID deaths in the both countries from Feb 15, 2020 to the present remarkably well. I find that most of the end-of-year surge in deaths in both the US and the UK was generated by pandemic fatigue and not the new variant of the virus. I then generate fore- casts for the evolution of the epidemic over the next two years with continuing seasonality, pandemic fatigue, and spread of the new variant.","PeriodicalId":18934,"journal":{"name":"National Bureau of Economic Research","volume":"129 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79577492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
On January 6, 2021, the U.S. Capitol was sieged by rioters protesting certification of Joseph R. Biden’s election as the 46th president of the United States. The Director of the Centers for Disease Control and Prevention (CDC) quickly predicted that the Riot would be a COVID-19 “surge event.” This study is the first to estimate the impact of the Capitol Riot on risk-averting behavior and community-level spread of the novel coronavirus. First, using anonymized smartphone data from SafeGraph, Inc. and an event-study approach, we document that on January 6th there was a substantial increase in non-resident smartphone pings in the census block groups including the Ellipse, the National Mall, and the U.S. Capitol Building, consistent with a large protest that day. Next, using data from the same source and a synthetic control approach, we find that the Capitol Riot increased stay-at-home behavior among District of Columbia residents, indicative of risk averting behaviors in response to violence and health risks. Finally, turning to COVID-19 case data, we find no evidence that the Capitol Riot substantially increased community spread of COVID-19 in the District of Columbia in the month-long period following the event. This may be due to increases in social distancing and a “virtual lockdown” of the Capitol prior to the inauguration of the new president. However, exploiting variation in non-resident smartphone inflows into the January 6 Capitol protest, we find that counties with the highest protester inflows experienced a significant increase in the rate of daily cumulative COVID-19 case growth in the month following the protest. We conclude that the Capitol Riot may have contributed to non-localized COVID-19 spread.
{"title":"Political Violence, Risk Aversion, and Non-Localized Disease Spread: Evidence from the U.S. Capitol Riot","authors":"Dhaval M. Dave, Drew McNichols, Joseph J. Sabia","doi":"10.3386/W28410","DOIUrl":"https://doi.org/10.3386/W28410","url":null,"abstract":"On January 6, 2021, the U.S. Capitol was sieged by rioters protesting certification of Joseph R. Biden’s election as the 46th president of the United States. The Director of the Centers for Disease Control and Prevention (CDC) quickly predicted that the Riot would be a COVID-19 “surge event.” This study is the first to estimate the impact of the Capitol Riot on risk-averting behavior and community-level spread of the novel coronavirus. First, using anonymized smartphone data from SafeGraph, Inc. and an event-study approach, we document that on January 6th there was a substantial increase in non-resident smartphone pings in the census block groups including the Ellipse, the National Mall, and the U.S. Capitol Building, consistent with a large protest that day. Next, using data from the same source and a synthetic control approach, we find that the Capitol Riot increased stay-at-home behavior among District of Columbia residents, indicative of risk averting behaviors in response to violence and health risks. Finally, turning to COVID-19 case data, we find no evidence that the Capitol Riot substantially increased community spread of COVID-19 in the District of Columbia in the month-long period following the event. This may be due to increases in social distancing and a “virtual lockdown” of the Capitol prior to the inauguration of the new president. However, exploiting variation in non-resident smartphone inflows into the January 6 Capitol protest, we find that counties with the highest protester inflows experienced a significant increase in the rate of daily cumulative COVID-19 case growth in the month following the protest. We conclude that the Capitol Riot may have contributed to non-localized COVID-19 spread.","PeriodicalId":18934,"journal":{"name":"National Bureau of Economic Research","volume":"114 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88144700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The expiration of the temporary $600 boost to weekly UI benefits under the Federal Pandemic Unemployment Compensation (FPUC) led to a sharp, unprecedented, 98 percentage point reduction (on average) in the replacement rate during a time when employment was recovering during the Covid recession. Leveraging the considerable variation in this drop across states, I use a difference-in-differences event study design to estimate the macro employment effects. I find little impact of job gains from the benefit reduction, especially when I focus on groups (non-college graduates, and those from non-high-income households) that comprise of most UI recipients. The estimates rule out job gains implied by much of the micro UI duration elasticities from the existing literature.
{"title":"Aggregate Employment Effects of Unemployment Benefits During Deep Downturns: Evidence from the Expiration of the Federal Pandemic Unemployment Compensation","authors":"Arindrajit Dubé","doi":"10.3386/W28470","DOIUrl":"https://doi.org/10.3386/W28470","url":null,"abstract":"The expiration of the temporary $600 boost to weekly UI benefits under the Federal Pandemic Unemployment Compensation (FPUC) led to a sharp, unprecedented, 98 percentage point reduction (on average) in the replacement rate during a time when employment was recovering during the Covid recession. Leveraging the considerable variation in this drop across states, I use a difference-in-differences event study design to estimate the macro employment effects. I find little impact of job gains from the benefit reduction, especially when I focus on groups (non-college graduates, and those from non-high-income households) that comprise of most UI recipients. The estimates rule out job gains implied by much of the micro UI duration elasticities from the existing literature.","PeriodicalId":18934,"journal":{"name":"National Bureau of Economic Research","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89052590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper estimates housing choice differences between households with and without remote workers. Prior to the pandemic, the expenditure share on housing was more than seven percent higher for remote households compared to similar non-remote households in the same commuting zone. Remote households’ higher housing expenditures arise from larger dwellings (more rooms) and a higher price per room. Pre-COVID, households with remote workers were actually located in areas with above-average housing costs, and sorting within-commuting zone to suburban or rural areas was not economically meaningful. Using the pre-COVID distribution of locations, we estimate how much additional pre-tax income would be necessary to compensate non-remote households for extra housing expenses arising from remote work in the absence of geographic mobility, and we compare this compensation to commercial office rents in major metro areas.
{"title":"Housing Consumption and the Cost of Remote Work","authors":"Christopher Stanton, P. Tiwari","doi":"10.3386/W28483","DOIUrl":"https://doi.org/10.3386/W28483","url":null,"abstract":"This paper estimates housing choice differences between households with and without remote workers. Prior to the pandemic, the expenditure share on housing was more than seven percent higher for remote households compared to similar non-remote households in the same commuting zone. Remote households’ higher housing expenditures arise from larger dwellings (more rooms) and a higher price per room. Pre-COVID, households with remote workers were actually located in areas with above-average housing costs, and sorting within-commuting zone to suburban or rural areas was not economically meaningful. Using the pre-COVID distribution of locations, we estimate how much additional pre-tax income would be necessary to compensate non-remote households for extra housing expenses arising from remote work in the absence of geographic mobility, and we compare this compensation to commercial office rents in major metro areas.","PeriodicalId":18934,"journal":{"name":"National Bureau of Economic Research","volume":"68 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84159778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper estimates the relationship between investments in five distributed generation technologies and hourly net injections to the distribution grid for over 2,000 substations in France between 2005 and 2018. We find that investments in distributed wind and solar capacity have little or no impact on the annual peak of hourly net injections to the distribution grid, while investments in hydroelectric and thermal distributed generation significantly reduce it. An optimistic analysis of battery storage suggests that high levels of investments are required for distributed wind and solar investments to deliver similar reductions in the annual peak of hourly net injections.
{"title":"What Kinds of Distributed Generation Technologies Defer Network Expansions? Evidence from France","authors":"N. Astier, R. Rajagopal, F. Wolak","doi":"10.3386/W28822","DOIUrl":"https://doi.org/10.3386/W28822","url":null,"abstract":"This paper estimates the relationship between investments in five distributed generation technologies and hourly net injections to the distribution grid for over 2,000 substations in France between 2005 and 2018. We find that investments in distributed wind and solar capacity have little or no impact on the annual peak of hourly net injections to the distribution grid, while investments in hydroelectric and thermal distributed generation significantly reduce it. An optimistic analysis of battery storage suggests that high levels of investments are required for distributed wind and solar investments to deliver similar reductions in the annual peak of hourly net injections.","PeriodicalId":18934,"journal":{"name":"National Bureau of Economic Research","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77568079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
COVID-19 led to a massive shutdown of businesses in the second quarter of 2020. Estimates from the CPS, for example, indicate that the number of active business owners dropped by 22 percent from February to April 2020. In this descriptive research note, we provide the first analysis of losses in sales and revenues among the universe of businesses in California using administrative data from the California Department of Tax and Fee Administration. The losses in sales average 17 percent in the second quarter of 2020 relative to the second quarter of 2019 even though year-over-year sales typically grow by 3-4 percent. We find that sales losses were largest in businesses affected by mandatory lockdowns such as Accommodations, which lost 91 percent, whereas online sales grew by 180 percent. Losses also differed substantially across counties with large losses in San Francisco (50 percent) and Los Angeles (24 percent) whereas some counties experienced small gains in sales. Placing business types into different categories based on whether they were essential or non-essential (and thus subject to early lockdowns) and whether they have a moderate or high level of person-to-person contact, we find interesting correlations between sales losses and COVID-19 cases per capita across counties in California. The results suggest that local implementation and enforcement of lockdown restrictions and voluntary behavioral responses as reactions to the perceived local COVID-19 spread both played a role, but enforcement of mandatory restrictions may have had a larger impact on sales losses.
{"title":"Sales Losses in the First Quarter of the COVID-19 Pandemic: Evidence from California Administrative Data","authors":"R. Fairlie, Frank M. Fossen","doi":"10.3386/W28414","DOIUrl":"https://doi.org/10.3386/W28414","url":null,"abstract":"COVID-19 led to a massive shutdown of businesses in the second quarter of 2020. Estimates from the CPS, for example, indicate that the number of active business owners dropped by 22 percent from February to April 2020. In this descriptive research note, we provide the first analysis of losses in sales and revenues among the universe of businesses in California using administrative data from the California Department of Tax and Fee Administration. The losses in sales average 17 percent in the second quarter of 2020 relative to the second quarter of 2019 even though year-over-year sales typically grow by 3-4 percent. We find that sales losses were largest in businesses affected by mandatory lockdowns such as Accommodations, which lost 91 percent, whereas online sales grew by 180 percent. Losses also differed substantially across counties with large losses in San Francisco (50 percent) and Los Angeles (24 percent) whereas some counties experienced small gains in sales. Placing business types into different categories based on whether they were essential or non-essential (and thus subject to early lockdowns) and whether they have a moderate or high level of person-to-person contact, we find interesting correlations between sales losses and COVID-19 cases per capita across counties in California. The results suggest that local implementation and enforcement of lockdown restrictions and voluntary behavioral responses as reactions to the perceived local COVID-19 spread both played a role, but enforcement of mandatory restrictions may have had a larger impact on sales losses.","PeriodicalId":18934,"journal":{"name":"National Bureau of Economic Research","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76910625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Exploiting a large migration of farmers to the West of Brazil between 1950 and 2010, we study how migration shapes aggregate and regional comparative advantage. We document that farmers emigrating from regions with high employment in an activity are more likely to work in that activity and have higher income than other migrants doing so. We incorporate this heterogeneity into a quantitative model and find that, by reshaping comparative advantage, declines in migration costs contributed substantially to Brazil's rise as a leading commodity exporter. Opportunities to migrate, moreover, account for a substantial share of the gains from trade.
{"title":"Migration, Specialization, and Trade: Evidence from Brazil's March to the West","authors":"Heitor S. Pellegrina, Sebastian Sotelo","doi":"10.3386/W28421","DOIUrl":"https://doi.org/10.3386/W28421","url":null,"abstract":"Exploiting a large migration of farmers to the West of Brazil between 1950 and 2010, we study how migration shapes aggregate and regional comparative advantage. We document that farmers emigrating from regions with high employment in an activity are more likely to work in that activity and have higher income than other migrants doing so. We incorporate this heterogeneity into a quantitative model and find that, by reshaping comparative advantage, declines in migration costs contributed substantially to Brazil's rise as a leading commodity exporter. Opportunities to migrate, moreover, account for a substantial share of the gains from trade.","PeriodicalId":18934,"journal":{"name":"National Bureau of Economic Research","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85219287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pierre-Olivier Gourinchas, Ṣebnem Kalemli-Özcan, Veronika Penciakova, N. Sander
This paper assesses the prospects of a 2021 time bomb in SME failures triggered by the generous support policies enacted during the 2020 COVID-19 crisis. Policies implemented in 2020, on their own, do not create a 2021 “time-bomb” for SMEs. Rather, business failures and policy costs remain modest. By contrast, credit contraction poses a significant risk. Such a contraction would disproportionately impact firms that could survive COVID-19 in 2020 without any fiscal support. Even in that scenario, most business failures would not arise from excessively generous 2020 policies, but rather from the contraction of credit to the corporate sector.
{"title":"COVID-19 and SMEs: A 2021 \"Time Bomb\"?","authors":"Pierre-Olivier Gourinchas, Ṣebnem Kalemli-Özcan, Veronika Penciakova, N. Sander","doi":"10.3386/W28418","DOIUrl":"https://doi.org/10.3386/W28418","url":null,"abstract":"This paper assesses the prospects of a 2021 time bomb in SME failures triggered by the generous support policies enacted during the 2020 COVID-19 crisis. Policies implemented in 2020, on their own, do not create a 2021 “time-bomb” for SMEs. Rather, business failures and policy costs remain modest. By contrast, credit contraction poses a significant risk. Such a contraction would disproportionately impact firms that could survive COVID-19 in 2020 without any fiscal support. Even in that scenario, most business failures would not arise from excessively generous 2020 policies, but rather from the contraction of credit to the corporate sector.","PeriodicalId":18934,"journal":{"name":"National Bureau of Economic Research","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82657842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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