{"title":"The Economic and Epidemiological Impact of COVID-19 and Government Policies: Part I","authors":"Matthew Famiglietti, Fernando Leibovici","doi":"10.20955/es.2021.14","DOIUrl":"https://doi.org/10.20955/es.2021.14","url":null,"abstract":"","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85082512","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}
Recent research shows that GVCs played a large role in the propagation of foreign shocks on U.S. industries.
最近的研究表明，全球价值链在外国冲击对美国工业的传播中发挥了重要作用。
{"title":"Rethinking Global Value Chains During COVID-19: Part 2","authors":"Ana Maria Santacreu, J. LaBelle","doi":"10.20955/es.2021.17","DOIUrl":"https://doi.org/10.20955/es.2021.17","url":null,"abstract":"Recent research shows that GVCs played a large role in the propagation of foreign shocks on U.S. industries.","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82322559","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}
report caused some consternation in financial markets. Headline inflation for April was 4.2 percent, which is a significant overshoot of the Federal Reserve’s (Fed’s) stated average inflation target of 2.0 percent. Although the Fed uses a personal consumption expenditures (PCE) inflation target, CPI inflation is highly correlated with that PCE target and is seen as a leading indicator of PCE inflation.1 Policymakers acknowledge that the April inflation report is likely picking up transitory effects, as April 2021 prices are compared with April 2020 prices; these were depressed during the height of the pandemic, especially for items such as restaurants, fuel, and hotels. However, the inflation report has stoked fears that the combination of recent fiscal stimulus and accommodative monetary policy has spurred higher prices.
{"title":"Putting Recent Inflation in Historical Context","authors":"Matthew Famiglietti, Carlos Garriga","doi":"10.20955/ES.2021.12","DOIUrl":"https://doi.org/10.20955/ES.2021.12","url":null,"abstract":"report caused some consternation in financial markets. Headline inflation for April was 4.2 percent, which is a significant overshoot of the Federal Reserve’s (Fed’s) stated average inflation target of 2.0 percent. Although the Fed uses a personal consumption expenditures (PCE) inflation target, CPI inflation is highly correlated with that PCE target and is seen as a leading indicator of PCE inflation.1 Policymakers acknowledge that the April inflation report is likely picking up transitory effects, as April 2021 prices are compared with April 2020 prices; these were depressed during the height of the pandemic, especially for items such as restaurants, fuel, and hotels. However, the inflation report has stoked fears that the combination of recent fiscal stimulus and accommodative monetary policy has spurred higher prices.","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"163 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77060589","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}
knowledge creation since the early 1980s, becoming one of the world leaders of innovation. A standard measure of innovation that academics, governments, and businesses use is the number of patents granted. By 2010, the number of new patents granted in the United States was almost three times larger than in 1980.1 A similar trend emerges when looking at new patents granted per 1,000 residents (Figure 1). While the United States has become more innovative overall, not all geographic areas have contributed equally to this upward trend. In this essay, we analyze state-level data on patents granted between 1980 and 2010 and document several features of the geographic distribution of U.S. innovation. First, we find that the rate at which patents are granted is highly heterogeneous across U.S. states. Figure 2 shows the distribution of patent creation across U.S. states in the 1980s (left panel) and 2000s (right panel). Darker colors represent states where patents were created at a faster pace. In the 2000s, patent creation was concentrated mostly in three regions: Geographic Patterns of Innovation Across U.S. States: 1980-2010
{"title":"Geographic Patterns of Innovation Across U.S. States: 1980-2010","authors":"Jesselynn LaBelle, Ana Maria Santacreu","doi":"10.20955/ES.2021.5","DOIUrl":"https://doi.org/10.20955/ES.2021.5","url":null,"abstract":"knowledge creation since the early 1980s, becoming one of the world leaders of innovation. A standard measure of innovation that academics, governments, and businesses use is the number of patents granted. By 2010, the number of new patents granted in the United States was almost three times larger than in 1980.1 A similar trend emerges when looking at new patents granted per 1,000 residents (Figure 1). While the United States has become more innovative overall, not all geographic areas have contributed equally to this upward trend. In this essay, we analyze state-level data on patents granted between 1980 and 2010 and document several features of the geographic distribution of U.S. innovation. First, we find that the rate at which patents are granted is highly heterogeneous across U.S. states. Figure 2 shows the distribution of patent creation across U.S. states in the 1980s (left panel) and 2000s (right panel). Darker colors represent states where patents were created at a faster pace. In the 2000s, patent creation was concentrated mostly in three regions: Geographic Patterns of Innovation Across U.S. States: 1980-2010","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85697507","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}
In Part 1 of this series we described the impact of COVID-19’s spread on economic activity and government policies.1 In contrast, in this essay we show how government policies impact the spread of COVID-19 and economic activity. In particular, we examine policies aimed at controlling the spread of the virus and economic support policies implemented to mitigate the economic cost of the pandemic. Both containment and economic policies were intensely debated up to the widespread availability of vaccinations. Health and containment policies were controversial because they were claimed to lower economic activity to prevent the spread of COVID-19, but their ability to curb the disease was not fully known. And evaluating the trade-off between health and the economy was difficult in real time. Likewise, people asked whether economic support policies were generous enough to address the economic cost of the pandemic or overly generous and too costly. In Famiglietti and Leibovici (2021), we use a statistical model to tease out how COVID-19’s spread, government policies, and economic activity affect each other. We do this by looking at cross-state variation in the intensity of, The Economic and Epidemiological Impact of COVID-19 and Government Policies: Part 2
{"title":"The Economic and Epidemiological Impact of COVID-19 and Government Policies: Part II","authors":"Matthew Famiglietti, Fernando Leibovici","doi":"10.20955/es.2021.15","DOIUrl":"https://doi.org/10.20955/es.2021.15","url":null,"abstract":"In Part 1 of this series we described the impact of COVID-19’s spread on economic activity and government policies.1 In contrast, in this essay we show how government policies impact the spread of COVID-19 and economic activity. In particular, we examine policies aimed at controlling the spread of the virus and economic support policies implemented to mitigate the economic cost of the pandemic. Both containment and economic policies were intensely debated up to the widespread availability of vaccinations. Health and containment policies were controversial because they were claimed to lower economic activity to prevent the spread of COVID-19, but their ability to curb the disease was not fully known. And evaluating the trade-off between health and the economy was difficult in real time. Likewise, people asked whether economic support policies were generous enough to address the economic cost of the pandemic or overly generous and too costly. In Famiglietti and Leibovici (2021), we use a statistical model to tease out how COVID-19’s spread, government policies, and economic activity affect each other. We do this by looking at cross-state variation in the intensity of, The Economic and Epidemiological Impact of COVID-19 and Government Policies: Part 2","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"76 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85652379","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}
Jeffrey P. Cohen, Cletus C. Coughlin, William. R. Emmons, J. Haas, Lowell R. Ricketts
struggling to meet their financial obligations (e.g., making loan payments). Yet housing markets and consumer spending have been strong, and personal bankruptcies and mortgage foreclosures are at multiyear lows. Expansive government policies that include income support, extended unemployment insurance, low interest rates, and relief from default or foreclosure may help explain low levels of reported distress. However, a major concern is that current policy measures are simply postponing rather than eliminating the household distress. To offer some insight, we created a national measure of household distress that allows comparisons over time and the ability to examine the importance of specific variables and policies.1 Perhaps surprisingly, we find that the Measuring Household Distress and Potential Policy Impacts
{"title":"Measuring Household Distress and Potential Policy Impacts","authors":"Jeffrey P. Cohen, Cletus C. Coughlin, William. R. Emmons, J. Haas, Lowell R. Ricketts","doi":"10.20955/ES.2021.3","DOIUrl":"https://doi.org/10.20955/ES.2021.3","url":null,"abstract":"struggling to meet their financial obligations (e.g., making loan payments). Yet housing markets and consumer spending have been strong, and personal bankruptcies and mortgage foreclosures are at multiyear lows. Expansive government policies that include income support, extended unemployment insurance, low interest rates, and relief from default or foreclosure may help explain low levels of reported distress. However, a major concern is that current policy measures are simply postponing rather than eliminating the household distress. To offer some insight, we created a national measure of household distress that allows comparisons over time and the ability to examine the importance of specific variables and policies.1 Perhaps surprisingly, we find that the Measuring Household Distress and Potential Policy Impacts","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"76 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90967906","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}
for economic growth. Companies that adopt better technology can produce more goods and services with fewer inputs. However, in the United States, the adoption of new technologies has been uneven. Firms in big cities have spent more money per employee and a larger share of their total investment budget on new information and communications technology (ICT) than firms in small cities. Rubinton (2020) examines the relationship between ICT spending and city size and finds that the incentives to adopt new technologies will be stronger in bigger cities with abundant skilled labor and in cities with a comparative advantage in using skilled labor.
{"title":"Information and Communications Technology Spending and City Size","authors":"Hannah Rubinton, M. Isaacson","doi":"10.20955/es.2021.7","DOIUrl":"https://doi.org/10.20955/es.2021.7","url":null,"abstract":"for economic growth. Companies that adopt better technology can produce more goods and services with fewer inputs. However, in the United States, the adoption of new technologies has been uneven. Firms in big cities have spent more money per employee and a larger share of their total investment budget on new information and communications technology (ICT) than firms in small cities. Rubinton (2020) examines the relationship between ICT spending and city size and finds that the incentives to adopt new technologies will be stronger in bigger cities with abundant skilled labor and in cities with a comparative advantage in using skilled labor.","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77980057","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}
economy, is measured by the rates at which firms enter the market, grow, and leave the market. Stronger dynamism is related to higher rates of productivity growth, as unproductive firms leave and more productive firms enter or grow (Bartelsman and Doms, 2000). Dynamism in the United States has been decreasing since the 1980s (Decker et. al, 2014), but the change has been distributed unequally. Larger cities have experienced Business Dynamism and City Size
经济是由企业进入市场、成长和退出市场的速度来衡量的。更强的活力与更高的生产率增长率有关，因为非生产性企业离开，生产性企业进入或成长(Bartelsman and Doms, 2000)。自20世纪80年代以来，美国的经济活力一直在下降(Decker et. al .， 2014)，但这种变化的分布并不均匀。较大的城市经历了商业活力和城市规模
{"title":"Business Dynamism and City Size","authors":"Hannah Rubinton","doi":"10.20955/ES.2021.4","DOIUrl":"https://doi.org/10.20955/ES.2021.4","url":null,"abstract":"economy, is measured by the rates at which firms enter the market, grow, and leave the market. Stronger dynamism is related to higher rates of productivity growth, as unproductive firms leave and more productive firms enter or grow (Bartelsman and Doms, 2000). Dynamism in the United States has been decreasing since the 1980s (Decker et. al, 2014), but the change has been distributed unequally. Larger cities have experienced Business Dynamism and City Size","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90101628","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 one: The personal saving rate skyrocketed at the start of the COVID-19-induced recession. The personal saving rate is important for many reasons: Large changes in savings can have big effects on financial markets. Additionally, the personal saving rate might reflect individuals’ expectations about the duration of a recession. People are likely to save more when they expect an economic downturn to last for a long time—the “precautionary” motive for saving. If the downturn is not expected to last, people are likely to use their savings to maintain their consumption; that is, they will keep paying their rent, mortgage, utility bills, etc. Figure 1 shows the U.S. personal saving rate. Shaded areas indicate recessions dated by the National Bureau of Economic Research. The figure offers three points to focus on: First, with the notable exception of 2020, the saving rate changes slowly over time. It was stable in the 1960s and 1970s, declined from the late 1970s until the first half of the 2000s, and then increased again. From 1959 to 2019, the saving rate remained mostly within 4 or 5 percentage Personal Saving During the COVID-19 Recession
在新冠肺炎引发的经济衰退开始时，个人储蓄率飙升。个人储蓄率之所以重要，有很多原因:储蓄的巨大变化会对金融市场产生巨大影响。此外，个人储蓄率可能反映了个人对经济衰退持续时间的预期。当人们预计经济低迷将持续很长一段时间时，他们可能会储蓄更多——这是储蓄的“预防性”动机。如果预计经济低迷不会持续下去，人们可能会用他们的储蓄来维持消费;也就是说，他们将继续支付房租、抵押贷款、水电费等。图1显示了美国的个人储蓄率。阴影区域表示美国国家经济研究局(National Bureau of Economic Research)确定的衰退日期。该数据提供了三点值得关注:首先，除了2020年的显著例外，储蓄率随时间变化缓慢。它在20世纪60年代和70年代保持稳定，从20世纪70年代末到21世纪前半期下降，然后再次上升。从1959年到2019年，在2019冠状病毒病经济衰退期间，储蓄率基本保持在个人储蓄的4%或5%以内
{"title":"Personal Saving During the COVID-19 Recession","authors":"G. Vandenbroucke","doi":"10.20955/ES.2021.2","DOIUrl":"https://doi.org/10.20955/ES.2021.2","url":null,"abstract":"this one: The personal saving rate skyrocketed at the start of the COVID-19-induced recession. The personal saving rate is important for many reasons: Large changes in savings can have big effects on financial markets. Additionally, the personal saving rate might reflect individuals’ expectations about the duration of a recession. People are likely to save more when they expect an economic downturn to last for a long time—the “precautionary” motive for saving. If the downturn is not expected to last, people are likely to use their savings to maintain their consumption; that is, they will keep paying their rent, mortgage, utility bills, etc. Figure 1 shows the U.S. personal saving rate. Shaded areas indicate recessions dated by the National Bureau of Economic Research. The figure offers three points to focus on: First, with the notable exception of 2020, the saving rate changes slowly over time. It was stable in the 1960s and 1970s, declined from the late 1970s until the first half of the 2000s, and then increased again. From 1959 to 2019, the saving rate remained mostly within 4 or 5 percentage Personal Saving During the COVID-19 Recession","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90027163","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 composition of the workforce has implications for the earnings consequences of a job loss and patterns in the job-finding rate.
劳动力的构成对失业的收入后果和求职率的模式有影响。
{"title":"Worker Types, Job Displacement, and Duration Dependence","authors":"Victoria Gregory, G. Menzio, David Wiczer","doi":"10.20955/es.2021.13","DOIUrl":"https://doi.org/10.20955/es.2021.13","url":null,"abstract":"The composition of the workforce has implications for the earnings consequences of a job loss and patterns in the job-finding rate.","PeriodicalId":11402,"journal":{"name":"Economic Synopses","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":"82379418","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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