The paper byCovarrubias, Gutiérrez, and Philippon providesmany useful insights into the rapidly emerging literature on rising concentration in US industries. Importantly, it catalogs some important empirical shortcomings in the literature. It also provides clarity on conceptual issues that have created confusion. The paper goes on to make two types of original empirical contributions. In the first, it focuses on two categories of explanations for rising concentration: “good” and “bad.” The former is associated with technological change that increases the elasticity of substitution among goods (j, and hence greater competition) or increases firms’ accumulation of intangible capital (g, perhaps associated with network externalities and returns to scale). Bad concentration is instead associated with rising barriers to entry, k. The authors argue that the data tend to favor good concentration earlier in their data sample—through 2000. Thereafter, there is increasing evidence of barriers to competition. The collection of evidence, while not dispositive, moves the weight of the evidence toward market power explanations, especially later in the sample. The last part of the paper takes a different tack. Instead of looking for indicators ofmarket power to explain a broad range of facts, the paper looks at combinations of explanations by industry and argues that there is merit in several of them and that the results vary by industry. I will argue that these last insights are especially helpful, as the macroeconomic data are unlikely to be captured by a single simple narrative.
{"title":"Comment","authors":"Janice C. Eberly","doi":"10.1086/707170","DOIUrl":"https://doi.org/10.1086/707170","url":null,"abstract":"The paper byCovarrubias, Gutiérrez, and Philippon providesmany useful insights into the rapidly emerging literature on rising concentration in US industries. Importantly, it catalogs some important empirical shortcomings in the literature. It also provides clarity on conceptual issues that have created confusion. The paper goes on to make two types of original empirical contributions. In the first, it focuses on two categories of explanations for rising concentration: “good” and “bad.” The former is associated with technological change that increases the elasticity of substitution among goods (j, and hence greater competition) or increases firms’ accumulation of intangible capital (g, perhaps associated with network externalities and returns to scale). Bad concentration is instead associated with rising barriers to entry, k. The authors argue that the data tend to favor good concentration earlier in their data sample—through 2000. Thereafter, there is increasing evidence of barriers to competition. The collection of evidence, while not dispositive, moves the weight of the evidence toward market power explanations, especially later in the sample. The last part of the paper takes a different tack. Instead of looking for indicators ofmarket power to explain a broad range of facts, the paper looks at combinations of explanations by industry and argues that there is merit in several of them and that the results vary by industry. I will argue that these last insights are especially helpful, as the macroeconomic data are unlikely to be captured by a single simple narrative.","PeriodicalId":51680,"journal":{"name":"Nber Macroeconomics Annual","volume":"34 1","pages":"47 - 54"},"PeriodicalIF":7.7,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1086/707170","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60709639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The NBER’s thirty-fourth Annual Conference on Macroeconomics brought together leading scholars to present, discuss, and debate six research papers on central issues in contemporary macroeconomics. In addition, James Stock, former chief economist and director of research at the International Monetary Fund, delivered a thought-provoking afterdinner talk on the economics of climate change. Video recordings of the presentations of the papers and the after-dinner talk are all accessible on the web page of the NBER Annual Conference on Macroeconomics (https:// www.nber.org/macroannualconference2019/macroannual2019.html). These videos,whichmake the content of the conferencemorewidely accessible, are a useful complement to this volume. This conference volume contains edited versions of the six papers presented at the conference, each followed by two written comments by leading scholars and a summary discussion of the debates that followed each paper. The volume also contains a paper, “Climate Change, Climate Policy, and Economic Growth,” by James Stock, based on his dinner talk. The paper provides an extremely useful introduction to the topic of climate change and climate change policy formacroeconomists. The paper makes four key points. First, simple time-series regression models confirm that essentially all the warming over the past 140 years is due to human activity. Second, policy has a crucial role toplay ifwe are to succeed in decarbonizing the economy. Third, current policies will not succeed in decarbonizing the economy in time to prevent severe damage from climate change. Fourth, the politics, as opposed to the economics, of Pigouvian carbon pricing do notwork. This suggests the importance of considering other policies, especially those that drive low-carbon technical innovation. There was no discussant for the paper because of its origin as a dinner talk. We are grateful to James Stock for taking the time to write up his comments on this vitally important topic.
{"title":"Editorial","authors":"M. Eichenbaum, Erik Hurst, J. Parker","doi":"10.1086/707168","DOIUrl":"https://doi.org/10.1086/707168","url":null,"abstract":"The NBER’s thirty-fourth Annual Conference on Macroeconomics brought together leading scholars to present, discuss, and debate six research papers on central issues in contemporary macroeconomics. In addition, James Stock, former chief economist and director of research at the International Monetary Fund, delivered a thought-provoking afterdinner talk on the economics of climate change. Video recordings of the presentations of the papers and the after-dinner talk are all accessible on the web page of the NBER Annual Conference on Macroeconomics (https:// www.nber.org/macroannualconference2019/macroannual2019.html). These videos,whichmake the content of the conferencemorewidely accessible, are a useful complement to this volume. This conference volume contains edited versions of the six papers presented at the conference, each followed by two written comments by leading scholars and a summary discussion of the debates that followed each paper. The volume also contains a paper, “Climate Change, Climate Policy, and Economic Growth,” by James Stock, based on his dinner talk. The paper provides an extremely useful introduction to the topic of climate change and climate change policy formacroeconomists. The paper makes four key points. First, simple time-series regression models confirm that essentially all the warming over the past 140 years is due to human activity. Second, policy has a crucial role toplay ifwe are to succeed in decarbonizing the economy. Third, current policies will not succeed in decarbonizing the economy in time to prevent severe damage from climate change. Fourth, the politics, as opposed to the economics, of Pigouvian carbon pricing do notwork. This suggests the importance of considering other policies, especially those that drive low-carbon technical innovation. There was no discussant for the paper because of its origin as a dinner talk. We are grateful to James Stock for taking the time to write up his comments on this vitally important topic.","PeriodicalId":51680,"journal":{"name":"Nber Macroeconomics Annual","volume":"34 1","pages":"xi - xviii"},"PeriodicalIF":7.7,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1086/707168","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43584113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Individuals without a college degree in the United States have experienced a relative decline in labor market and other opportunities. This is especially the case for lower-educated white men who entered the labor market in the early 1980s and after. These trends are not exclusive to the United States; in theUnitedKingdom and elsewhere, thosewithout a college degree have fared poorly since the early 1980s. For the United States, the raw statistics point to one of the largest declines for developed economies. There has been a fall in (relative) real earnings for the low educated, especially white men. There appears to be almost no wage progression over the working life for low-educated men and women. There is strong assortativeness by wages in marriage such that the increasing labor market participation of women has not offset the growth in earnings inequality for couple households. In addition, medical costs have risen, especially in terms of social care, and perhaps most surprisingly, mortality has risen. Motivated by these trends, the authors specify a life-cycle model that includes marriage and divorce, human capital accumulation, medical expenditures, and changing life expectancy. They use data from the Panel Study of Income Dynamics and the Health and Retirement Survey to construct a sample of white, non-college-educated Americans. Sample moments are then used to estimate the model. Counterfactual simulations are then used to ask: What if the 1940s cohort of non-college-educated white Americans had experienced the wages, the medical expenses, and the mortality of the 1960s cohort? The “what if” is for labor market participation, hours, savings, and welfare. In this discussion, I first examine the trends in outcomes for these different groups over this period in the United States. I then briefly run
{"title":"Comment","authors":"R. Blundell","doi":"10.1086/707174","DOIUrl":"https://doi.org/10.1086/707174","url":null,"abstract":"Individuals without a college degree in the United States have experienced a relative decline in labor market and other opportunities. This is especially the case for lower-educated white men who entered the labor market in the early 1980s and after. These trends are not exclusive to the United States; in theUnitedKingdom and elsewhere, thosewithout a college degree have fared poorly since the early 1980s. For the United States, the raw statistics point to one of the largest declines for developed economies. There has been a fall in (relative) real earnings for the low educated, especially white men. There appears to be almost no wage progression over the working life for low-educated men and women. There is strong assortativeness by wages in marriage such that the increasing labor market participation of women has not offset the growth in earnings inequality for couple households. In addition, medical costs have risen, especially in terms of social care, and perhaps most surprisingly, mortality has risen. Motivated by these trends, the authors specify a life-cycle model that includes marriage and divorce, human capital accumulation, medical expenditures, and changing life expectancy. They use data from the Panel Study of Income Dynamics and the Health and Retirement Survey to construct a sample of white, non-college-educated Americans. Sample moments are then used to estimate the model. Counterfactual simulations are then used to ask: What if the 1940s cohort of non-college-educated white Americans had experienced the wages, the medical expenses, and the mortality of the 1960s cohort? The “what if” is for labor market participation, hours, savings, and welfare. In this discussion, I first examine the trends in outcomes for these different groups over this period in the United States. I then briefly run","PeriodicalId":51680,"journal":{"name":"Nber Macroeconomics Annual","volume":"34 1","pages":"116 - 126"},"PeriodicalIF":7.7,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1086/707174","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44169425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This chapter discusses the empirical results, adds additional results, and compares derived insights to other scientific conclusions from the domain of behavioral economics. The first subchapter sums up understandings of agent behavior by the results of the various hypotheses, and includes further results from statistical analyses.
{"title":"Discussion","authors":"U. Strunz","doi":"10.1086/718657","DOIUrl":"https://doi.org/10.1086/718657","url":null,"abstract":"This chapter discusses the empirical results, adds additional results, and compares derived insights to other scientific conclusions from the domain of behavioral economics. The first subchapter sums up understandings of agent behavior by the results of the various hypotheses, and includes further results from statistical analyses.","PeriodicalId":51680,"journal":{"name":"Nber Macroeconomics Annual","volume":"36 1","pages":"80 - 81"},"PeriodicalIF":7.7,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46610808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In 2008, for the first time since the Great Depression, the Federal Reserve encountered the zero lower bound (ZLB) on the nominal interest rate. The Fed’s target rate, the overnight federal funds rate, fell effectively to zero in the fall as the central bank’s emergency lending programs rapidly increased the supply of bank reserves. Then at its December 2008 meeting, the FederalOpenMarketCommittee (FOMC), the Fed’smonetary policymaking body, formally set the target range for the funds rate at 0 to 25 basis points—effectively zero. With the economy in free fall and little scope for additional rate cuts, the FOMC then turned to nonstandard policy tools, including forward guidance (communication about the likely or intended forward path of the policy rate) and large-scale asset purchases, also known as quantitative easing. Both tools were used actively during the Great Recession and the subsequent recovery. Did the nonstandard tools work? The current consensus of central bankers and economists is that forward guidance and asset purchases eased financial conditions and supported the economy, with fewer adverse side effects than many predicted. Accordingly, these policies appear to have become permanent components of the monetary tool kit, both in the United States and abroad. However, the prevailing view also holds that the overall response of monetary policy was effectively constrained by the ZLB; that is, although nonstandard policies evidentlymitigated the downturn, their use did not fully compensate for the inability of the Fed to cut short-term rates significantly further. This view, and the concern that in a world of low neutral interest rates future encounters with the ZLB may be frequent, has led the Fed and other central banks to actively consider new tools and new policy frameworks for dealing with the ZLB constraint. In contrast to this prevailing view, however, a small literature has adduced indirect evidence to argue that the Fed’s response to the Great
{"title":"Comment","authors":"B. Bernanke","doi":"10.1086/707178","DOIUrl":"https://doi.org/10.1086/707178","url":null,"abstract":"In 2008, for the first time since the Great Depression, the Federal Reserve encountered the zero lower bound (ZLB) on the nominal interest rate. The Fed’s target rate, the overnight federal funds rate, fell effectively to zero in the fall as the central bank’s emergency lending programs rapidly increased the supply of bank reserves. Then at its December 2008 meeting, the FederalOpenMarketCommittee (FOMC), the Fed’smonetary policymaking body, formally set the target range for the funds rate at 0 to 25 basis points—effectively zero. With the economy in free fall and little scope for additional rate cuts, the FOMC then turned to nonstandard policy tools, including forward guidance (communication about the likely or intended forward path of the policy rate) and large-scale asset purchases, also known as quantitative easing. Both tools were used actively during the Great Recession and the subsequent recovery. Did the nonstandard tools work? The current consensus of central bankers and economists is that forward guidance and asset purchases eased financial conditions and supported the economy, with fewer adverse side effects than many predicted. Accordingly, these policies appear to have become permanent components of the monetary tool kit, both in the United States and abroad. However, the prevailing view also holds that the overall response of monetary policy was effectively constrained by the ZLB; that is, although nonstandard policies evidentlymitigated the downturn, their use did not fully compensate for the inability of the Fed to cut short-term rates significantly further. This view, and the concern that in a world of low neutral interest rates future encounters with the ZLB may be frequent, has led the Fed and other central banks to actively consider new tools and new policy frameworks for dealing with the ZLB constraint. In contrast to this prevailing view, however, a small literature has adduced indirect evidence to argue that the Fed’s response to the Great","PeriodicalId":51680,"journal":{"name":"Nber Macroeconomics Annual","volume":"34 1","pages":"171 - 181"},"PeriodicalIF":7.7,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1086/707178","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42971193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently, I had a dream where I was trying to explain supply and demand to an audience of intransigent economists.How could I say that demand curves sloped downward, they asked, when for so many goods, a simple plot of quantity demanded against price showed the opposite? How could these curves be useful concepts when, even by the most generous account, their parameters shifted from year to year? I knew the answers. The incorrect slope of demand was no surprise; a plot of quantities against prices would reveal the demand curve only if the variation was caused by supply shocks. And yes, supply and demand didmove around from year to year, but this did not invalidate the concepts. If I am selling oil, I can predict that a sudden decline in supply (embargo) will increase the price, I can predict that a new source of supply (fracking) will decrease the price, and I can predict that a decline in demand (fuel efficiency) will decrease the price. All of this is useful information. The dream audience was unmoved. But upon waking up, I was relieved to find myself in a world where economists are not so silly. We understand that supply and demand is a useful framework, even if there is an identification problem and even if there is no consensus on the parameters for a particular market. In fact, we persist even in the face of more profound theoretical complications, like imperfect competition or increasing returns. Then I started reading commentary on the Phillips curve and economists started seeming awfully silly again. Somehow, a weak reducedform relationship in the aggregate data has led many people to deny the Phillips curve as a structural relationship. In the face of this criticism, McLeay and Tenreyro’s paper is a vitally important rejoinder.
{"title":"Comment","authors":"M. Rognlie","doi":"10.1086/707183","DOIUrl":"https://doi.org/10.1086/707183","url":null,"abstract":"Recently, I had a dream where I was trying to explain supply and demand to an audience of intransigent economists.How could I say that demand curves sloped downward, they asked, when for so many goods, a simple plot of quantity demanded against price showed the opposite? How could these curves be useful concepts when, even by the most generous account, their parameters shifted from year to year? I knew the answers. The incorrect slope of demand was no surprise; a plot of quantities against prices would reveal the demand curve only if the variation was caused by supply shocks. And yes, supply and demand didmove around from year to year, but this did not invalidate the concepts. If I am selling oil, I can predict that a sudden decline in supply (embargo) will increase the price, I can predict that a new source of supply (fracking) will decrease the price, and I can predict that a decline in demand (fuel efficiency) will decrease the price. All of this is useful information. The dream audience was unmoved. But upon waking up, I was relieved to find myself in a world where economists are not so silly. We understand that supply and demand is a useful framework, even if there is an identification problem and even if there is no consensus on the parameters for a particular market. In fact, we persist even in the face of more profound theoretical complications, like imperfect competition or increasing returns. Then I started reading commentary on the Phillips curve and economists started seeming awfully silly again. Somehow, a weak reducedform relationship in the aggregate data has led many people to deny the Phillips curve as a structural relationship. In the face of this criticism, McLeay and Tenreyro’s paper is a vitally important rejoinder.","PeriodicalId":51680,"journal":{"name":"Nber Macroeconomics Annual","volume":"34 1","pages":"267 - 279"},"PeriodicalIF":7.7,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1086/707183","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46376775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
December 18, 2018,marked the fortieth anniversary of the Third Plenary Session of the Eleventh Central Committee of the Chinese Communist Party (CCP), at which Deng Xiaoping launched China on its remarkable recent trajectory of economic growth. By giving greater play over time to market forces, Deng’s reform and opening initiative spurred rapid income convergence. But it did so while preserving the CCP’s political monopoly. As figure 1 shows, China’s real gross domestic product (GDP) growth (insofar as the official data are accurate) has been high on average although anything but smooth. Moreover, it has declined markedly since the last year of double-digit growth in 2010 and even more so since the heady precrisis peak. China’s politics have not evolved monotonically either. The year 2019 marked the thirtieth anniversary of the Tiananmen protests, sparked by the (vain) hope that China’s economic evolution would encourage a commensurate political evolution. Chinese politics—and, I argue, economics— have only regressed under the more authoritarian rule of President Xiaoping Xi. In this paper, Chong-en Bai, Chang-Tai Hsieh, and Zheng Song likewise link China’s falling growth rate over the past decade to political factors, but I emphasize a set of factors different from the one that they highlight. What mechanism linking politics to growth do the authors emphasize? In his speech commemorating the fortieth anniversary of Deng’s reforms, President Xi stated that “we will resolutely reform what should and can be reformed, and make no change where there should not and cannot be any reform.” An alternative title for this paper could have been “Chinese Cronyism: Can It Be Changed? Should It Be Changed?” The authors’mainmessage is that cronyism is deeply ingrained inChina’smode
{"title":"Comment","authors":"M. Obstfeld","doi":"10.1086/707190","DOIUrl":"https://doi.org/10.1086/707190","url":null,"abstract":"December 18, 2018,marked the fortieth anniversary of the Third Plenary Session of the Eleventh Central Committee of the Chinese Communist Party (CCP), at which Deng Xiaoping launched China on its remarkable recent trajectory of economic growth. By giving greater play over time to market forces, Deng’s reform and opening initiative spurred rapid income convergence. But it did so while preserving the CCP’s political monopoly. As figure 1 shows, China’s real gross domestic product (GDP) growth (insofar as the official data are accurate) has been high on average although anything but smooth. Moreover, it has declined markedly since the last year of double-digit growth in 2010 and even more so since the heady precrisis peak. China’s politics have not evolved monotonically either. The year 2019 marked the thirtieth anniversary of the Tiananmen protests, sparked by the (vain) hope that China’s economic evolution would encourage a commensurate political evolution. Chinese politics—and, I argue, economics— have only regressed under the more authoritarian rule of President Xiaoping Xi. In this paper, Chong-en Bai, Chang-Tai Hsieh, and Zheng Song likewise link China’s falling growth rate over the past decade to political factors, but I emphasize a set of factors different from the one that they highlight. What mechanism linking politics to growth do the authors emphasize? In his speech commemorating the fortieth anniversary of Deng’s reforms, President Xi stated that “we will resolutely reform what should and can be reformed, and make no change where there should not and cannot be any reform.” An alternative title for this paper could have been “Chinese Cronyism: Can It Be Changed? Should It Be Changed?” The authors’mainmessage is that cronyism is deeply ingrained inChina’smode","PeriodicalId":51680,"journal":{"name":"Nber Macroeconomics Annual","volume":"34 1","pages":"380 - 388"},"PeriodicalIF":7.7,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1086/707190","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49009707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The topics of climate change and climate change policy encompass a complex mixture of the natural sciences, economics, and a mass of institutional, legal, and technical details. This complexity and multidisciplinary nature make it difficult for thoughtful citizens to reach their own conclusions on the topic and for potentially interested economists to know where to start. This essay aims to provide a point of entry formacroeconomists interested in climate change and climate change policy but with no special knowledge of the field. I therefore start at the beginning, with some basic background on climate change, presented through the eyes of an econometrician. I then turn to climate policy in the United States. That discussion points to a large number of researchable open questions that macroeconomists are particularly well suited to tackle. Let me summarize my four main points. First, although a healthy dose of skepticism is always in order (as academics it is in our DNA), simple and transparent time series regression models familiar to macroeconomists provide independent verification of some key conclusions from climate science models and in particular confirm that essentially all the warming over the past 140 years is because of human activity, that is, is anthropogenic. Figure 1 shows time series data on annual global mean temperature since 1860, when reliable instrumental records start. As seen in the figure, the global mean temperature has increased by approximately 1 degree Celsius, compared with its 1870–90 average value. This increase in temperatures drives a wide range of changes in climate, including droughts, more hot days, and more intense rainfalls and storms, all of which vary regionally. Because climate science uses large, opaque calibrated models of the climate system, there is room for confusion among legitimately skeptical outsiders about just howmuch of the global warming observed since the industrial revolution results from human
{"title":"Climate Change, Climate Policy, and Economic Growth","authors":"J. Stock","doi":"10.1086/707193","DOIUrl":"https://doi.org/10.1086/707193","url":null,"abstract":"The topics of climate change and climate change policy encompass a complex mixture of the natural sciences, economics, and a mass of institutional, legal, and technical details. This complexity and multidisciplinary nature make it difficult for thoughtful citizens to reach their own conclusions on the topic and for potentially interested economists to know where to start. This essay aims to provide a point of entry formacroeconomists interested in climate change and climate change policy but with no special knowledge of the field. I therefore start at the beginning, with some basic background on climate change, presented through the eyes of an econometrician. I then turn to climate policy in the United States. That discussion points to a large number of researchable open questions that macroeconomists are particularly well suited to tackle. Let me summarize my four main points. First, although a healthy dose of skepticism is always in order (as academics it is in our DNA), simple and transparent time series regression models familiar to macroeconomists provide independent verification of some key conclusions from climate science models and in particular confirm that essentially all the warming over the past 140 years is because of human activity, that is, is anthropogenic. Figure 1 shows time series data on annual global mean temperature since 1860, when reliable instrumental records start. As seen in the figure, the global mean temperature has increased by approximately 1 degree Celsius, compared with its 1870–90 average value. This increase in temperatures drives a wide range of changes in climate, including droughts, more hot days, and more intense rainfalls and storms, all of which vary regionally. Because climate science uses large, opaque calibrated models of the climate system, there is room for confusion among legitimately skeptical outsiders about just howmuch of the global warming observed since the industrial revolution results from human","PeriodicalId":51680,"journal":{"name":"Nber Macroeconomics Annual","volume":"34 1","pages":"399 - 419"},"PeriodicalIF":7.7,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1086/707193","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45137359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
DaronAcemoglu contextualized the authors’ paper as part of an ongoing debate about the origins of intercohort trends in labor market outcomes. He argued that differences across education groups have been studied extensively,whereas differences across cohorts are less understood.He contrasted two views on the subject. According to the first one, which he labeled the “early labor view,” intercohort trends stem from differences in protections and unionization across cohorts. The second view, which Acemoglu labeled the “Card-Lemieux (2001) view” (David Card and Thomas Lemieux [“Can Falling Supply Explain the Rising Return to College for Younger Men? A Cohort-Based Analysis,” Quarterly Journal of Economics 116, no. 2 (2001): 705–46]), imputes these trends to differences in educational attainments across cohorts. Acemoglu downplayed the importance of the first view. He suggested instead that a decrease in the relative supply of educated workers across cohorts is the most plausible explanation for the rise in the skill premium observed in the data. He noted that college graduation rates rose steadily for cohorts born before 1950, but educational attainments stagnated or even declined afterward. Acemoglu argued that the literature still does not have a good understanding of the source of this structural break. The authors agreed that the decline in educational achievements across cohorts is striking, especially because the skill premium rose over the relevant period. They would not speculate about the reasons underlying this trend but suggested that skill-biased technical changes might also have played a role for the rising skill premium. Valerie Ramey followedupon the subject andoffered a tentative explanation for the decline in educational achievements across cohorts. She highlighted the role of expectations for investment in human capital. She noted that the 1960s cohort (studied in the paper) turned 18 in the late 1970s, when the college premiumwas low and strong unions guaranteed
{"title":"Discussion","authors":"","doi":"10.1086/707176","DOIUrl":"https://doi.org/10.1086/707176","url":null,"abstract":"DaronAcemoglu contextualized the authors’ paper as part of an ongoing debate about the origins of intercohort trends in labor market outcomes. He argued that differences across education groups have been studied extensively,whereas differences across cohorts are less understood.He contrasted two views on the subject. According to the first one, which he labeled the “early labor view,” intercohort trends stem from differences in protections and unionization across cohorts. The second view, which Acemoglu labeled the “Card-Lemieux (2001) view” (David Card and Thomas Lemieux [“Can Falling Supply Explain the Rising Return to College for Younger Men? A Cohort-Based Analysis,” Quarterly Journal of Economics 116, no. 2 (2001): 705–46]), imputes these trends to differences in educational attainments across cohorts. Acemoglu downplayed the importance of the first view. He suggested instead that a decrease in the relative supply of educated workers across cohorts is the most plausible explanation for the rise in the skill premium observed in the data. He noted that college graduation rates rose steadily for cohorts born before 1950, but educational attainments stagnated or even declined afterward. Acemoglu argued that the literature still does not have a good understanding of the source of this structural break. The authors agreed that the decline in educational achievements across cohorts is striking, especially because the skill premium rose over the relevant period. They would not speculate about the reasons underlying this trend but suggested that skill-biased technical changes might also have played a role for the rising skill premium. Valerie Ramey followedupon the subject andoffered a tentative explanation for the decline in educational achievements across cohorts. She highlighted the role of expectations for investment in human capital. She noted that the 1960s cohort (studied in the paper) turned 18 in the late 1970s, when the college premiumwas low and strong unions guaranteed","PeriodicalId":51680,"journal":{"name":"Nber Macroeconomics Annual","volume":"34 1","pages":"137 - 139"},"PeriodicalIF":7.7,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1086/707176","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42395876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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