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About the Researcher(s)/Author(s)

Andrew (Andy) Atkeson is a research associate in the NBER’s Economic Fluctuations and Growth and Asset Pricing programs. He is a professor of economics at the University of California, Los Angeles, a consultant at the Federal Reserve Bank of Minneapolis, and has served on the editorial boards of various journals, including the American Economic Review, The Review of Economic Studies, and The Quarterly Journal of Economics.

Prior to arriving at UCLA, Atkeson was at the Federal Reserve Bank of Minneapolis, the University of Minnesota, the University of Pennsylvania, and the University of Chicago. He received his PhD from Stanford University’s Graduate School of Business and his BA from Yale University.

Like many economists, over the past year Atkeson has focused on learning as much as he can about epidemiology and COVID-19. He has learned a lot in particular from conversations with Ben Moll, Jim Stock, and Mike Droste, in addition to those with Karen Kopecky and Tao Zha.

Footnotes

1. “Trends in Infectious Disease Mortality in the United States during the 20th Century,” Armstrong G, Conn L, Pinner R. Journal of the American Medical Association 281(1), January 1999, pp. 61–66.   Go to ⤴︎
2. “Emerging Pandemic Diseases: How We Got to COVID-19,” Morens D, Fauci A. Cell 182(5), September 2020, pp. 1077–1092. See also this September 2019 report from the President’s Council of Economic Advisers on the potential public health and economic impact of pandemic influenza. To place the mortality rate from COVID-19 in historical perspective, note that COVID mortality in the United States was roughly 100 in 100,000 in 2020 and may very well reach this level again in 2021. So while mortality from COVID will not reach the levels reached during the 1918–19 influenza pandemic, it will clearly be the most significant short-term increase in mortality from infectious disease in the United States in at least 60 years.   Go to ⤴︎
4. Later data from other countries suggest that COVID progresses at substantially faster rates than initially estimated in China. Thus, if one were to update the analysis in my paper from March 2020, the time scale on the x axis of all of the figures would be substantially shortened. In a contemporaneous paper, James H. Stock used a similar standard epidemiological model to arrive at similar forecasts for peak infections and the long-run impact of the disease. “Data Gaps and the Policy Response to the Novel Coronavirus,” Stock J. NBER Working Paper 26902, March 2020. His estimates of the time scale of the pandemic are closer to those that have been observed outside of China.   Go to ⤴︎
5. These implications of a standard epidemiological model for the magnitude of the first peak and the long-run impact of COVID-19 are driven by estimates of the basic reproduction number of the virus (the R0 ) from early data in China. “Herd Immunity: Understanding COVID-19,” Randolph H, Barreiro L. Immunity 52(5), May 2020, pp. 737–741, offers a description of the calculations and considerations involved. Data on the recent emergence of more virulent variants of COVID-19 in the United Kingdom and elsewhere yield higher estimates of this basic reproduction number. Thus, if I were to update this first paper with new parameter estimates, the implications for the peak of active infections and the long-run impact of COVID-19 would be even more dire.   Go to ⤴︎
6. Note the range of parameter estimates suggested by the CDC in Table 1 here: https://www.cdc.gov/coronavirus/2019-ncov/hcp/planning-scenarios.html.   Go to ⤴︎
7. “Estimating and Forecasting Disease Scenarios for COVID-19 with an SIR Model,” Atkeson A, Kopecky K, Zha T. NBER Working Paper 27335, June 2020. Here we propose a method for estimating epidemiological models with time-varying transmission rates; “How Deadly Is COVID-19? Understanding the Difficulties with Estimation of Its Fatality Rate,” Atkeson, A. NBER Working Paper 26965, April 2020. In this paper I examine some of the challenges in identifying model parameters from aggregate time series data; In “Four Stylized Facts about COVID-19,” Atkeson A, Kopecky K, Zha T. NBER Working Paper 27719, August 2020, we describe our findings regarding the evolution of the COVID-19 pandemic through the summer of 2020.   Go to ⤴︎
8. “Economic Epidemiology and Infectious Diseases,” Philipson T. NBER Working Paper 7037, March 1999. Go to ⤴︎
9. “Behavior and the Transmission of COVID-19,” Atkeson A, Kopecky K, Zha T. Federal Reserve Bank of Minneapolis, Staff Report 618, February 2021. Go to ⤴︎
10. “The Economic Consequences of R̂=1: Toward a Workable Behavioral Epidemiological Model of Pandemics,” Gans J. NBER Working Paper 27632, July 2020. Joshua Gans reviews the implications of epidemiological models with a prevalence-elastic demand for costly measures to prevent disease transmission and much of the work by NBER affiliates on this topic.   Go to ⤴︎
11. See “Resurgence of COVID-19 in Manaus, Brazil, despite High Seroprevalence,” Sabino E, Buss L, Carvalho M, Prete C, Crispim M, Fraiji N, et al. Lancet 297(10273) February 2021, pp. 452–455, and “Vaccines Are Curbing COVID: Data from Israel Show Drop in Infections,” Mallapaty S. Nature 590(197), February 2021, regarding data from Brazil and Israel on the empirical herd immunity threshold. More complex models that emphasize heterogeneity and the network structure of human interaction potentially offer more optimistic implications for the long-run impact of COVID. See, for example: “Implications of Heterogeneous SIR Models for Analyses of COVID-19,” Ellison G. NBER Working Paper 27373, June 2020; “Socioeconomic Network Heterogeneity and Pandemic Policy Response,” Akbarpour M, Cook C, Marzuoli A, Mongey S, Nagaraj A, Saccarola M, Tebaldi P, Vasserman S, Yang H. NBER Working Paper 27374, June 2020; “Pandemic Control in ECON-EPI Networks,” Azzimonti M, Fogli A, Perri F, Ponder M. NBER Working Paper 27741, August 2020; “Integrated Epi-Econ Assessment,” Boppart T, Harmenberg K, Hassler J, Krusell P, Olsson J. NBER Working Paper 28282, December 2020. Recent research “Immunological Characteristics Govern the Transition of COVID-19 to Endemicity,” Lavine J, Bjornstad O, Antia R. Science 371(6530), February 2021, pp. 741–745 forecasts that COVID-19 may become endemic if immunity is only temporary, as is the case for other coronaviruses. Go to ⤴︎
13. Given the wide variety of public policies to slow COVID transmission worldwide, ranging from strict to none, this finding of a nearly universal decline in the growth of the pandemic suggests that private behavioral responses played a prominent role in limiting peaks of infections and deaths. A great deal of research by NBER affiliates, much of it summarized by Sumheda Gupta and his coauthors in “Mandated and Voluntary Social Distancing during the COVID-19 Epidemic: A Review,” Gupta S, Simon K, Wing C. NBER Working Paper 28139, November 2020, documents in detail the importance of costly private efforts to prevent disease transmission in shaping the early phase of this pandemic. Go to ⤴︎
14. "Macroeconomic Outcomes and COVID-19: A Progress Report,” Fernández-Villaverde J, Jones C. NBER Working Paper 28004, October 2020; “How Should We Interpret the Cross Country or Region Relationship between Cumulative Deaths and Lost Economic Activity from COVID?” Atkeson A. October 2020. Both these papers are forthcoming in Brookings Papers on Economic Activity.   Go to ⤴︎
15. “What Explains Temporal and Geographic Variations in the Early US Coronavirus Pandemic?” Allcott H, Boxell L, Conway J, Ferguson B, Gentzkow M, Goldman B. NBER Working Paper 27965, October 2020, examines the importance of such factors for explaining the early evolution of the pandemic across many locations. See also “Modeling Infectious Disease Dynamics,” Cobey S. Science 368(6492), May 2020, pp. 713–714.   Go to ⤴︎
16. “Social Distancing and Social Capital: Why US Counties Respond Differently to COVID-19,” Ding W, Levine R, Lin C, Xie W. NBER Working Paper 27393, June 2020; “Polarization and Public Health: Partisan Differences in Social Distancing during the Coronavirus Pandemic,” Allcott H, Boxell L, Conway J, Gentzkow M, Thaler M, Yang D. NBER Working Paper 26946, April 2020; “Inequality and the Coronavirus: Socioeconomic Covariates of Behavioral Responses and Viral Outcomes across US Counties,” Brown C, Ravallion M. NBER Working Paper 27549, July 2020.   Go to ⤴︎
17. See “National COVID-19 Testing Action Plan,” The Rockefeller Foundation, as advocated by Paul Romer, as well as “An SEIR Infectious Disease Model with Testing and Conditional Quarantine,” Berger D, Herkenhoff K, Mongey S. NBER Working Paper 26901, March 2020; “The Macroeconomics of Testing and Quarantining,” Eichenbaum M, Rebelo S, Trabandt M. NBER Working Paper 27104, August 2020; “The Cost of Privacy: Welfare Effects of the Disclosure of COVID-19 Cases,” Argente D, Hsieh C, Lee M. NBER Working Paper 27220, May 2020; “Testing, Voluntary Social Distancing and the Spread of an Infection,” Acemoglu D, Makhdoumi A, Malekian A, Ozdaglar A. NBER Working Paper 27483, July 2020; “Group Testing in a Pandemic: The Role of Frequent Testing, Correlated Risk, and Machine Learning,” Augenblick N, Kolstad J, Obermeyer Z, Wang A. NBER Working Paper 27457, July 2020; “A Theory of Voluntary Testing and Self-Isolation in an Ongoing Pandemic,” Hellmann T, Thiele V. NBER Working Paper 27941, October 2020.   Go to ⤴︎
18. “Economic Benefits of COVID-19 Screening Tests,” Atkeson A, Droste M, Mina M, Stock J. NBER Working Paper 28031, October 2020.     Go to ⤴︎
19. The University of Illinois, Urbana-Champaign has conducted one of the largest mass testing campaigns among universities with remarkable results after an initial difficulty with compliance with quarantines. The mass testing pilot conducted in Liverpool, England, had less favorable outcomes due to problems with uptake of testing, as described here.   Go to ⤴︎

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