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Missing Growth from Creative Destruction
Philippe Aghion, London School of Economics
Antonin Bergeaud, Banque de France
Timo Boppart, IIES, Stockholm University
Peter J. Klenow, Stanford University and NBER
Huiyu Li, Federal Reserve Bank of San Francisco
Pablo Fajgelbaum, Princeton University and NBER

Statistical agencies typically impute inflation for disappearing products from the inflation rate for surviving products. As some products disappear precisely because they are displaced by better products, inflation may be lower at these points than for surviving products. As a result, creative destruction may result in overstated inflation and understated growth. Aghion, Bergeaud, Boppart, Klenow, and Li use a simple model to relate this "missing growth" to the frequency and size of various kinds of innovations. Using U.S. Census data, the researchers then apply two ways of assessing the magnitude of missing growth for all private non-farm businesses for 1983 - 2013. The first approach exploits information on the market share of surviving plants. The second approach applies indirect inference to firm-level data. The researchers find: (i) missing growth from imputation is substantial -- 0.5 percentage points per year when using the first approach, 1 percentage point per year using the second method; and (ii) almost all of the missing growth is due to creative destruction (as opposed to new varieties).


This paper was distributed as Working Paper 24023, where an updated version may be available.

The Rate of Return on Everything, 1870–2015
Òscar Jordà, Federal Reserve Bank of San Francisco
Katharina Knoll, Deutsche Bundesbank
Dmitry Kuvshinov, Universitat Pompeu Fabra
Moritz Schularick, University of Bonn
Alan M. Taylor, University of California, Davis and NBER
Matthew Rognlie, Northwestern University and NBER

Jordà, Knoll, Kuvshinov, Schularick, and Taylor answer fundamental questions that have preoccupied modern economic thought since the 18th century. What is the aggregate real rate of return in the economy? Is it higher than the growth rate of the economy and, if so, by how much? Is there a tendency for returns to fall in the long-run? Which particular assets have the highest long-run returns? The researchers answer these questions on the basis of a new and comprehensive dataset covering total returns for all important assets classes--equity, housing, bonds, and bills--across 16 advanced economies from 1870 to 2015.


This paper was distributed as Working Paper 24112, where an updated version may be available.

Financial Cycles with Heterogeneous Intermediaries
Nuno Coimbra, Banque de France
Hélène Rey, London Business School and NBER
Arvind Krishnamurthy, Stanford University and NBER

Coimbra and Rey develop a dynamic macroeconomic model with heterogeneous financial intermediaries and endogenous entry. The model features time-varying endogenous macroeconomic risk that arises from the risk-shifting behavior of financial intermediaries combined with entry and exit. The researchers show that when interest rates are high, a decrease in interest rates stimulates investment and increases financial stability. In contrast, when interest rates are low, further stimulus can increase systemic risk and induce a fall in the risk premium through increased risk-shifting. In this case, the monetary authority faces a trade-off between stimulating the economy and financial stability.

Robots and Jobs: Evidence from US Labor Markets
Daron Acemoglu, Massachusetts Institute of Technology and NBER
Pascual Restrepo, Boston University and NBER
Richard Rogerson, Princeton University and NBER

As robots and other computer-assisted technologies take over tasks previously performed by labor, there is increasing concern about the future of jobs and wages. Acemoglu and Restrepo analyze the effect of the increase in industrial robot usage between 1990 and 2007 on US local labor markets. Using a model in which robots compete against human labor in the production of different tasks, the researchers show that robots may reduce employment and wages, and that the local labor market effects of robots can be estimated by regressing the change in employment and wages on the exposure to robots in each local labor market--defined from the national penetration of robots into each industry and the local distribution of employment across industries. Using this approach, the researchers estimate large and robust negative effects of robots on employment and wages across commuting zones. Acemoglu and Restrepo bolster this evidence by showing that the commuting zones most exposed to robots in the post-1990 era do not exhibit any differential trends before 1990. The impact of robots is distinct from the impact of imports from China and Mexico, the decline of routine jobs, offshoring, other types of IT capital, and the total capital stock (in fact, exposure to robots is only weakly correlated with these other variables). According to their estimates, one more robot per thousand workers reduces the employment to population ratio by about 0.18-0.34 percentage points and wages by 0.25-0.5 percent.


This paper was distributed as Working Paper 23285, where an updated version may be available.

The Macroeconomic Impact of Microeconomic Shocks: Beyond Hulten's Theorem
Emmanuel Farhi, Harvard University
David Baqaee, University of California, Los Angeles and NBER
Jennifer La'O, Columbia University and NBER

Farhi and Baqaee provide a nonlinear characterization of the macroeconomic impact of microeconomic TFP shocks in terms of reduced-form non-parametric elasticities for efficient economies. The researchers also provide the mapping from structural parameters to these reduced-form elasticities, under general equilibrium. In this sense, the paper extends the foundational theorem of Hulten (1978) beyond first-order terms to capture nonlinearities. Key features ignored by first-order approximations that play a crucial role are: structural elasticities of substitution, network linkages, structural returns to scale, and the degree to which factors can be reallocated. Higher-order terms are large and economically interesting: they magnify negative shocks and attenuate positive shocks, resulting in an output distribution that is asymmetric (negative skewness), fat-tailed (excess kurtosis), and has a lower mean. They explain how small microeconomic shocks to critical sectors can have a large macroeconomic impact. To give a sense of magnitudes: in their benchmark calibration, output losses due to business cycle fluctuations are 0.6% of GDP, an order of magnitude larger than the cost of business cycles calculated by Lucas (1987), and are entirely due to a reduction in the mean of GDP because of nonlinearities in production; and accounting for second-order terms increases the estimated impact of the price shock to the critical sector of oil in the 1970s from 0.6% to 2.3% of world GDP.

Uncertainty Shocks as Second-Moment News Shocks
David W. Berger, Duke University and NBER
Ian Dew-Becker, Northwestern University and NBER
Stefano Giglio, Yale University and NBER
Nicholas Bloom, Stanford University and NBER

This paper provides new empirical evidence on the relationship between aggregate uncertainty and the macroeconomy. Berger, Dew-Becker, and Giglio identify uncertainty shocks using methods from the literature on news shocks, following the observation that second-moment news is a shock to uncertainty. The key distinction the researchers draw is between realized volatility - the realization of large shocks - and forward-looking uncertainty - the expectation that future shocks will be large. According to a wide range of VAR specifications, shocks to realized stock market volatility are contractionary, while shocks to uncertainty have no significant effect on the economy. In line with those findings, investors have historically paid large premia to hedge shocks to realized volatility, but the premia associated with shocks to uncertainty have not been statistically different from zero. The researchers argue that these facts, and the VAR identification, are consistent with a simple model in which output growth is skewed left. Aggregate volatility matters, but it is the realization of volatility, rather than uncertainty about the future, that seems to be associated with declines.



Andrea Ajello, Federal Reserve Board
Michelle Alexopoulos, University of Toronto
Cynthia Balloch, London School of Economics
Santiago Bazdresch, Bank of Mexico
Mark Bognanni, Federal Reserve Bank of Cleveland
Paolo Bonomolo, De Nederlandsche Bank
Yasser Boualam, University of North Carolina
Craig Brown, Purdue University
Gonzalo A. Castex, Central Bank of Chile
Yoosoon Chang, Indiana University
Haiyan Ding, Zhejiang University of Finance and Economics
Taeyoung Doh, Federal Reserve Bank of Kansas City
Javier D. Donna, University of Florida
Kevin Donovan, Yale University
Carlo Galli, Universidad Carlos III de Madrid
Juan Angel García, European Central Bank
Valentina Gavazza, Stockholm University
James Graham, New York University
Hui He, International Monetary Fund
Irma Hindrayanto, Netherlands Central Bank
Cars Hommes, Bank of Canada
Ryo Jinnai, Hitotsubashi University
Baris Kaymak, University of Montreal
Lynda Khalaf, Carleton University
Jinill Kim, Korea University
Jonathon Lecznar, Boston University
Oksana Leukhina, Federal Reserve Bank of St. Louis
Guannan Luo, City University of Hong Kong
Shaowen Luo, Virginia Polytechnic Institute and State University
Claudia Macaluso, Federal Reserve Bank of Richmond
Aytek Malkhozov, Federal Reserve Board
John McDermott, University of South Carolina
Elmar Mertens, Deutsche Bundesbank
Indrajit Mitra, Federal Reserve Bank of Atlanta
Wataru Miyamoto, University of Hong Kong
Rosemarie Nagel, Universitat Pompeu Fabra
Thuy Lan Nguyen, Federal Reserve Bank of San Francisco
Kristoffer Nimark, Cornell University
Morten G. Olsen, University of Copenhagen
Araceli Ortega Diaz, EGAP
Sophie S. Osotimehin, University of Quebec at Montreal
Assaf Patir, Hebrew University
Pascal Paul, Federal Reserve Bank of San Francisco
Damjan Pfajfar, Federal Reserve Board
Matthew Pritsker, Federal Reserve Bank of Boston
Zhongjun Qu, Boston University
Stanislav Rabinovich, University of North Carolina at Chapel Hill
Michael Reher, University of California San Diego, Rady School of Management
Abeer Reza, Bank of Canada
Alberto G. Rossi, Georgetown University
Filip Rozsypal, Danmarks Nationalbank
Mirco Rubin, EDHEC Business School - Nice
Francisco Ruge-Murcia, McGill University
Erick Sager, Federal Reserve Board
Kathrin Schlafmann, Copenhagen Business School
Bastian Schulz, Aarhus University
Nihar Shah, Harvard University
Jake Short, Bank of Canada
Saverio Simonelli, University of Naples Federico II
Vincent Sterk, University College London
Christian Stoltenberg, University of Amsterdam
Daan Struyven, Goldman Sachs
Yosuke Takeda, Sophia University
Andrea Tamoni, Rutgers University
John d. Tsoukalas, University of Glasgow
Tomohiro Tsuruga, International Monetary Fund
Didem Tuzemen, Federal Reserve Bank of Kansas City
Kozo Ueda, Waseda University
Yoichi Ueno, Bank of Japan
Kenji Wada, Keio University
Yikai Wang, University of Oslo
Fabian Winkler, Federal Reserve Board
Erin L. Wolcott, Middlebury College
Yohei Yamamoto, Hitotsubashi University
Eran Yashiv, Tel Aviv University
Marios Zachariadis, University of Cyprus
David L. Zeke, University of Southern California
Tong Zhang, University of Zurich

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