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Innovative Growth Accounting
Peter J. Klenow, Stanford University and NBER
Huiyu Li, Federal Reserve Bank of San Francisco
John C. Haltiwanger, University of Maryland and NBER

Recent work highlights a falling entry rate of new firms and a rising market share of large firms in the United States. To understand how these changing firm demographics have affected growth, Klenow and Li decompose productivity growth into the firms doing the innovating. They trace how much each firm innovates by the rate at which it opens and closes plants, the market share of those plants, and how fast its surviving plants grow. Using data on all nonfarm businesses from 1982-2013, Klenow and Li find that new and young firms (ages 0 to 5 years) account for almost one-half of growth -- three times their share of employment. Large established firms contribute only one-tenth of growth despite representing one-fourth of employment. Older firms do explain most of the speedup and slowdown during the middle of our sample. Finally, most growth takes the form of incumbents improving their own products, as opposed to creative destruction or new varieties.


This paper was distributed as Working Paper 27015, where an updated version may be available.

The Glass Ceiling and The Paper Floor: Gender Differences among Top Earners, 1981-2012
Fatih Guvenen, University of Minnesota and NBER
Greg Kaplan, University of Chicago and NBER
Jae Song, Social Security Administration
Paola Sapienza, Northwestern University and NBER
Raquel Fernández, New York University and NBER

Guvenen, Kaplan, and Song analyze changes in the gender structure at the top of the earnings distribution in the United States over the last 30 years using a 10% sample of individual earnings histories from the Social Security Administration. Despite making large inroads, females still constitute a small proportion of the top percentiles: the glass ceiling, albeit a thinner one, remains. They measure the contribution of changes in labor force participation, changes in the persistence of top earnings, and changes in industry and age composition to the change in the gender composition of top earners. A large proportion of the increased share of females among top earners is accounted for by the mending of, what the researchers refer to as, the paper floor -- the phenomenon whereby female top earners were much more likely than male top earners to drop out of the top percentiles. Guvenen, Kaplan, and Song also provide new evidence at the top of the earnings distribution for both genders: the rising share of top earnings accruing to workers in the Finance and Insurance industry, the relative transitory status of top earners, the emergence of top earnings gender gaps over the life cycle, and gender differences among lifetime top earners.

Diverging Trends in National and Local Concentration
Esteban Rossi-Hansberg, University of Chicago and NBER
Pierre-Daniel Sarte, Federal Reserve Bank of Richmond
Nicholas Trachter, Federal Reserve Bank of Richmond
Robert E. Hall, Stanford University and NBER
Jan Eeckhout, Universitat Pompeu Fabra

Using U.S. NETS data, Rossi-Hansberg, Sarte, and Trachter present evidence that the positive trend observed in national productmarket concentration between 1990 and 2014 becomes a negative trend when they focus on measures of local concentration. The researchers document diverging trends for several geographic definitions of local markets. SIC 8 industries with diverging trends are pervasive across sectors. In these industries, top firms have contributed to the amplification of both trends. When a top firm opens a plant, local concentration declines and remains lower for at least 7 years. Their findings, therefore, reconcile the increasing national role of large firms with falling local concentration, and a likely more competitive local environment.


This paper was distributed as Working Paper 25066, where an updated version may be available.

Sources of U.S. Wealth Inequality: Past, Present, and Future
Per Krusell, Stockholm University and NBER
Joachim Hubmer, University of Pennsylvania
Anthony A. Smith, Yale University and NBER
Owen M. Zidar, Princeton University and NBER
Benjamin Moll, London School of Economics

This paper employs a benchmark heterogeneous-agent macroeconomic model to examine a number of plausible drivers of the rise in wealth inequality in the U.S. over the last forty years. Krusell, Hubmer, and Smith find that the significant drop in tax progressivity starting in the late 1970s is the most important driver of the increase in wealth inequality since then. The sharp observed increases in earnings inequality and the falling labor share over the recent decades fall far short of accounting for the data. The model can also account for the dynamics of wealth inequality over the period -in particular the observed U-shape - and here the observed variations in asset returns are key. Returns on assets matter because portfolios of households differ systematically both across and within wealth groups, a feature in their model that also helps us to match, quantitatively, a key long-run feature of wealth and earnings distributions: the former is much more highly concentrated than the latter.

Imperfect Expectations: Theory and Evidence
George-Marios Angeletos, Massachusetts Institute of Technology and NBER
Zhen Huo, Yale University
Karthik Sastry, Massachusetts Institute of Technology
Jessica Wachter, University of Pennsylvania
Ricardo Reis, London School of Economics

Angeletos, Huo, and Sastry complement existing evidence about the predictability of average and individual forecast errors with a new fact: in response to aggregate shocks, expectations under-react initially but over-shoot later on. They next inspect these facts under the lens of a parsimonious theoretical framework that distills the essence of diverse existing theories about expectation formation. The researchers conclude that the evidence favors a theory that combines dispersed information with over-extrapolation. Theories that emphasize cognitive discounting, level-k thinking and over-confidence find little support. Angeletos, Huo, and Sastry finally illustrate the general-equilibrium implications of the documented facts within the New Keynesian model.

What Do We Learn From Cross-Regional Empirical Estimates in Macroeconomics?
Adam Guren, Boston University and NBER
Alisdair McKay, Federal Reserve Bank of Minneapolis
Emi Nakamura, University of California, Berkeley and NBER
Jón Steinsson, University of California, Berkeley and NBER
Valerie A. Ramey, University of California, San Diego and NBER
Gabriel Chodorow-Reich, Harvard University and NBER

Recent empirical work uses variation across cities or regions to identify the effects of economic shocks of interest to macroeconomists. The interpretation of such estimates is complicated by the fact that they reflect both partial equilibrium and local general equilibrium effects of the shocks. Guren, McKay, Nakamura, and Steinsson propose an approach for recovering estimates of partial equilibrium effects from these cross-regional empirical estimates. The basic idea is to divide the cross-regional estimate by an estimate of the local fiscal multiplier, which measures the strength of local general equilibrium amplification. The researchers apply this approach to recent estimates of housing wealth effects based on city-level variation, and derive conditions under which the adjustment is exact. Guren, McKay, Nakamura, and Steinsson then evaluate its accuracy in a richer general equilibrium model of consumption and housing. The paper also reconciles the positive cross-sectional correlation between house price growth and construction with the notion that cities with larger price volatility have lower housing supply elasticities using a model in which housing supply elasticities are more dispersed in the long run than in the short run.


This paper was distributed as Working Paper 26881, where an updated version may be available.


Patrick A. Adams, Massachusetts Institute of Technology
Elena Afanasyeva, Federal Reserve Board
Andrea Ajello, Federal Reserve Board
Federico R. Bennet, Duke University
Agneta K. Berge
Nicolas Caramp, University of California at Davis
Xiang Ding, Georgetown University
Min Fang, University of Lausanne
Diego R. Kaenzig, London Business School
Maziar Kazemi, Massachusetts Institute of Technology
Federico Kochen, New York University
Eunseong Ma, Louisiana State University
Max Miller, University of Pennsylvania
Marialuz Moreno Badia, International Monetary Fund
Thuy Lan Nguyen, Federal Reserve Bank of San Francisco
Jacob Orchard, University of California at San Diego
James Paron, University of Pennsylvania
Stefano Pica, Boston University
Tatevik Sekhposyan, Texas A&M University
Joe Simmons, Boston University

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