NBER Macroeconomics Annual 2019: Volume 34

Contents

Copyright

NBER Board of Directors

Relation of the Directors to the Work and Publications of the NBER

Contents

Editorial

Martin Eichenbaum, Erik Hurst, and Jonathan A. Parker

Abstracts

From Good to Bad Concentration? US Industries over the Past 30 Years

Matias Covarrubias, Germán Gutiérrez, and Thomas Philippon

Comment

Janice Eberly

Comment

Chad Syverson

Discussion

The Lost Ones: The Opportunities and Outcomes of White, Non-College-Educated Americans Born in the 1960s

Margherita Borella, Mariacristina De Nardi, and Fang Yang

Comment

Richard Blundell

Comment

Greg Kaplan

Discussion

On the Empirical (Ir)Relevance of the Zero Lower Bound Constraint

Davide Debortoli, Jordi Galí, and Luca Gambetti

Comment

Ben S. Bernanke

Comment

Mark W. Watson

Discussion

Optimal Inflation and the Identification of the Phillips Curve

Michael McLeay and Silvana Tenreyro

Comment

Marc P. Giannoni

Comment

Matthew Rognlie

Discussion

Trading Up and the Skill Premium

Nir Jaimovich, Sergio Rebelo, Arlene Wong, and Miao Ben Zhang

Comment

Daron Acemoglu

Comment

Jonathan Vogel

Discussion

Special Deals with Chinese Characteristics

Chong-en Bai, Chang-Tai Hsieh, and Zheng Song

Comment

Maurice Obstfeld

Comment

Antoinette Schoar

Discussion

Climate Change, Climate Policy, and Economic Growth

James H. Stock

Copyright

© 2020 by The University of Chicago. All rights reserved.

NBER Board of Directors

© 2020 by The University of Chicago. All rights reserved.

Relation of the Directors to the Work and Publications of the NBER

© 2020 by The University of Chicago. All rights reserved.

Contents

© 2020 by The University of Chicago. All rights reserved.

Editorial

Martin Eichenbaum

Northwestern University and NBER

Erik Hurst

University of Chicago and NBER

Jonathan A. Parker

MIT and NBER

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 after-dinner 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, which make the content of the conference more widely 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 for macroeconomists. 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 to play if we 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 not work. 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.

During the last two decades in the United States, production has become more concentrated, with a smaller set of firms producing a larger fraction of aggregate output. During that same time, firm profits have increased, labor share of output has fallen, and firm investment has decreased. Is increased concentration the efficient response to changing consumer behavior or technology? Or is increasing concentration the inefficient result of increased barriers to firm entry?

These questions are explored in the paper From Good to Bad Concentration? US Industries over the Past 30 Years, by Matias Covarrubias, Germán Gutiérrez, and Thomas Philippon. Covarrubias et al. draw on insights from the industrial organization literature and provide a simple framework to highlight that increasing concentration is a market outcome and can be the equilibrium result of either less market competition or more market competition.

Using a variety of aggregate data sources, the authors find that during the 1990s, increased aggregate concentration was correlated with rising productivity, falling prices, and higher investment. These findings are consistent with models where increased concentration is driven by increases in the returns to scale in firm production and/or increases in the elasticity of substitution across consumption goods. The authors conclude that the increased concentration in the United States during the 1990s reflected good concentration. However, during the 2000s, increased aggregate concentration was correlated with falling productivity growth, rising prices, and falling investment. These findings are consistent with increasing barriers to firm entry during the 2000s. The authors conclude that much of the increased concentration during the 2000s reflects an increase in bad concentration.

In the last part of their paper, the authors use cross-industry variation to shed further light on the causes of increased concentration during the 2000s. The authors conclude that the aggregate results may be too coarse to accurately reflect the underlying causes of increased concentration. By exploiting cross-industry variation, the authors conclude that multiple forces are responsible for the increased concentration observed in the United States during the 2000s. Although increased barriers to entry are part of the story—particularly in some industries—changes in firm technology and consumer demand patterns are also an important part of the story.

Both of the discussants applaud the authors for their careful data work and for laying out a simple framework to discuss the potential causes of increased concentration. Both also agree that the cross-industry results are more interesting in that they highlight that multiple factors are likely changing simultaneously within the US economy during the 2000s.

Real wages among lower income groups in the United States have grown very little since the late 1960s. Even strikingly, there has been a reduction in life expectancy among white men born in the 1960s relative to the previous generation. Such declines are not supposed to happen in a healthy growing economy. Margherita Borella, Mariacristina De Nardi, and Fang Yang study this decline in well-being in The Lost Ones: The Opportunities and Outcomes of White, Non-College-Educated Americans Born in the 1960s. The paper develops a structural life cycle model to quantify the economic outcomes of less educated Americans born in the 1960s.

The paper begins by confirming and documenting a number of important facts about less educated white Americans, largely using the Panel Study of Income Dynamics. Real wages declined between these generations for less educated women (who started from a lower starting point), and postretirement, out-of-pocket medical expenses rose dramatically. Expected life spans declined for both men and women.

The paper analyzes these changes by estimating a rich structural model of life cycle consumption and saving on those born in the 1960 cohort. Taking the estimated preference parameters as given, the authors ask how this generation would have behaved and fared if instead they had faced the wages, medical costs, and health/longevity of those born in the 1940s. The results are striking.

The decline in wages that men born in the 1960s faced lowered their labor supply, whereas that of women increased slightly; the decrease in life expectancy reduced their saving, but the increase in out-of-pocket medical expenses increased by more. Thus, together, consumption falls significantly. The welfare decline is large, ranging from an equivalent of 7% to 13% of lifetime income depending on gender and marital status.

The discussants raised a number of important issues, including whether actual inflation was lower than measured inflation. To the extent this was the case real wages for less educated white men have not fallen. Of course, such mismeasurement of inflation does not alter the declines in life spans. Another issue that was discussed was how to measure the welfare costs of lower life spans.

The financial crisis of 2007–8 and the ensuing recession led central banks around the world to lower short-term interest rates to values near their (rough) lower bound of zero. The Federal Reserve kept its policy rate at that level until the end of December 2015. As a result, the Fed could not use short-term interest rates to combat the recession or fight incipient deflationary pressures. In their paper, On the Empirical (Ir)Relevance of the Zero Lower Bound Constraint, Davide Debortoli, Jordi Galí, and Luca Gambetti investigate whether this constraint affected the performance of the US economy. They do so by assessing the extent to which the constraint affected the volatility of US macro aggregates and the response of those aggregates to various shocks. They find very little evidence that the constraint materially affected the economy.

This finding is very surprising from the perspective of standard macroeconomic models like the New Keynesian (NK) model. One’s first reaction is that this finding is a power issue. But the paper’s evidence is persuasive that power is not the issue. From the perspective of the NK model, one should be able to detect substantial effects on macro aggregates when the zero lower bound binds, even in sample sizes as small as those available to the authors.

How can we explain this important finding? According to the authors, the answer is that policy makers developed new tools that were effective in making the zero lower bound constraint not constraining. The prime examples are forward guidance and unconventional purchases of long-term assets. The paper’s findings are clearly very important, especially in a world where, going forward, short-term policy interests are likely to hit the zero lower bound much more frequently.

The first discussant examined factors, other than the effectiveness of the new tools developed by monetary policy makers, that could explain the authors’ main results. He also investigated whether the authors’ findings are consistent with other more direct evidence regarding the effectiveness of nonstandard policies. The second discussant raised important methodological questions about statistical inference in sign-restricted structural vector autoregressions, one of the methods used in the paper.

Many researchers and members of the commentariat have announced the death of the Phillips curve. This view is based on the apparent weak statistical relationship between inflation and various measures of unused economic capacity. The latter include unemployment and estimates of the output gap. Such claims, if true, would pose an important challenge to the way macroeconomists think about fluctuations in economic activity and the paradigm within which central banks conduct policy.

In their paper Optimal Inflation and the Identification of the Phillips Curve, Michael McLeay and Silvana Tenreyro challenge the validity of these claims. Their argument is as follows. Suppose that policy makers seek to minimize welfare subject to a structural Phillips curve. In that world, policy makers will raise inflation when output is below its full potential. Therefore, the better policy makers are at their job, the harder it will be to see a positive relationship between inflation and output. Simple correlations between inflation and output are completely uninformative about the presence of a structural Phillips curve or its slope.

The authors explore the problem of identifying the slope of the Phillips curve under various assumptions about the ability of policy makers to commit to a policy rule, the nature of the shocks to the economy, and the availability of data from different parts of an economy subject to different shocks. The first part of their analysis is conducted within the confines of a simple NK model. To assess the robustness of their results, they also investigate the problem using a full-scale dynamic stochastic general equilibrium model. Finally, the authors consider practical attempts to overcome the problem of identifying the slope of the Phillips curve. One particularly promising approach is the use of cross-sectional regional variation in unemployment.

In sum, the paper makes a very important contribution to a topic that is extremely relevant to the academic literature and ongoing policy debates.

Both discussants spoke enthusiastically about the paper, framing the analysis in terms of the classic problem of identifying a demand or a supply curve from market data. Like those curves, the Phillips curve is a structural relationship, not a reduced-form relationship. This simple but fundamental point is often neglected in popular discussions of the Phillips curve. Both discussants examined the theoretical underpinning of the structural Phillips curve and the practical difficulties of identifying that curve. In addition, one discussant contrasted the reduced-form relationship between inflation and unemployment with the relationship between wage growth and inflation, analyzing the latter in detail.

There has been a large rise in US income inequality over the last four decades. In their paper Trading Up and the Skill Premium, Nir Jaimovich, Sergio Rebelo, Arlene Wong, and Miao Ben Zhang highlight a relatively unexplored mechanism that could be contributing to the rising skill premium. Their mechanism stems from two assumptions. First, households trade up to higher-quality products as they become richer. Second, higher-quality products are more skill intensive. Together, the assumptions imply that as an economy grows, the demand for skills will endogenously grow, providing an additional force generating upward pressure on the skill premium.

Jaimovich et al. begin their paper by providing empirical support for the two assumptions at the heart of their mechanism. First, using data from the Nielsen Homescan database and the Consumer Expenditure Survey, the paper documents that richer households do, in fact, purchase higher-quality goods. Second, using data from Yelp matched with microdata from the Occupational Employment Statistics, the paper shows that higher-quality goods are produced with a higher share of skilled workers. Both discussants emphasized that this empirical work is an important contribution to the literature.

The paper provides a simple model of trading up. The goal of the model is to quantitatively explore the extent of skill-biased technological change that is needed to generate the observed increase in the skill premium in the United States over the last 40 years. In their model, the endogenous skill upgrading results in a larger change in the skill premium with lower amounts of skill-biased technological change. According to their calibrated model, the extent of skill-biased technological change that is needed to match the data is only 1.1% per year as opposed to 5.5% per year in a model without skill upgrading. Although the mechanism is novel and should stimulate further research, both discussants stressed that the authors’ model is too simple to provide a definitive quantitative assessment of the importance of skill upgrading as an explanation for the rising skill premium.

Our final paper takes up the important topic of economic growth in China. China has undergone a 30-year economic growth miracle despite economic and political institutions that look nothing like those that appear to be required for prosperity in most of the rest of the world. A fascinating paper by Chong-en Bai, Chang-Tai Hsieh, and Zheng Song, Special Deals with Chinese Characteristics, argues that the lack of formal institutional, legal, and jurisprudential constraints on politicians creates growth because it has been combined with high-powered incentives.

The paper proposes a theory in which local politicians compete against other localities to maximize local economic growth. The lack of formal and regulatory constraints on politicians means that local officials are free to favor certain industries and to promote particular businesses by handing out special deals. In many countries, this lack of oversight leads to economic stagnation. But in China, local officials have high-powered incentives instead of formal legal oversight. Politicians’ careers benefit from growth, as their locality grows in importance and as their success increases their stature with the central Chinese authorities. They also benefit financially, as they often invest in the businesses in their locality that they are backing. When things go badly, the penalties for local officials can include criminal charges.

The paper brings a range of evidence to support its case. Most novel, in an almost ethnographic approach, the authors describe the workdays of local officials as akin to those of venture capitalists in a Western economy—visiting company headquarters, evaluating business strategies, pulling together financing, and so forth. The authors further elucidate their ideas in a model and show a number of facts about the Chinese economy that are consistent with their interpretation.

The discussants raise a number of concerns with this theory of Chinese growth and argue that the sources of rapid growth in China remain mysterious. They question whether the incentives are really high powered, and how they are maintained. Further, local politicians often erect barriers to intra-China trade, which would seem to work against strong economic growth.

As in previous years, the editors posted and distributed a call for proposals in the spring and summer prior to the conference, and some of the papers in this volume were selected from proposals submitted in response to this call. Other papers are commissioned on central and topical areas in macroeconomics. Both are done in consultation with the advisory board, which we thank for its input and support of both the conference and the published volume.

The authors and the editors would like to take this opportunity to thank Jim Poterba and the National Bureau of Economic Research for their continued support for the NBER Macroeconomics Annual and the associated conference. We would also like to thank the NBER conference staff, particularly Rob Shannon for his continued excellent organization and support. We would also like to thank the NBER public relations staff and Charlie Radin in particular for overseeing the high-quality multimedia content. Financial assistance from the National Science Foundation is gratefully acknowledged. We also thank the rapporteurs, Nathan Zorzi and Riccardo Bianchi Vimercati, who provided excellent assistance in the preparation of the summaries of the general discussions. And last but far from least, we are grateful to Helena Fitz-Patrick for her invaluable assistance in editing and publishing the volume.

Endnote

For acknowledgments, sources of research support, and disclosure of the authors’ material financial relationships, if any, please see https://www.nber.org/chapters/c14232.ack.

© 2020 by the National Bureau of Economic Research. All rights reserved.

978-0-226-70789-1/2019/2019-0001$10.00

Abstracts

1. From Good to Bad Concentration? US Industries over the Past 30 Years

Matias Covarrubias, Germán Gutiérrez, and Thomas Philippon

We study the evolution of profits, investment, and market shares in US industries over the past 40 years. During the 1990s, and at low levels of initial concentration, we find evidence of efficient concentration driven by tougher price competition, intangible investment, and increasing productivity of leaders. After 2000, however, the evidence suggests inefficient concentration, decreasing competition, and increasing barriers to entry as leaders become more entrenched and concentration is associated with lower investment, higher prices, and lower productivity growth.

2. The Lost Ones: The Opportunities and Outcomes of White, Non-College-Educated Americans Born in the 1960s

Margherita Borella, Mariacristina De Nardi, and Fang Yang

White, non-college-educated Americans born in the 1960s face shorter life expectancies, higher medical expenses, and lower wages per unit of human capital compared with those born in the 1940s; men’s wages declined more than women’s. After documenting these changes, we use a life-cycle model of couples and singles to evaluate their effects. The drop in wages depressed the labor supply of men and increased that of women, especially in married couples. Their shorter life expectancy reduced their retirement savings, but the increase in out-of-pocket medical expenses increased savings by more. Welfare losses, measured as a onetime asset compensation, are 12.5%, 8%, and 7.2% of the present discounted value of earnings for single men, couples, and single women, respectively. Lower wages explain 47%–58% of these losses, shorter life expectancies 25%–34%, and higher medical expenses account for the rest.

3. On the Empirical (Ir)Relevance of the Zero Lower Bound Constraint

Davide Debortoli, Jordi Galı́, and Luca Gambetti

We evaluate the hypothesis that the zero lower bound (ZLB) constraint was, in practice, irrelevant during the recent ZLB episode experienced by the US economy (the 2009Q1–2015Q4 period). We focus on two dimensions of economic performance thatwere ex ante likely to have been affected by a binding ZLB: (i) the volatility of macro variables and (ii) the economy’s response to shocks. Using a variety of empirical methods, we find little evidence against the irrelevance hypothesis, with our estimates suggesting that the responses of output, inflation, and the long-term interest rate were hardly affected by the binding ZLB constraint. We show how a shadow interest rate rule (which we take as a proxy for forward guidance) can reconcile our empirical findings with the predictions of a simple New Keynesian model with a ZLB constraint.

4. Optimal Inflation and the Identification of the Phillips Curve

Michael McLeay and Silvana Tenreyro

Several academics and practitioners have pointed out that inflation follows a seemingly exogenous statistical process, unrelated to the output gap, leading some to argue that the Phillips curve has weakened or disappeared. In this paper, we explain why this seemingly exogenous process arises, or, in other words, why it is difficult to empirically identify a Phillips curve, a key building block of the policy framework used by central banks. We show why this result need not imply that the Phillips curve does not hold—on the contrary, our conceptual framework is built under the assumption that the Phillips curve always holds. The reason is simple: if monetary policy is set with the goal of minimizing welfare losses (measured as the sum of deviations of inflation from its target and output from its potential), subject to a Phillips curve, a central bank will seek to increase inflation when output is below potential. This targeting rule will impart a negative correlation between inflation and the output gap, blurring the identification of the (positively sloped) Phillips curve. We discuss different strategies to circumvent the identification problem and present evidence of a robust Phillips curve in US data.

5. Trading Up and the Skill Premium

Nir Jaimovich, Sergio Rebelo, Arlene Wong, and Miao Ben Zhang

We study the impact on the skill premium of increases in the quality of goods consumed by households (trading up). Our empirical work shows that high-quality goods are more intensive in skilled labor than low-quality goods and that household spending on high-quality goods rises with income. We propose a model consistent with these facts. This model accounts for the past rise in the skill premium with more plausible rates of skill-biased technical change than those required by the canonical model. It also implies that an expansion of the skilled labor force reduces the skill premium by much less than in the canonical model.

6. Special Deals with Chinese Characteristics

Chong-en Bai, Chang-Tai Hsieh, and Zheng Song

Chinese local governments wield their enormous political power and administrative capacity to provide special deals for favored private firms. We argue that China’s extraordinary economic growth comes from these special deals. Local political leaders do so because they derive personal benefits, either political or monetary, from providing special deals. Competition between local governments limits the predatory effects of special deals.

© 2020 by the National Bureau of Economic Research. All rights reserved.

978-0-226-70789-1/2019/2019-0002$10.00

From Good to Bad Concentration? US Industries over the Past 30 Years

Matias Covarrubias

New York University

Germán Gutiérrez

New York University

Thomas Philippon

New York University, CEPR, and NBER

We study the evolution of profits, investment, and market shares in US industries over the past 40 years. During the 1990s, and at low levels of initial concentration, we find evidence of efficient concentration driven by tougher price competition, intangible investment, and increasing productivity of leaders. After 2000, however, the evidence suggests inefficient concentration, decreasing competition, and increasing barriers to entry as leaders become more entrenched and concentration is associated with lower investment, higher prices, and lower productivity growth.

We analyze the evolution of concentration in US industries over the past 40 years. Figure 1 summarizes the four stylized facts that motivate our work. Concentration and profits have increased, while the labor share and investment have decreased (fig. 1a–1d, respectively).¹ This is true across most US industries as shown by Autor et al. (2017a; labor shares), Gutiérrez and Philippon (2016; investment and profits), and Grullon, Larkin, and Michaely (2019; concentration and profits). Although these stylized facts are well established, we are still far from consensus on what is causing them and what they tell us about the health of the US economy. The most prominent explanations can be organized in two groups:

The goal of this paper is to differentiate between these explanations at the aggregate and industry level. Before discussing our approach and results, however, it is important to clarify three points. First, these hypotheses are not mutually exclusive. Leaders can become more efficient and more entrenched at the same time—which can explain their growth but also the rise of barriers to entry (Crouzet and Eberly 2018). Indeed, a combination of these explanations is often heard in the discussion of internet giants Google, Amazon, Facebook, or Apple.

Fig. 1. Evolution of US concentration, profits, labor shares, and investment. (a) Cumulative change in eight-firm concentration ratio (CR8; in %), based on the cumulated sales-weighted average change in CR8. Data from the US Economic Census based on Standard Industrial Classification-4 codes before 1992 and North American Industry Classification System-6 codes after 1997. When multiple tax groups are reported, only taxable firms are included. CR8 equals the market share (by sales) of the eight largest firms in each industry. We include only those industries that are consistently defined over each 5-year period. Change from 1992 to 1997 imputed from Autor et al. (2017b). (b) Profits/value added (VA), (c) labor share, and (d) net investment to net operating surplus, based on quarterly data for the nonfinancial corporate sector from the Financial Accounts of the US, via Federal Reserve Economic Data. Profit rate defined as the ratio of after-tax corporate profits with inventory valuation adjustment and capital consumption adjustment to VA (series W328RC1A027NBEA and NCBGVAA027S, respectively). Labor share defined as the ratio of compensation of employees (NCBCEPQ027S) to gross VA (NCBGVAQ027S). Net investment to net operating surplus defined as the ratio of net investment (gross fixed capital formation minus consumption of fixed capital, series NCBGFCA027N minus NCBCFCA027N) to net operating surplus (series NCBOSNQ027S). Dotted lines show the average of the corresponding series before and after 2002.

Second, intangibles can play a role in all theories. They may increase the elasticity of substitution (e.g., through online price comparison), increase returns to scale (e.g., organizational capital), and also create barriers to entry (e.g., through patents and/or the compilation of Big Data).

Third, these specific patterns are unique to the US. Figure 2a shows that profits margins have increased in the US, but they have remained stable or decreased in Europe, Japan, and South Korea. Figure 2b shows that concentration has increased in the US but it has remained roughly stable in Europe and Asia.⁴ Last, figure 2c shows that the labor share has declined in the US, but it has remained stable in Europe since 2000.⁵ Assuming that all advanced economies use similar technologies, the uniqueness of US trends suggests that technology alone cannot explain the trends.

Fig. 2. Profits, concentration, and labor shares across advanced economies. (a) Gross Operating Surplus over Production (GOS/PROD) for nonagriculture business sector excluding real estate, from Organization for Economic Co-operation and Development and Structural Analysis (OECD STAN) database. (b) Change in eight-firm concentration ratio (CR8; since 2000) for nonagriculture business sector excluding real estate, based on Compustat but adjusted for coverage using OECD STAN. CR8 for Japan and Korea (JPN + KOR) reported only since 2006 because Compustat coverage increases rapidly beforehand. (c) Change in labor share (since 2000) for market economy from EU capital (K), labor (L), energy (E), materials (M), and service (S; KLEMS). See appendix E (see https://www.nber.org/data-appendix/c14237/appendix.pdf) for details. EU28 = current European Union member states; EU15 = original European Union member states; NA = North America; CP = Compustat.

Approach

We begin by using a sequence of simple models to clarify the theories of good and bad concentration. We derive a broad set of predictions regarding the joint evolution of competition, concentration, productivity, prices, and investment under each theory. We then evaluate these predictions empirically, first at the aggregate level, then at the industry level. Although some of these predictions have been studied by the literature, we contribute new facts/results for each of them. We also clarify several measurement issues and, perhaps more important, we show how the combination of all the facts helps us differentiate good and bad concentration.

Aggregate results

Table 1 summarizes our aggregate results. It contrasts the theoretical prediction of theories of good and bad concentration against the observed evolution of each measure.⁶ Predictions in the right column are consistent with the data after 2000. Predictions in the middle column are not.

Note. CR = concentration ratio; TFP = total factor productivity.

View typeset image: 1

According to theories of good concentration, the growth of large firms is an efficient response to technological change. Under σ, competition increases as consumers become more price elastic. More productive firms expand to capture a larger share of the market, while less productive firms either shrink or exit. Economic activity reallocates toward more productive firms, increasing industry-level productivity and decreasing prices. Under γ, technological change leads to increasing returns to scale. Large firms again respond by expanding, which increases concentration and productivity while decreasing prices. The productivity gap between small and large firms grows.

If the economy experiences good concentration, we should observe: (i) concentration driven in part by exit; (ii) concentration associated with higher productivity and lower prices; and (iii) stable or increasing investment rates relative to Tobin’s Q—particularly for leaders. If the increase is driven by σ, we should also find higher volatility of market shares as demand responds more strongly to cost shocks. If the increase is driven by γ, however, the prediction could flip: volatility of market shares could fall as leaders’ comparative advantages become (potentially) more persistent (e.g., Aghion et al. 2019).

We already know that σ and γ are important for certain industries during certain periods. For instance, they describe well the evolution of the retail industry from 1990 to 2005 (Basu et al. 2003; Blanchard 2003). The rise of superstores and e-commerce led to more price competition, higher concentration, higher productivity, and the exit of inefficient retailers (Hortacsu and Syverson 2015). The question is whether these theories explain the evolution of the economy as a whole over the past 30 years. We test these predictions in the data and find some support for them during the 1990s. During this period, concentration is correlated with rising productivity, falling prices, and high investment, particularly in intangibles. Since 2000, however, these predictions are rejected by the data. The correlation between concentration and productivity growth has become negative, while the correlation between concentration and price growth has become positive; exit rates have remained stable; investment relative to Q has fallen; and market shares have become more persistent. Estimates of returns to scale based on the methodology of Basu, Fernald, and Kimball (2006) have remained stable, as have other estimates in the recent literature (Ho and Ruzic 2018; Diez, Fan, and Villegas-Sanchez 2019). All these predictions are consistent with the κ theory.

Barriers to competition therefore emerge as the most relevant explanation over the past 15 years. It correctly predicts the evolution of profits, entry, exit, turnover, prices, productivity, and investment in most industries.

Industry results

Aggregate trends are interesting, but the dynamics of individual industries are more informative: σ and γ cannot explain the broad trends but they probably matter for some industries. To obtain a systematic classification of industry-level changes, we perform a principal components analysis (PCA) on a wide range of measures related to competition. We find that the first principal component, PC1, captures the σ and γ theories of good concentration while the second principal component, PC2, captures theories of bad concentration. This distinction is quite stark and allows us to show which industries have experienced good versus bad concentration and compare the importance of each theory over time.

Durable computer manufacturing exhibits the highest loading on PC1. It exhibits high intangible capital intensity but remains relatively competitive, likely as a result of intense foreign competition. By contrast, telecommunications, banking, and airlines are predominantly explained by κ, consistent with the results of Gutiérrez and Philippon (2018). They exhibit high concentration, high profits, and low productivity growth. Interestingly, some industries, such as nondurable chemical manufacturing and information (data), load heavily on both PC1 and PC2. These industries hold large amounts of intangible assets but also exhibit high barriers to entry. They are good examples of intangible assets giving rise to barriers to entry, as emphasized by Crouzet and Eberly (2018). In fact, Crouzet and Eberly (2018) argue that the health-care sector, which includes nondurable chemical manufacturing, is one where market power derived from intangible assets is largest.

Looking at the evolution of loadings over time further emphasizes the transition from good to bad concentration. The average PC1 score (reflecting good concentration) was substantially higher than PC2 in 1997 and increased faster from 1997 to 2002. But PC2 caught up afterward and, by 2012, explained a larger portion of industry dynamics. Our results therefore indicate that the US economy has transitioned from good to bad concentration over the past 30 years.

Related literature

Our paper contributes to a growing literature studying trends in competition and concentration in the US economy. The literature began by (separately) documenting the stylized facts. Haltiwanger, Jarmin, and Miranda (2011, 2) find that job creation and destruction both exhibit a downward trend over the past few decades. Decker et al. (2015) argue that, whereas in the 1980s and 1990s declining dynamism was observed in selected sectors (notably retail), the decline was observed across all sectors in the 2000s, including the traditionally high-growth information technology (IT) sector. CEA (2016) and Grullon et al. (2019) document the broad increases in profits and concentration; Elsby, Hobijn, and Sahin (2013) and Karabarbounis and Neiman (2014) document the decline in the labor share; and IMF (2014), Hall (2015), and Fernald et al. (2017) discuss the decline in investment in the context of weak overall growth. Akcigit and Ates (2019) review some of the literature.

Over time, the literature began to connect these facts and propose theories of good and bad concentration (we use good and bad for didactic purposes). The most prominent explanations of good concentration include Autor et al. (2017a) and Van Reenen (2018, 1), who argue that rising concentration and declining labor shares are explained by an increase in σ, which results in winner take most/all competition, and Alexander and Eberly (2018) and Crouzet and Eberly (2018), who link the rise in concentration and the decline in investment to intangible capital. Bessen (2017) links IT use to industry concentration. Ganapati (2018) links concentration to increasing labor productivity and stable prices. Aghion et al. (2019) and Ridder (2019) develop models where information and communication technologies increase returns to scale, leading to higher concentration and lower labor shares.

Moving to bad concentration, Grullon et al. (2019) show that firms in concentrating industries exhibit higher profits, positive abnormal stock returns, and more profitable merger and acquisition deals. Barkai (2017) documents a rise in economic profits and links it to concentration and labor shares. De Loecker, Eeckhout, and Unger (2019) argue that markups have increased. Gutiérrez and Philippon (2016) link the weakness of investment to rising concentration and market power, while Lee, Shin, and Stulz (2016) find that capital stopped flowing to high Q industries in the late 1990s. Eggertsson, Robbins, and Wold (2018) introduce time-varying market power to a standard neoclassical model to explain several of our stylized facts. Gutiérrez and Philippon (2018), Jones, Gutiérrez, and Philippon (2019), and Gutiérrez and Philippon (2019) argue that domestic competition has declined in many US industries because of increasing entry costs, lax antitrust enforcement, and lobbying.

We would like to note that this debate between good and bad concentration has a direct precedent in the industrial organization literature of the 1970s and 1980s. By then, the discussion was centered on how to interpret the positive correlation between profits and concentration at the industry level, first documented by Bain (1951). While this fact was commonly rationalized as evidence of market power (bad concentration), Demsetz (1973) argued that the observed pattern was instead explained by differences in productivity (good concentration). This seminal contribution spawned a series of empirical papers evaluating these two hypotheses, reviewed in Schmalensee (1987).

Finally, our paper is also related to the effect of foreign competition, particularly from China (see Bernard et al. 2012 for a review). Bernard, Jensen, and Schott (2006) show that capital-intensive plants and industries are more likely to survive and grow in the wake of import competition. Bloom, Draca, and Van Reenen (2016) argue that Chinese import competition leads to increased technical change within firms and a reallocation of employment toward more technologically advanced firms. Frésard and Valta (2015) find that tariff reductions lead to declines in investment in markets with competition in strategic substitutes and low costs of entry. Within industry, they find that investment declines primarily at financially constrained firms. The decline in investment is negligible for financially stable firms and firms in markets featuring competition in strategic complements. Hombert and Matray (2015) show that research and development (R&D)–intensive firms were better able to cope with Chinese competition than low-R&D firms. They explain this result based on product differentiation, using the Hoberg and Phillips (2017) product similarity index. Autor, Dorn, and Hanson (2013), Pierce and Schott (2016), Autor, Dorn, and Hanson (2016), and Feenstra, Ma, and Xu (2017) study the effects of Chinese import exposure on US manufacturing employment. Feenstra and Weinstein (2017) estimate the impact of globalization on markups, and conclude that markups decreased in industries affected by foreign competition. Some of these papers find a reduction in investment for the average firm, which is consistent with our results and highlights the importance of considering industry leaders and laggards separately.

The remainder of this paper is organized as follows. Section I derives theoretical predictions. Section II discusses measurement issues related to common empirical proxies of competition. Section III tests aggregate predictions related to business dynamism, productivity, prices, investment, and returns to scale. Section IV replicates the exercise at the industry level, using PCA. Section V concludes.

I. Theory

We use a few simple models to derive testable predictions for the various hypotheses. The timing of the models follows the classic model of Hopenhayn (1992): (i) there is a sunk entry cost κ; (ii) firms draw their productivities a (and/or idiosyncratic demand shocks); and (iii) they either produce with a fixed operating cost ϕ or they exit early.

A. Good Concentration, Bad Concentration

Let us start with the simple case where there is no heterogeneity. Consider, then, an industry with N , and industry demand Y. Suppose the game among the N firms leads to a markup μ over marginal cost. In other words, firms set the price

and firm i’s profits are

In a symmetric equilibrium with identical firms, all firms produce

So profits are

Under free entry, we have

where r is the discount rate, δ is the (exogenous) exit rate, and κ is the sunk entry cost. The free entry condition is then

. We then have the following proposition.

Proposition 1.In response to shocks to ex post markups μ, concentration is positively related to competition. In response to shocks to κ, concentration is negatively related to competition.

This proposition summarizes the fundamental issue with using concentration as a proxy for competition. Concentration is endogenous and can signal either increasing or decreasing degrees of competition. In other words, when looking at concentration measures, it is crucial to take a stand on why concentration is changing, in particular to see whether it is driven by shrinking margins or by higher barriers to entry.

Corollary 1.Concentration is a valid measure of market power only when concentration is driven by barriers to entry or by mergers.

, which shows that our propositions are valid when markups vary with concentration.

B. Selection and Ex Post Profits

) and the number of firms that actually produce (N). Formally, consider the following industry entry game:

exit early. The