Tag Archives: GDP

(Superstar) Firms and Inequality

The Fall of the Labor Share and the Rise of Superstar Firms

By: David Autor (MIT, NBER and IZA), David Dorn (University of Zurich and IZA), Lawrence F. Katz (Harvard University, NBER and IZA), Christina Patterson (MIT) and John Van Reenen (MIT, NBER and IZA)

Abstract: The fall of labor’s share of GDP in the United States and many other countries in recent decades is well documented but its causes remain uncertain. Existing empirical assessments of trends in labor’s share typically have relied on industry or macro data, obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S. Economic Census since 1982 and international sources and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of “superstar firms.” If globalization or technological changes advantage the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms with high profits and a low share of labor in firm value-added and sales. As the importance of superstar firms increases, the aggregate labor share will tend to fall. Our hypothesis offers several testable predictions: industry sales will increasingly concentrate in a small number of firms; industries where concentration rises most will have the largest declines in the labor share; the fall in the labor share will be driven largely by between-firm reallocation rather than (primarily) a fall in the unweighted mean labor share within firms; the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; and finally, such patterns will be observed not only in U.S. firms, but also internationally. We find support for all of these predictions.

URL: http://EconPapers.repec.org/RePEc:iza:izadps:dp10756

Distributed by NEP-HIS on: 2017‒05‒28

Review by: Sebastian Fleitas (University of Arizona)

In the last few years, inequality has been at the center of many political and academic debates. It turns out that, although less mentioned in these debates, the rapid growth of some developing countries in the last decades has actually decreased global inequality. But then, why is there a big debate about inequality? The issue is that, on the other hand, inequality in developed countries has been increasing over time. From the perspective of the functional distribution of income between labor and capital, one of the indicators of this increase in inequality is that the labor’s share of GDP has been falling in the United States and other countries in recent decades. These forces have generated winners and losers. As economist Branko Milanovic points out with his famous “elephant chart,” the middle class of the world and the very rich of the world are the two groups whose incomes have increased more rapidly. In contrast, it can be easily seen that there are large groups of people uncomfortable with increased inequality. Moreover, the factors assumed to be causing inequality have taken a vital role in political debates and recent elections.

ElephantChart

“Elephant Chart”: Lakner & Milanovic (2016)

In this context, it is extremely important to understand what is driving these changes in inequality. There are different approaches to understand the increase in inequality in developed countries. The two main perspectives point to the importance of top incomes and changes in the tax system (e.g. Piketty and Saez, 2014), on one hand, and to changes in the labor market, mainly related to the incorporation of technological change that is more favorable to skilled workers (e.g. Autor, 2014), on the other. More recent approaches have begun to more directly incorporate the role of firms. For example, a growing literature estimates models to separate the firm’s and employee’s contributions to wage differences via double fixed-effects models, with many studies finding that firm wage effects account for approximately 20% of the overall variance of wages and have had an increasingly important role over time (e.g. Card et al., 2016). However, while we can all see that “superstar firms” like Apple, Microsoft, Google or many others in different sectors of the economy are growing very quickly, we still do not know what their effect of inequality is.

Do these “superstar firms” increase inequality because they are responsible for the decrease in labor’s share? The paper by Autor, Dorn, Katz, Patterson and Van Reenen addresses exactly this issue. If we are interested in understanding the role of firms in the increase in inequality, it is particularly important to answer the question of whether the decrease in labor’s share of income can be explained by technological changes occurring within firms, or if it is better explained by a rise of “superstar” firms, which tend to use new technologies and are more capital-intensive. The main argument of the authors is that markets have changed in such a way that firms with superior quality, lower costs, or greater innovation get disproportionately high rewards relative to previous periods. Since these “superstar firms” have higher profit levels, they also tend to have a lower share of labor in sales and value-added. Therefore, as these firms gain market share across a wide range of sectors, the aggregate share of labor falls. In this way, “superstar firms” are one of the drivers of the decrease in labor’s share (in favor of capital’s share) of value added.

Before they start developing the evidence for this argument, the authors clearly document the fall in labor’s share of GDP in the United States and other developed countries. After that, they formalize their main argument in a model of “superstar firms,” in order to derive the set of predictions that will be taken to the data. With this model in hand, the authors use several sources of information (U.S. Economic Census, KLEMS, UN Comtrade Database, and others) to run a series of regressions and decompositions to analyze the testable predictions of the model. First, the authors find that sales concentration levels have risen in most sectors. Second, they show that the larger decreases in labor’s share are observed in industries where concentration has increased the most. Third, by comparing the weighted and unweighted mean of labor’s share, the authors conclude that the fall in labor’s share has an important component of reallocation between (and not within) firms. Furthermore, they find that the between-firm reallocation of labor’s share is greatest in the sectors that are concentrating the most. Finally, these patterns are not only present in the US but also in many European countries.

Overall, all of these findings are consistent with the idea of a rise of “superstar firms” that have lower labor’s share, and which have gained more importance by concentrating large shares of sales in different sectors of the economy. It should be noted, however, that the authors do not provide a clean causal identification of the superstar firm model. The empirical exercises are done carefully and controlling for the factors that can more clearly affect the tested relationships. The use of fixed effects and trends by industry allow the authors to obtain identification exclusively from the acceleration or deceleration of labor’s shares and concentration conditional on these controlled trends. Thus, any potential threat to this identification strategy would have to come from other factors not captured by these trends or fixed effects and which are correlated with industry concentration and inequality.

This paper makes a major contribution by pointing out the role of “superstar firms” in explaining increasing inequality and opens some avenues for future research in a direction that had not been typically considered in the literature. In this sense, a particularly interesting direction would be to use the matched employer-employee databases with census data on sales to test if industry concentration has impacts on the firm component of wages and the within and between firm decomposition in each sector.

Sweated LabourFinally, the paper addresses the question of what is the driver of the growth of these “superstar firms.” The main debate here is whether the rise of these “superstar firms” and industry concentration are associated with competitive forces, or if they are a signal of an economy with competition problems. Increased concentration can be a result of technological changes: some sectors could be introducing technologies that have a “winner takes all” aspect. An alternative, more worrisome story is that leading firms are less exposed to competition because they can create barriers to entry or have more lobbying power. The authors provide evidence that is somewhat comforting about this point. They show that concentration is greater in industries experiencing faster technical change, approximated either by patent activity or by total factor productivity growth. However, this evidence is still subject to debate. It could be the case that these originally innovative firms are now using their market power to generate barriers to entry. This can be even more important in some technology sectors where network effects generate an important advantage to the innovators. I think this discussion is actually one of the main directions where this stream of research can be expanded and complemented in the future. In this sense, for example, sector-specific partial equilibrium models could allow formalizing the product and labor markets under innovation dynamics, and such models could be estimated using data for specific industries and structural econometrics estimation techniques.

To sum up, I think that this paper makes a major contribution by pointing out the effect of “superstar firms” on the decrease of labor’s share of GDP, and therefore increased inequality in developed countries. Additionally, this paper opens several avenues for future work in order to generate more evidence consistent with the “superstar firms” model and, critically, to understand its causes and consequences at the individual micro level, especially using matched individual and firm level databases and sector-specific analysis. To understand the relationship between firms and inequality is a key task in a world of “superstar firms,” and these are key inputs for the discussion of, for example, the roles of tax policies, labor market institutions and their relationship with the increasing heterogeneity of firms.

REFERENCES

Autor, D. (2014). Skills, Education, and the Rise of Earnings Inequality Among the “Other 99 Percent.” Science 344 (6186), 843-851.

Card, D., Cardoso, A. R., Heining, J., & Kline, P. (2016). Firms and Labor Market Inequality: Evidence and Some Theory. National Bureau of Economic Research Working Paper 22850

Lakner, C., & Milanovic, B. (2016). Global Income Distribution: From the Fall of the Berlin Wall to the Great Recession. World Bank Economic Review 30(2), 203-232.

Piketty, T., & Saez, E. (2014). Inequality in the Long Run. Science 344(6186), 838-843.

 

 

The challenges of updating the contours of the world economy (1AD – today)

The First Update of the Maddison Project: Re-estimating Growth Before 1820

by Jutta Bolt (University of Groningen) and Jan Luiten van Zanden (Utrecht University)

Abstract: The Maddison Project, initiated in March 2010 by a group of close colleagues of Angus Maddison, aims to develop an effective way of cooperation between scholars to continue Maddison’s work on measuring economic performance in the world economy. This paper is a first product of the project. Its goal is to inventory recent research on historical national accounts, to briefly discuss some of the problems related to these historical statistics and to extend and where necessary revise the estimates published by Maddison in his recent overviews (2001; 2003; 2007) (also made available on his website at http://www.ggdc.net/MADDISON/oriindex.htm).

URL http://www.ggdc.net/maddison/publications/wp.htm

Review by Emanuele Felice

Angus Maddison (1926-2010) left an impressive heritage in the form of his GDP estimates. These consider almost all of the world, from Roman times until our days, and are regularly cited by both specialists and non-specialists for long-run comparisons of economic performance. The Maddison project was launched in March 2010 with the aim of expanding and improving Maddison’s work. One of the first products is the paper by Jutta Bolt and Jan Luiten van Zanden, which aims to provide an inventory while also critically review the available research on historical national accounts. It also aims “to extend and where necessary revise” Maddison’s estimates. This paper was circulated by NEP-HIS on 2014-01-26.

The paper starts by presenting, in a concise but clear way, the reasons that motivated the Maddison’s project and its main goals. It also tells that some issues are left to be the subject of future work, particularly thorny issues left out include the use of 2005 purchasing power parities rather than Maddison’s (1990) ones; and the consistency of benchmarks and time series estimates over countries and ages.

Jutta Bolt

Firstly (and fairly enough, from a ontological perspective) Bolt  and van Zanden deal with the possibility of providing greater transparency in the estimates. Instead of presenting the margins of errors of each estimate (which in turn would be based “on rather subjective estimates of the possible margins of error of the underlying data”), the authors, following an advice by Steve Broadberry, choose to declare explicitly the provenance of the estimates and the ways in which they have been produced. This leads to classifying Maddison’s estimates in four groups: a) official estimates of GDP, released by national statistical offices or by international agencies; b) historical estimates (that is, estimates produced by economic historians) which roughly follow the same method as the official ones and are based on a broad range of data and information; c) historical estimates based on indirect proxies for GDP (such as wages, the share of urban population, etc.); d) “guess estimates”.

Jan Luiten van Zanden

Then the article moves on to review and discuss new estimates: although revisions for the nineteenth and twentieth century (mostly falling under the “b” category) are also incorporated, the most important changes come from the pre-industrial era (“c” kind estimates). For Europe, we now have a considerable amount of new work, for several countries including England, Holland, Italy, Spain and Germany (but not for France). The main result is that, from 1000 to 1800 AD, growth was probably more gradual than what proposed by Maddison; that is, European GDP was significantly higher in the Renaissance (above 1000 PPP 1990 dollars in 1500, against 771 proposed by Maddison); hence, growth was slower in the following three centuries (1500-1800), while faster in the late middle ages (1000-1500). For Asia, the new (and in some cases very detailed) estimates available for some regions of India (Bengal) and China (the Yangzi Delta), for Indonesia and Java, and for Japan, confirm Maddison’s view of the great divergence, against Pomeranz revisionist approach: in the late eighteenth and early nineteenth century, a significant gap between Europe and Asia was already present (for instance GDP per capita in the whole of China was 600 PPP 1990 dollars in 1820, as in Maddison; against 1455 of Western Europe, instead of 1194 proposed by Maddison).

New estimates are also included for some parts of Africa and for the Americas, with marginal changes on the overall picture (for the whole of Latin America, per capita GDP in 1820 is set to 628 PPP 1990 dollars, instead of 691). For Africa, however, there are competing estimates for the years 1870 to 1950, by Leandro Prados de la Escosura (based on the theoretical relationship between income terms of trade per head and GDP per capita) on the one side, and Van Leeuwen, Van Leeuwen-Li and Foldvari (mostly based on real wage data, deflated with indigenous’ crops prices) on the other. The general trends of these differ substantially: the authors admit that they “are still working on ways to integrate this new research into the Maddison framework” and thus at the present no choice is made between the two, although both are included in the data appendix.

New long-run estimates are presented also for the Near East, as well as for the Roman world, in this latter case with some differences (smaller imbalances between Italy and the rest of the empire) as compared to Maddison’s picture. The authors also signal the presence of estimates for ancient Mesopotamia, produced by Foldvari and Van Leeuwen, which set the level of average GDP a bit below that of the Roman empire (600 PPP 1990 dollars per year, versus 700), but they are not included in the dataset.

Per capita GDP in Roman times, according to Maddison (1990 PPP dollars)

Per capita GDP in Roman times, according to Maddison (1990 PPP dollars)

What can we say about this impressive work? First, that it is truly impressive and daring. But then come the problems. Needless to say Maddison’s guessed estimates is one of the main issues or limitations, and this looks kind of downplayed by Bolt and van Zanden. As pointed out by Gregory Clark, in his 2009 Review of Maddison’s famous Contours of the World Economy:

“All the numbers Maddison estimates for the years before 1820 are fictions, as real as the relics peddled around Europe in the Middle Ages (…) Just as in the Middle Ages, there was a ready market for holy relics to lend prestige to the cathedrals and shrines of Europe (…), so among modern economists there is a hunger by the credulous for numbers, any numbers however dubious their provenance, to lend support to the model of the moment. Maddison supplies that market” (Clark 2009, pp. 1156-1157).

The working paper by Bolt and Van Zanden makes significant progress in substituting some fictitious numbers (d), with indirect estimates of GDP (c), but then in discussing the results it leaves unclear which numbers are reliable, which not, thus still leaving some ground for the “market for holy relics”.

Image

This is all the more problematic if we think that nominally all the estimates have been produced at 1990 international dollars. It is true that there is another part of the Maddison project specifically aiming at substituting 1990 purchasing power parities with 2005 ones. But this is not the point. The real point is that even 2005 PPPs would not change the fact that we are comparing economies of distant times under the assumption that differences in the cost of living remained unchanged over centuries, or even over millennia. This problem, not at all a minor neither a new one − e.g. Prados de la Escosura (2000) − is here practically ignored. One indeed may have the feeling that the authors (and Maddison before them) simply don’t care about the parities they use, de facto treating them as if they were at current prices. For example, they discuss the evidence emerging from real wages, saying that they confirm the gaps in per capita GDP: but the gaps in real wages are usually at the current parities of the time, historical parities, while those in GDP are at constant 1990 parities. If we assume, as reasonably should be, that differences in the cost of living changed over the centuries, following the different timing of economic growth, then the evidence from real wages (at current prices) may actually not confirm the GDP figures (at constant 1990 PPPs). Let’s take, for instance, China. It could be argued that differences in the cost of living, as compared to Europe, were before the industrial revolution, say in 1820, lower than in 1990, given that also the differences in per capita GDP were lower in 1820 than in 1990; hence, prices in 1820 China were relatively higher. The same is true for China when compared to Renaissance or Roman Italy (since prices in 1990 China were arguably significantly lower than prices in 1990 Italy, in comparison with the differences in the sixteenth century or in ancient times). This would mean that real GDP at current PPPs would be in 1820 even lower, as compared to Europe; or that 1820 China would have a per capita GDP remarkably lower than that of the Roman empire, maybe even lower than that of ancient Mesopotamia. Is this plausible?

References

Clark, G. (2009). Review essay: Angus Maddison, Contours of the world economy, 1-2030 AD: essays in macro-economic history. Journal of Economic History 69(4): 1156−1161.

Prados de la Escosura, L. (2000). International comparisons of real product, 1820–1990: an alternative data set. Explorations in Economic History 37(1):1–41.