Monthly Archives: July 2017

Knowledge in Mining does matter. But not any Knowledge.

The Mining Sectors in Chile and Norway, ca. 1870 – 1940: the Development of a Knowledge Gap

By: Kristin Ranestad (University of Oslo)

Abstract: Chile and Norway are two ‘natural resource intensive economies’, which have had different development trajectories, yet are closely similar in industrial structure and geophysical conditions. The questions of how and why Chile and Norway have developed so differently are explored through an analysis of how knowledge accumulation occurred and how it was transformed by learning into technological innovation in mining, a sector which has long traditions in Norway and has been by far the largest export sector in Chile for centuries. Similar types of ‘knowledge organisations’ with the direct aim of developing knowledge for mining were developed in both countries. Formal mining education, scientifically trained professionals, organisations for technology transfer and geological mapping and ore surveys are compared in the search for differences which may explain the underlying reasons for variations in economic growth.


Distributed by NEP-HIS on: 2016-11-13

Review by Miguel A. López-Morell (University of Murcia)

The effect of mining on the economic development of countries with abundant natural resources is a central issue of the history of economics. The question is straightforward: Why does mining have a positive effect on some countries while in others its contributions to the economic development are scant, not to mention the huge environmental problems that mineral extraction and processing generate? The “resource curse” myth does, unfortunately, hold true in most developing economies, but it is hard to take on board when we consider countries with very long mining traditions like Australia, the USA and Canada, to mention but three, and their high levels of income. There is, therefore, a need for studies that do not demonize the sector but rather search out deep causes and well-founded arguments to explain the conditions in which mining has a positive effect, or other, on development.


Mines in Antofagasta (Chile). Source: Tapia, Daniela. “Distrito Minero Centinela: La ambiciosa apuesta de Antofagasta Minerals.” Nueva Minería y Energía, November 17, 2014, link.


Kristin Ranestad approaches the issue from a comparative institutional perspective. The examples she uses, Chile and Norway, are in some ways congruent, in that both have a long mining tradition and they are not dependent countries with development problems; indeed, in terms of development per inhabitant, they are clear leaders in South America and Europe.

Ranestad identifies the similarities and differences in the levels of education of the mining engineers and technicians; the proportional presence of the latter in mining; the deployment of advanced information systems, such as scientific journals or attendance at congresses and exhibitions; the existence of study travels and work abroad; and the intensity of geological mapping and ore surveys.

The conclusions Ranestad draws leave little room for doubt. All the above facets that affect technological knowledge in modern mining are to be found in both countries, yet there are important differences in terms of quality and quantity, with Norway always coming out on top, except in terms of university education. Chile loses out as there is no direct relationship between the size of the mining sector and the level of development of other factors, where it trails Norway by some way.

The reasons, although not explained in depth here, lie to a large extent in the presence of large North American groups like Kennecot or Anaconda in Chile since the First World War. These controlled the huge deposits of Chuquicamata or El Teniente, where they introduced modern mining production technologies that boosted export capacity, although they always acted in isolation. At the same time, there was a large group of small and medium size Chilean mines that was working with minimum technology, almost non-existent externalities and a highly deficient exploitation of the deposits, which were frequently abandoned well before they had been fully exploited with the technology of the time. In contrast, Norway was streets ahead in all aspects and its mines were far more diversified and making far better use of their resources. They were also far more in tune with the economic environment.

The approach seems to be an interesting one since economic historians frequently, and mistakenly, argue in favor of the importance of quickly reaching historical landmarks that affect institutional and technological development, while overlooking the real significance of these for the production system. We tend to give an overwhelming importance to the age of technical schools, professional associations or scientific publications rather than to reflect more on how much influence they have had and how mature they are.

There may be some question marks hanging over Ranestad’s figures for the numbers of active engineers in each country. According to her reasoning and to the sources consulted, the argument stems from the idea that training was an endogenous affair since she draws on the mining schools’ own records to fix the figures of engineers. So we cannot, on the basis of the information provided, know what percentage of engineers had been trained abroad. In Spain, for example, which was a leading mining power at the time, there was a relatively high number of engineers who had studied abroad prior to the Second World War. Indeed, foreigners and Spaniards who had studied abroad accounted for some 250 mining engineers, according to one database constructed using the annuals of mining engineers, even though it did not include man professionals working in large companies in Spain, like Rio Tinto Co, Tharsis, la Asturiana or Peñarroya, which did not even bother to inform about such matters (see Bertilorenzi, Passaqui and Garçon 2016, pp. 143-162). The author herself, when talking about foreign engineers, notes: “However, their dominance was negative in the sense that the lack of collaboration with domestic engineers and leaders prevented knowledge transfer within the sector”. Yet she does not back this up with hard figures.

Nevertheless, her contribution is a valuable one which affords a novel approach that is perfectly applicable to other works of comparative economic history. In the case of Chile, there is no explanation of the differences to the sector following the nationalization of the copper industry between 1853 and 1971. In perspective, though, it is not comparable with the Norwegian situation in the sense of the sector’s capacity to transfer knowledge to other sectors and to the country as a whole. A prime example is Orkla, which is today a huge, widely diversified conglomerate that has little do to with mining, but which in the 1920s produced copper and pyrites more profitably than its competitors, despite its mineral being 10% poorer in quality. It would even sell technology to Rio Tinto, no less. It would also be worthwhile analyzing whether the nationalization of copper mining and the government control of oil in Norway have had similar repercussions for the inhabitants of each country. A starting point would be to ask Chilean pensioners whether they have similar benefits to their Norwegian counterparts, even though the answer does seem foregone.


Bertilorenzi, Marco; Passaqui, Jean-Philippe and Garçon, Anne-Françoise (dirs.) (2016) Entre technique et gestion, une histoire des « ingénieurs civils des mines » (XIXe-XXe siècles).París, Press des mines

Harvey, C. and Press, J. (1989) “Overseas Investment and the Professional Advance of British Metal Mining Engineers, 1851 – 1914”, Economic History Review 1989, 42 (1) pp. 64-86.

Mokyr, Joel (2002) The Gifts of Athena: Historical Origins of the Knowledge Economy. Princeton: Princeton University Press.

Rosenberg, Nathan (1982) Inside the Black Box: Technology and Economics. Cambridge: Cambridge University Press.


(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.


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.


“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.


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.