FIGURE 9.8. Income inequality in Europe versus the United States, 1900–2010
The top decile income share was higher in Europe than in the United States in 1900–1910; it is a lot higher in the United States in 2000–2010.
Sources and series: see piketty.pse.ens.fr/capital21c.
If we calculate (somewhat abusively) an average for Europe based on these four countries, we can make a very clear international comparison: the United States was less inegalitarian than Europe in 1900–1910, slightly more inegalitarian in 1950–1960, and much more inegalitarian in 2000–2010 (see Figure 9.8).25
Apart from this long-term picture, there are of course multiple national histories as well as constant short- and medium-term fluctuations linked to social and political developments in each country, as I showed in Chapter 8 and analyzed in some detail in the French and US cases. Space will not permit me to do the same for every country here.26
In passing, however, it is worth mentioning that the period between the two world wars seems to have been particularly tumultuous and chaotic almost everywhere, though the chronology of events varied from country to country. In Germany, the hyperinflation of the 1920s followed hard on the heels of military defeat. The Nazis came to power a short while later, after the worldwide depression had plunged the country back into crisis. Interestingly, the top centile’s share of German national income increased rapidly between 1933 and 1938, totally out of phase with other countries: this reflects the revival of industrial profits (boosted by demand for armaments), as well as a general reestablishment of income hierarchies in the Nazi era. Note, too, that the share of the top centile—and, even more, the top thousandth—in Germany has been noticeably higher since 1950 than in most other continental European countries (including, in particular, France) as well as Japan, even though the overall level of inequality in Germany is not very different. This can be explained in various ways, among which it is difficult to say that one is better than another. (I will come back to this point.)
In addition, there are serious lacunae in German tax records, owing in large part to the country’s turbulent history in the twentieth century, so that it is difficult to be sure about certain developments or to make sharp comparisons with other countries. Prussia, Saxony, and most other German states imposed an income tax relatively early, between 1880 and 1890, but there were no national laws or tax records until after World War I. There were frequent breaks in the statistical record during the 1920s, and then the records for 1938 to 1950 are missing altogether, so it is impossible to study how the income distribution evolved during World War II and its immediate aftermath.
This distinguishes Germany from other countries deeply involved in the conflict, especially Japan and France, whose tax administrations continued to compile statistics during the war years without interruption, as if nothing were amiss. If Germany was anything like these two countries, it is likely that the top centile’s share of national income reached a nadir in 1945 (the year in which German capital and income from capital were reduced to virtually nothing) before beginning to rise sharply again in 1946–1947. Yet when German tax records return in 1950, they show the income hierarchy already beginning to resemble its appearance in 1938. In the absence of complete sources, it is difficult to say more. The German case is further complicated by the fact that the country’s boundaries changed several times during the twentieth century, most recently with the reunification of 1990–1991, in addition to which full tax data are published only every three years (rather than annually as in most other countries).
Inequalities in Emerging Economies: Lower Than in the United States?
Let me turn now to the poor and emerging economies. The historical sources we need in order to study the long-run dynamics of the wealth distribution there are unfortunately harder to come by than in the rich countries. There are, however, a number of poor and emerging economies for which it is possible to find long series of tax data useful for making (rough) comparisons with our results for the more developed economies. Shortly after Britain introduced a progressive income tax at home, it decided to do the same in a number of its colonies. Thus an income tax fairly similar to that introduced in Britain in 1909 was adopted in South Africa in 1913 and in India (including present-day Pakistan) in 1922. Similarly, the Netherlands imposed an income tax on its Indonesian colony in 1920. Several South American countries introduced an income tax between the two world wars: Argentina, for example, did so in 1932. For these four countries—South Africa, India, Indonesia, and Argentina—we have tax data going back, respectively, to 1913, 1922, 1920, and 1932 and continuing (with gaps) to the present. The data are similar to what we have for the rich countries and can be employed using similar methods, in particular national income estimates for each country going back to the turn of the twentieth century.
My estimates are indicated in Figure 9.9. Several points deserve to be emphasized. First, the most striking result is probably that the upper centile’s share of national income in poor and emerging economies is roughly the same as in the rich economies. During the most inegalitarian phases, especially 1910–1950, the top centile took around 20 percent of national income in all four countries: 15–18 percent in India and 22–25 percent in South Africa, Indonesia, and Argentina. During more egalitarian phases (essentially 1950–1980), the top centile’s share fell to between 6 and 12 percent (barely 5–6 percent in India, 8–9 percent in Indonesia and Argentina, and 11–12 percent in South Africa). Thereafter, in the 1980s, the top centile’s share rebounded, and today it stands at about 15 percent of national income (12–13 percent in India and Indonesia and 16–18 percent in South Africa and Argentina).
Figure 9.9 also shows two countries for which the available tax records allow us only to study how things have changed since the mid-1980s: China and Colombia.27 In China, the top centile’s share of national income rose rapidly over the past several decades but starting from a fairly low (almost Scandinavian) level in the mid-1980s: less than 5 percent of national income went to the top centile at that time, according to the available sources. This is not very surprising for a Communist country with a very compressed wage schedule and virtual absence of private capital. Chinese inequality increased very rapidly following the liberalization of the economy in the 1980s and accelerated growth in the period 1990–2000, but according to my estimates, the upper centile’s share in 2000–2010 was 10–11 percent, less than in India or Indonesia (12–14 percent, roughly the same as Britain and Canada) and much lower than in South Africa or Argentina (16–18 percent, approximately the same as the United States).
FIGURE 9.9. Income inequality in emerging countries, 1910–2010
Measured by the top percentile income share, income inequality rose in emerging countries since the 1980s, but ranks below the US level in 2000–2010.
Sources and series: see piketty.pse.ens.fr/capital21c.
Colombia on the other hand is one of the most inegalitarian societies in the WTID: the top centile’s share stood at about 20 percent of national income throughout the period 1990–2010, with no clear trend (see Figure 9.9). This level of inequality is even higher than that attained by the United States in 2000–2010, at least if capital gains are excluded; if they are included, the United States was slightly ahead of Colombia over the past decade.
It is important, however, to be aware of the significant limitations of the data available for measuring the dynamics of the income distribution in poor and emerging countries and for comparing them with the rich countries. The orders of magnitude indicated here are the best I was able to come up with given the available sources, but the truth is that our knowledge remains meager. We have tax data for the entire twentieth century for only a few emerging economies, and there are many gaps and breaks in the data, often in the period 1950–1970, the era of independence (in Indonesia, for example). Work is going forward to update the WTID with historical data from many other countries, especially from among the former British and French col
onies, in Indochina and Africa, but data from the colonial era are often difficult to relate to contemporary tax records.28
Where tax records do exist, their interest is often reduced by the fact that the income tax in less developed countries generally applies to only a small minority of the population, so that one can estimate the upper centile’s share of total income but not the upper decile’s. Where the data allow, as in South Africa for certain subperiods, one finds that the highest observed levels for the top decile are on the order of 50–55 percent of national income—a level comparable to or slightly higher than the highest levels of inequality observed in the wealthy countries, in Europe in 1900–1910 and in the United States in 2000–2010.
I have also noticed a certain deterioration of the tax data after 1990. This is due in part to the arrival of computerized records, which in many cases led the tax authorities to interrupt the publication of detailed statistics, which in earlier periods they needed for their own purposes. This sometimes means, paradoxically, that sources have deteriorated since the advent of the information age (we find the same thing happening in the rich countries).29 Above all, the deterioration of the sources seems to be related to a certain disaffection with the progressive income tax in general on the part of certain governments and international organizations.30 A case in point is India, which ceased publishing detailed income tax data in the early 2000s, even though such data had been published without interruption since 1922. As a result, it is harder to study the evolution of top incomes in India since 2000 than over the course of the twentieth century.31
This lack of information and democratic transparency is all the more regrettable in that the question of the distribution of wealth and of the fruits of growth is at least as urgent in the poor and emerging economies as in the rich ones. Note, too, that the very high official growth figures for developing countries (especially India and China) over the past few decades are based almost exclusively on production statistics. If one tries to measure income growth by using household survey data, it is often quite difficult to identify the reported rates of macroeconomic growth: Indian and Chinese incomes are certainly increasing rapidly, but not as rapidly as one would infer from official growth statistics. This paradox—sometimes referred to as the “black hole” of growth—is obviously problematic. It may be due to the overestimation of growth of output (there are many bureaucratic incentives for doing so), or perhaps the underestimation of income growth (household surveys have their own flaws), or most likely both. In particular, the missing income may be explained by the possibility that a disproportionate share of the growth in output has gone to the most highly remunerated individuals, whose incomes are not always captured in the tax data.
In the case of India, it is possible to estimate (using tax return data) that the increase in the upper centile’s share of national income explains between one-quarter and one-third of the “black hole” of growth between 1990 and 2000.32 Given the deterioration of the tax data since 2000, it is impossible to do a proper social decomposition of recent growth. In the case of China, official tax records are even more rudimentary than in India. In the current state of research, the estimates in Figure 9.9 are the most reliable we have.33 It is nevertheless urgent that both countries publish more complete data—and other countries should do so as well. If and when better data become available, we may discover that inequality in India and China has increased more rapidly than we imagined.
In any case, the important point is that whatever flaws the tax authorities in poor and emerging countries may exhibit, the tax data reveal much higher—and more realistic—top income levels than do household surveys. For example, tax returns show that the top centile’s share of national income in Colombia in 2000–2010 was more than 20 percent (and almost 20 percent in Argentina). Actual inequality may be even greater. But the fact that the highest incomes declared in household surveys in these same countries are generally only 4 to 5 times as high as the average income (suggesting that no one is really rich)—so that, if we were to trust the household survey, the top centile’s share would be less than 5 percent—suggests that the survey data are not very credible. Clearly, household surveys, which are often the only source used by international organizations (in particular the World Bank) and governments for gauging inequality, give a biased and misleadingly complacent view of the distribution of wealth. As long as these official estimates of inequality fail to combine survey data with other data systematically gleaned from tax records and other government sources, it will be impossible to apportion macroeconomic growth properly among various social groups or among the centiles and deciles of the income hierarchy. This is true, moreover, of wealthy countries as well as poor and emerging ones.
The Illusion of Marginal Productivity
Let me now return to the explosion of wage inequality in the United States (and to a lesser extent Britain and Canada) after 1970. As noted, the theory of marginal productivity and of the race between technology and education is not very convincing: the explosion of compensation has been highly concentrated in the top centile (or even the top thousandth) of the wage distribution and has affected some countries while sparing others (Japan and continental Europe are thus far much less affected than the United States), even though one would expect technological change to have altered the whole top end of the skill distribution in a more continuous way and to have worked its effects in all countries at a similar level of development. The fact that income inequality in the United States in 2000–2010 attained a level higher than that observed in the poor and emerging countries at various times in the past—for example, higher than in India or South Africa in 1920–1930, 1960–1970, and 2000–2010—also casts doubt on any explanation based solely on objective inequalities of productivity. Is it really the case that inequality of individual skills and productivities is greater in the United States today than in the half-illiterate India of the recent past (or even today) or in apartheid (or postapartheid) South Africa? If that were the case, it would be bad news for US educational institutions, which surely need to be improved and made more accessible but probably do not deserve such extravagant blame.
To my mind, the most convincing explanation for the explosion of the very top US incomes is the following. As noted, the vast majority of top earners are senior managers of large firms. It is rather naïve to seek an objective basis for their high salaries in individual “productivity.” When a job is replicable, as in the case of an assembly-line worker or fast-food server, we can give an approximate estimate of the “marginal product” that would be realized by adding one additional worker or waiter (albeit with a considerable margin of error in our estimate). But when an individual’s job functions are unique, or nearly so, then the margin of error is much greater. Indeed, once we introduce the hypothesis of imperfect information into standard economic models (eminently justifiable in this context), the very notion of “individual marginal productivity” becomes hard to define. In fact, it becomes something close to a pure ideological construct on the basis of which a justification for higher status can be elaborated.
To put this discussion in more concrete terms, imagine a large multinational corporation employing 100,000 people and with gross annual revenue of 10 billion euros, or 100,000 euros per worker. Suppose that half of this revenue figure represents purchases of goods and services by the firm (this is a typical figure for the economy as a whole), so that the value added by the firm—the value available to pay the labor and capital that it directly employs—is 5 billion euros, or 50,000 euros per worker. To set the pay of the firm’s CFO (or his deputies, or of the director of marketing and her staff, etc.), one would in principle want to estimate his marginal productivity, that is, his contribution to the firm’s value-added of 5 billion euros: is it 100,000, 500,000, or 5 million euros per year? A precise, objective answer to this question is clearly impossible. To be sure, one could in theory experiment by trying out several CFOs, each for several years, in order to determine wh
at impact the choice has on the firm’s total revenue of 10 billion euros. Obviously, such an estimate would be highly approximate, with a margin of error much greater than the maximum salary one would think of paying, even in a totally stable economic environment.34 And the whole idea of experimentation looks even more hopeless when one remembers that the environment is in fact changing constantly, as is the nature of the firm and the exact definition of each job.
In view of these informational and cognitive difficulties, how are such remunerations determined in practice? They are generally set by hierarchical superiors, and at the very highest levels salaries are set by the executives themselves or by corporate compensation committees whose members usually earn comparable salaries (such as senior executives of other large corporations). In some companies, stockholders are asked to vote on compensation for senior executives at annual meetings, but the number of posts subject to such approval is small, and not all senior managers are covered. Since it is impossible to give a precise estimate of each manager’s contribution to the firm’s output, it is inevitable that this process yields decisions that are largely arbitrary and dependent on hierarchical relationships and on the relative bargaining power of the individuals involved. It is only reasonable to assume that people in a position to set their own salaries have a natural incentive to treat themselves generously, or at the very least to be rather optimistic in gauging their marginal productivity. To behave in this way is only human, especially since the necessary information is, in objective terms, highly imperfect. It may be excessive to accuse senior executives of having their “hands in the till,” but the metaphor is probably more apt than Adam Smith’s metaphor of the market’s “invisible hand.” In practice, the invisible hand does not exist, any more than “pure and perfect” competition does, and the market is always embodied in specific institutions such as corporate hierarchies and compensation committees.
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