Russia is back in the news again in the United States, with the ongoing investigation of Russian interference in the U.S. presidential election as well as a growing set of links between a variety of figures (including Cabinet and family members) associated with Donald Trump and the regime of Vladimir Putin.

This year is also the hundredth anniversary of the October Revolution, which sought to create the conditions for a transition to communism in the midst of a society characterized by various forms of feudalism, peasant communism, and capitalism. But we shouldn’t forget that, in addition, the Red Century has clearly left its mark on the political economy of the West, including the United States—both in the early years, when the “communist threat” undoubtedly led to reforms associated with a more equal distribution of income, and later, when the Fall of the Wall reinforced the neoliberal turn to privatization and deregulation.

Now we have a third reason to think about Russia, which happens to intersect with the first two concerns. A new study of income and wealth data by Filip Novokmet, Thomas Piketty, Gabriel Zucman reveals just how much has changed in Russia from the time of the tsarist oligarchy through the Soviet Union to rise of the new oligarchy during and after the “shock therapy” that served to create a new form of private capitalism under Putin.

As is clear from the chart, income inequality was extremely high in Tsarist Russia, then dropped to very low levels during the Soviet period, and finally rose back to very high levels after the fall of the Soviet Union. Thus, for example, the top 1-percent income share was somewhat close to 20 percent in 1905, dropped to as little as 4-5 percent during the Soviet period, and rose spectacularly to 20-25 percent in recent decades.


The data sets used by Novokmet et al. reveal a level of inequality under the new oligarchs that is much higher that was the case using survey data—a top 1-percent income share that is more than double for 2007-08.


Novokmet et al. also show that the income shares of the top 10 percent and the bottom 50 percent moved in exactly opposite directions after the privatization of Russian state capitalism in the early 1990s. While the top 10-percent income share rose from less than 25 percent in 1990-1991 to more than 45 percent in 1996, the share of the bottom 50 percent collapsed, dropping from about 30 percent of total income in 1990-1991 to less than 10 percent in 1996, before gradually returning to 15 percent by 1998 and about 18 percent by 2015.


In comparison to other countries, Russia was much more equal during the Soviet period and, by 2015, had approached a level of inequality higher than that of France and comparable only to that of the United States.


Finally, Novokmet et al. have been able to estimate the enormous growth of private wealth under the new oligarchy, especially the wealth that was captured by a tiny group at the very top and is now owned by Russia’s billionaires. As the authors explain,

The number of Russian billionaires—as registered in international rankings such as the Forbes list—is extremely high by international standards. According to Forbes, total billionaire wealth was very small in Russia in the 1990s, increased enormously in the early 2000s, and stabilized around 25-40% of national income between 2005 and 2015 (with large variations due to the international crisis and the sharp fall of the Russian stock market after 2008). This is much larger than the corresponding numbers in Western countries: Total billionaire wealth represents between 5% and 15% of national income in the United States, Germany and France in 2005-2015 according to Forbes, despite the fact that average income and average wealth are much higher than in Russia. This clearly suggests that wealth concentration at the very top is significantly higher in Russia than in other countries.

Clearly, there is nothing “natural” about the distribution of income and the ownership of wealth. This new study demonstrates that different economic structures and political events create fundamentally different levels of inequality in both income and wealth, both within and between countries.

The Russian experience is a perfect example how inequality can fall and then, later, be reversed with radical economic and political transformations—thus creating a new oligarchy that dominates the national political economy and seeks to intervene in other countries.

Not unlike the United States.


Special mention



As regular readers know, I have written about minimum wages many times over the years on this blog. However, after reading about the much-publicized study by Ekaterina Jardim et al., according to which Seattle’s decision to raise the minimum wage actually hurt low-wage workers, I decided to turn to my old friend and minimum-wage expert Dale Belman to see what he thought of the study. Dale is a professor in the School of Human Resources & Labor Relations at Michigan State University and coauthor (with Paul J. Wolfson) of What Does the Minimum Wage Do? I am pleased to publish his guest post here. 

Seattle embarked on an audacious policy change in raising its minimum wage from $9.47 to $15.00 over five years.* The first two increments, to $11 in April 2016 and $13.00 in January 2017, have gone into effect. This policy has notable positive effects for employed low-wage workers and also provides an “experiment” central to the ongoing debate over the employment effects of the minimum wage.

The conventional analysis of the minimum wage suggests that, in the face of a typical (downward-sloping demand curve), a higher minimum wage must cause a reduction in the employment of workers “bound” by the new minimum wage–those who currently work between the old and new minimum wage. However, since 2000, a large body of empirical research has found few-if-any employment effects for historical increases in the minimum wage. Although not universally accepted, many economists are increasingly open to the view that moderate increases in the minimum wage may be good policy for low- wage workers, increasing their earnings with negligible employment costs.

An important remaining issue is whether increases outside of the range of historical experience, such as the increases sought by Fight for $15, reduce employment. The Seattle minimum-wage increase provides data to test the employment effect. One study, “Minimum Wage Increases, Wages, and Low-Wage Employment: Evidence from Seattle,” by Jardim et al., uses Washington state unemployment data that, unique among such state data sets, provides not only quarterly earnings, but quarterly hours of work. This allows computation of the hourly wage. Using established regression methods, the authors report that the increase in the minimum wage to $13 resulted in a 6.8-percent decline in low-wage employment in Seattle. It should come as no surprise that this result reinvigorated the argument that the minimum wage causes large declines in employment, and has been widely featured in the Washington Post (but, interestingly, not the New York Times).

The results are not as decisive as portrayed by Jardim et al., as there are several unresolved methodological issues. The first is that the estimated elasticity of employment (the percentage change in employment for a 1% change in the wage) is well outside the bounds of prior research. Jardim et al. report an elasticity of -3. In contrast, the work of [first name] Neumark and [first name] Wascher, the most prominent researchers arguing for a negative employment effect, finds an average elasticity of -1. Jardim et al.’s elasticity is particularly unexpected since, although Seattle’s $13 minimum wage is high for the United States, it is not unusually high relative to Seattle’s wage structure. Second, the study finds the increase in the minimum wage is associated with a 21-percent increase in employment and hours among workers earning at least $19 per hour. Given that high-wage workers employment should only be marginally affected by the increase, this suggests the study does not properly account for the employment effects of Seattle’s booming labor market. Finally, the study excluded the 38 percent of Washington employees who work for firms with multiple locations. These employees cannot be included because the U.I. data does not record whether they work in Seattle. These multi-location firms, which tend to be larger than single location firms, may respond differently to the minimum wage than single location firms. If there is a shift of employment from single- to multi-location firms in response to the minimum wage, the large magnitude of the elasticity may well result from measuring only part of the relevant labor force.

The literature on the minimum wage developed “falsification” tests that can be used to determine whether or not an estimated results from spurious correlations. These include such issues as estimated results that may be well outside the range that could be expected from a minimum wage increase, whether the effect is found among groups that should not have been affected by the minimum wage, and whether the effect of the minimum wage is found prior to its implementation.

Until the authors include these tests in their research, we cannot know if their results do in fact represent a serious challenge to the emerging consensus on the employment effects of increases in the minimum wage.


*I want to acknowledge the work of Michael Reich et al. and John Schmidt and Ben Zipperer for the analysis of “Minimum Wage Increases, Wages, and Low-Wage Employment: Evidence from Seattle.”


Special mention

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The crisis takes a much longer time coming than you think, and then it happens much faster than you would have thoughtRudi Dornbusch

Last week, a wide variety of U.S. media (including the Wall Street Journal and USA Today) marked what they considered to be the ten-year anniversary of the beginning of the global economic crisis—from which we still haven’t recovered.

The event in question, which occurred on 9 August 2007, was the announcement by international banking group BNP Paribas that, because their fund managers could not calculate a reliable net asset value of three mutual funds, they were suspending redemptions.

But, as I explain to my students, “Beware the appearance of precision!” For example, the more numbers after the decimal point (2.9, 2.93, 2.926, etc.), the more real and precise the number appears to be. But such a number is only ever an estimate, a best guess, about what is going on (whether it be the growth of output or the increase in new home sales).

The same holds for dates. It would be odd to choose a particular day ten years ago that, among all the possible causes and precipitating events, put the U.S. and world economies on the road to the Second Great Depression. That would be like saying World War I was caused on 28 June 1914, when Yugoslav nationalist Gavrilo Princip assassinated Archduke Franz Ferdinand of Austria. Or that the first Great Depression began on Black Thursday, 24 October 1929.


Given the centrality of housing sales, mortgages, and mortgage-backed securities in creating the fragility of the financial sector, we could just as easily choose July 2005 (when, as in the green line in the chart above, new one-family house sales peaked), January 2006 (when, as in the blue line, new privately owned housing units starts peaked), or February 2007 (when the Case-Shiller home price index, the red line, started its slide).

fredgraph (1)

Or, alternatively, we could choose the third quarter of 2006, when the U.S. corporate profit share (before taxes and without adjustments) reached its peak, at almost 12 percent of national income. After that, it began to fall, and the decisions of capitalists dragged the entire economy to the brink of disaster.

fredgraph (2)

Or the year 2005, when the profits of the financial and insurance sector were at their highest level—at $158.3 trillion—and then began to decline. Then, of course, it was bailed out after falling into negative territory in 2008.


Or, given the centrality of inequality in creating the conditions for the crash, we can go all the way back to 1980, when the share of income going to the top 1 percent was “only” 10.7 percent—since after that it started to rise, reaching an astounding 20.6 percent in 2006.

Those are all possible dates, some of course more precise than others.

What is important is each one of those indicators gives us a sense of how the normal workings of capitalism—in housing, finance and insurance, corporate profits, and the distribution of income—created, together and over time, the conditions for the most severe set of crises since the first Great Depression. And now, as a result of the crash and the nature of the recovery, all of them have been restored.

Thus creating the conditions for the next crash to occur, ten years after the last one.


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Special mention

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