Monday, March 20, 2017

Robots and Inequality: A Skeptic's Take

Paul Krugman presents "Robot Geometry" based on Ryan Avent's "Productivity Paradox". It's more-or-less the skill-biased technological change hypothesis, repackaged. Technology makes workers more productive, which reduces demand for workers, as their effective supply increases. Workers still need to work, with a bad safety net, so they end up moving to low-productivity sectors with lower wages. Meanwhile, the low wages in these sectors makes it inefficient to invest in new technology.

My question: Are Reagan-Thatcher countries the only ones with robots? My image, perhaps it is wrong, is that plenty of robots operate in Japan and Germany too, and both countries are roughly just as technologically advanced as the US. But Japan and Germany haven't seen the same increase in inequality as the US and other Anglo countries after 1980 (graphs below). What can explain the dramatic differences in inequality across countries? Fairly blunt changes in labor market institutions, that's what. This is documented in the Temin/Levy "Treaty of Detroit" paper and the oddly ignored series of papers by Piketty, Saez and coauthors which argues that changes in top marginal tax rates can largely explain the evolution of the Top 1% share of income across countries. (Actually, it goes back further -- people who work in Public Economics had "always" known that pre-tax income is sensitive to tax rates...) They also show that the story of inequality is really a story of incomes at the very top -- changes in other parts of the income distribution are far less dramatic. This evidence also is not suggestive of a story in which inequality is about the returns to skills, or computer usage, or the rise of trade with China.

With Lester Lusher, I've also waded into this debate (here and here). What we set out to do is show a variety of evidence all pointing to the conclusion that trade shocks have not caused a rise in inequality. First, we look at the two largest trade shocks in the US, the 1980s dollar bubble, and the late 1990s appreciation + rise of China shock. Perhaps surprisingly, neither hurt the wages of low-wage workers who worked in exposed sectors disproportionately. Sectors more exposed to the shocks also did not experience increases in inequality. We also found no association between capital upgrading by sectors, and inequality, or between TFP growth and inequality.  And then we looked at the cross-country evidence, and found that trade with China, trade deficits, trade levels, and changes in trade are all not even correlated with top income shares. As a last bit, we tested the Piketty, Saez, and Stantcheva results out-of-sample. Although we found that a slightly different functional form, and a dynamic model worked much better, we found that their results hold up out-of-sample. Interestingly, even though this was just a small part of our paper, referees protested that the result was not new. They apparently see no value in subjecting previously published work to additional testing, even if it is seminal work on a major policy topic that is also controversial enough that many top people (Krugman, Autor, Acemoglu, etc.) seem not to believe it. And this journal was second tier!

In any case, there is a long history of constructing mathematical models to show how international trade or skill-biased technological change can influence the wage distribution in theory. However, it's not clear to me this literature has been very successful empirically, in the end. It seems to me that any theory meant to apply to all countries will be a theory that doesn't apply to any country. And somehow it always seems that the contributors to this literature are not aware that there is already a perfectly good explanation for rising inequality that has explanatory power internationally (and out-of-sample).

Lastly, why are wages growing slowly? Well, let's not forget that the Fed has raised interest rates 3 times already since the Taper, despite below-target inflation and slow wage growth. The labor market has been bad since 2007 (or, in fact, since 2000 -- see my longer explanation here). Wages tend to grow slowly in bad labor markets, and tight money will keep them from growing quickly. There's no need here to draw parallelograms.


  1. Thank you for pointing this out. Germany has more robots/worker than the U.S. yet a much larger percentage of high-wage manufacturing jobs in the workforce. That said, we musn't compare apples to oranges -- recall that in Germany many laws protecting labor insure lower inequality. Viz., the dual board system for Germany corporations + codetermination, etc. Moreover, if robots are taking so many jobs in the U.S. why are U.S. productivity stats down so badly since 2000?

    1. I agree with you. The institutions are different between the US and Germany, which accounts for the difference in inequality. In addition, labor market institutions in the US are different from the pre-Reagan era, when top marginal tax rates were extremely high, the minimum wage bound, and unions were more powerful.

      I like your last comment "Moreover, if robots are taking so many jobs in the U.S. why are U.S. productivity stats down so badly since 2000?" Exactly. It's hard to see the impact of robots specifically in the productivity statistics. Manufacturing productivity growth has more-or-less been constant before and after the advent of industrial robots.

  2. I view this somewhat differently and am not sure of the direction of causality. It seems to me that:

    In order to be economically viable, mass-production techniques require mass markets—that is, markets with large numbers of people who have purchasing power. Otherwise, the mass quantities of goods and services that can be produced via mass-production techniques cannot be sold. The existence of mass markets within a society, in turn, depends crucially on the distribution of income within that society: The less concentrated the distribution of income, the greater the purchasing power out of income of large numbers of people, the larger the domestic mass market will be; the more concentrated the distribution of income, the smaller the purchasing power out of income of large numbers of people, the smaller the domestic mass market will be.

    This brings us to the crux of the problem endemic in the changes in the distribution of income that have taken place during the past thirty-five years. Namely, that the share of income that went to the top 1% of the income distribution in the 2000s was twice what it was in the 1960s and 1970s. Doubling the income share of the top 1% from approximately 8% in 1980 to 19% in 2012 means the share of the bottom 99% went from 92% to 81%. As a result, the bottom 99% of the income distribution—99 out of 100 families—had, on average, 12% less purchasing power from income relative to the output produced in 2012 than the bottom 99% had relative to the output produced in 1980, and as we go down the income scale the reduction in purchasing power from income becomes more dramatic. The World Top Incomes Database shows that the fall in income for the bottom 90% of the income distribution in the United States from 1980 to 2012 was 23%. This means that in 2012 the bottom 90% of the population—9 out of 10 families—had, on average, 23% less purchasing power from income relative to the output produced in 2012 than the bottom 90% had in 1980 relative to the output produced in 1980....

    The point is, given the state of mass-production technology within our society, the domestic markets necessary to support full employment could not have been maintained without an increase in debt as the income transfer to the top of the income distribution examined in Chapter 1 took place and, thus, diluted the purchasing power out of income of the rest of the population relative to the output produced.[17] This is especially so as the situation was made worse as imports of mass produced goods increased relative to exports and productivity increased. Since employment, output, and productivity all increased during this period, it should not be surprising to find that debt increased substantially as well....

    It seems to me that these factors interact to determine the way in which the concentration of income affects the way in which technology is adopted. I develop this argument more fully here:

    And what I think it means here: