Who are the workers forced to bear the costs of the increase in workplace robots?
According to Acemoglu and Restrepo, men take about twice as big a hit in terms of lost jobs as women do. Although both sexes suffer wage losses when robots replace people, the size of the drop in employment for women was about half that of men.
In terms of occupational sectors, the authors found that
the effects of robots concentrate in automobile manufacturing, electronics, metal products, chemicals, pharmaceuticals, plastic, food, glass and ceramics.
Workers without college degrees experience substantially larger wage and employment losses when exposed to competition from robots, while the same competition results in
a small and marginally significant negative effect on employment for workers with college, and no effect on employment and wages for workers with post-college degrees.
In political terms, the workers who experience the highest costs from industrial automation fit the crucial Trump voter demographic: white non-college voters, disproportionately male, whose support for the Republican nominee surged from 2012 to 2016 — as shown in the accompanying graphic, which is based on data from the Pew Research Center.
The graphic shows a major transformation of the Republican presidential electorate. Among whites with college degrees, support for Trump fell by 11 percentage points compared with support for Mitt Romney; among whites without degrees, Trump’s support rose by 12 points when compared with Romney’s.
The increase in workplace robots was not alone in driving voters to the right. Communities where industries lost ground to imports from China followed a similar pattern.
In a September 2017 paper, “Importing Political Polarization? The Electoral Consequences of Rising Trade Exposure,” David Autor, who is also an economist at M.I.T., and three of his colleagues, dug further into the demographics of those suffering the economic costs of trade with China.
Autor and his co-authors found that
Trade exposure catalyzed strong movements towards conservative Republicans between 2002 and 2010 in counties with majority non-Hispanic white populations.
The gains made by hard-right Republicans came at the expense of moderate Republican and Democratic incumbents.
Even more significant, Autor determined that though generally speaking trade shocks did not “favor conservative politicians,” shocks “that disproportionately affect white males” did.
The authors provide more detail, explaining that the
rightward shift is driven by trade shocks to industries that have traditionally employed white men in relatively large numbers, and is largely unrelated to shocks to other industries.
Autor and his co-authors cite research showing that
voters choose to supply fewer public goods when a significant fraction of tax revenues collected from one ethnic group is used to provide public goods shared with other ethnic groups
voters in an in-group object to their tax contributions being used to support individuals in out-groups.
That translates to: white voters, especially white men, oppose paying taxes for programs that primarily provide services to others. In practice, the authors suggest, trade shocks
catalyze anti-redistributionist sentiment (seen in the election of conservative Republicans) in majority white non-Hispanic locations where taxpayers may perceive themselves as transfer-payment donors.
This white male effect was critical to the link connecting, as Autor and his co-authors write,
economic adversity to in-group/out-group identification, as motivated by group-based resource competition or opportunistic use of political extremism.
Their analysis resonates, they suggest,
with the themes of recent literature on the political economy of right-wing populism, in which economic shocks to dominant population groups engender a political response that sharpens group identities and enhances support for conservative politicians. This pattern is evident in our finding that the impact of trade shocks on political polarization appears largely attributable to increases in foreign competition facing manufacturing industries that are intensive in the employment of non-Hispanic white males.
Acemoglu, Autor and their colleagues provide a synthesis between the economic and the sociocultural explanations of the rise of the populist right. In doing so, they provide a corrective to the recent tendency in segments of the liberal media to downplay economic factors and to focus instead on racial resentment and cultural dislocation as the primary forces motivating Trump voters.
I myself have written that
Republican voters have a strong sense of white identity, they harbor high levels of racial resentment and they sometimes exhibit authoritarian leanings.
The point here is that the two generalized explanatory realms — the one focused on race and the other on economic shock — overlap. It is not either/or but both that gave us President Trump.
Still, explanations tend to become monocausal.
Take, for example, the Dec. 15, 2017 headline at the Vox website: “The past year of research has made it very clear: Trump won because of racial resentment.” According to German Lopez, the article’s author, “employment and income were not significantly related to that sense of white vulnerability.” What was? “Racial resentment.”
A May 9, 2017 story in The Atlantic asserted that
that fear of societal change, not economic pressure, motivated votes for the president among non-salaried workers without college degrees.
Those stories were by no means alone. Salon: “Liberals were right: Racism played a larger role in Trump’s win than income and authoritarianism”; The Nation: “Economic Anxiety Didn’t Make People Vote Trump, Racism Did.”
The debate over the role of economic hardship among whites in building support for Trump began while the campaign was in full swing.
Nate Silver, founder and editor of the FiveThirtyEight website, wrote “The Mythology of Trump’s ‘Working Class’ Support” in the midst of the primary fight for the Republican nomination.
“Compared with most Americans, Trump’s voters are better off. The median household income of a Trump voter so far in the primaries is about $72,000,” Silver pointed out, “well above the national median household income of about $56,000.”
Silver’s argument is accurate insofar as it goes, but it does not go far enough.
In the primaries, Trump’s voters were more affluent than the general electorate. But among Republican primary voters, the core of Trump’s support was among those with the lowest level of education and, in most cases, the lowest income levels.
Take a look at the exit polls from the March 1 Virginia primary. Trump beat his closest competitor, Senator Marco Rubio, among those without college degrees, 43-25, while Rubio beat Trump among those with degrees, 37-27. Trump beat Rubio 39-25 among voters making less than $100,000 but Rubio beat Trump 40-27 among those making more than $100,000. The same pattern was repeated over and over again in primaries across the country.
Trump’s strongest support in the primaries and in the general election came disproportionately from the least well educated whites — those who, as Acemoglu and Autor argue, are most vulnerable to the economic dislocation resulting from automation, the rise of a robot work force, global trade and outsourcing.
In an email, Autor describes how the two explanatory models dovetail. He starts with a question:
Do you think non-college, non-urban whites would feel so dislocated if their job prospects were strong and their wages rising?
He then goes on to point out that
all of these observations — authoritarianism, racism, cultural dislocation — have relevance. The only claim that’s irrelevant because it’s already been disproved is that economic factors were unimportant to Trump’s victory.
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