Education Levels, Not Income, Led to Trump

With it being Trump’s inauguration today, I thought I’d highlight an article from November by Nate Silver. Where did Clinton do well and where did she falter?:

I took a list of all 981 U.S. counties with 50,000 or more people and sorted it by the share of the population that had completed at least a four-year college degree. Hillary Clinton improved on President Obama’s 2012 performance in 48 of the country’s 50 most-well-educated counties. And on average, she improved on Obama’s margin of victory in these countries by almost 9 percentage points, even though Obama had done pretty well in them to begin with.

Yet, when he looks at “50 counties (minimum population of 50,000) where the smallest share of the population has bachelor’s degrees,” the tune changes considerably:

These results are every bit as striking: Clinton lost ground relative to Obama in 47 of the 50 counties — she did an average of 11 percentage points worse, in fact. These are really the places that won Donald Trump the presidency, especially given that a fair number of them are in swing states such as Ohio and North Carolina. He improved on Mitt Romney’s margin by more than 30 points (!) in Ashtabula County, Ohio, for example, an industrial county along Lake Erie that hadn’t voted Republican since 1984.

Silver continues by showing just how important education was in determining Trump/Clinton support:

  • High-education, medium-income white counties shifted to Clinton.
  • High-income, medium-education white counties shifted to Trump.
  • Highly educated majority-minority counties shifted toward Clinton.
  • Low-education majority-minority counties shifted toward Trump.

Silver concludes,

In short, it appears as though educational levels are the critical factor in predicting shifts in the vote between 2012 and 2016. You can come to that conclusion with a relatively simple analysis, like the one I’ve conducted above, or by using fancier methods. In a regression analysis at the county level, for instance, lower-income counties were no more likely to shift to Trump once you control for education levels. And although there’s more work to be done, these conclusions also appear to hold if you examine the data at a more granular level, like by precinct or among individual voters in panel surveys.

So it wasn’t necessarily the economically destitute that voted for Trump. A 2016 Gallup study found

that Americans who live in places where employment in manufacturing has declined since 1990 are not more favorable to Trump. Rothwell [the author] did not find a relationship when he focused only on white respondents, either, or even specifically on white Republicans. Trump’s supporters have many other traits in common with the factory workers whose economic prospects have been negatively affected by automation and global trade. They tend to be less educated men who hold blue-collar occupations. Yet those two broad trends in factory work do not account for Trump’s appeal, Rothwell’s analysis suggests. In fact, among those who share other traits, those who live in districts with more manufacturing are less favorably disposed toward Trump.

However, Silver offers a few “competing hypotheses” to the straightforward interpretation above:

  • Education levels may be a proxy for cultural hegemony. Academia, the news media and the arts and entertainment sectors are increasingly dominated by people with a liberal, multicultural worldview, and jobs in these sectors also almost always require college degrees. Trump’s campaign may have represented a backlash against these cultural elites.
  • Educational attainment may be a better indicator of long-term economic well-being than household incomes. Unionized jobs in the auto industry often pay reasonably well even if they don’t require college degrees, for instance, but they’re also potentially at risk of being shipped overseas or automated.
  • Education levels probably have some relationship with racial resentment, although the causality isn’t clear. The act of having attended college itself may be important, insofar as colleges and universities are often more diverse places than students’ hometowns. There’s more research to be done on how exposure to racial minorities affected white voters. For instance, did white voters who live in counties with large Hispanic populations shift toward Clinton or toward Trump?
  • Education levels have strong relationships with media-consumption habits, which may have been instrumental in deciding people’s votes, especially given the overall decline in trust in the news media.
  • Trump’s approach to the campaign — relying on emotional appeals while glossing over policy details — may have resonated more among people with lower education levels as compared with Clinton’s wonkier and more cerebral approach.

So with that, enjoy Inauguration Day.

2016: Best Year Ever

Image result for 2016 burning dumpster

Here’s a bit of optimism after the train wreck that was 2016:

By conventional wisdom, 2016 has been a horrible year. Only someone living in a cave could have missed the flood of disheartening headlines. However, if 2016 continues the global trends of previous years, it may turn out to have been one of the best years for humanity as a whole.

Those of us who live in the world of poverty research and rigorous measurement have watched many global indicators improve consistently for the past few decades. Between 1990 and 2013 (the last year for which there is good data), the number of people living in extreme poverty dropped by more than half, from 1.85 billion to 770 million. As the University of Oxford’s Max Roser recently put it, the top headline every day for the past two decades should have been: “Number of people in extreme poverty fell by 130,000 since yesterday.” At the same time, child mortality has dropped by nearly half, while literacy, vaccinations and the number of people living in democracy have all increased.

The authors point to four things that can make 2017 even better for the poor and destitute:

  1. “First, give the poor cash. Studies in Kenya and elsewhere show that the simplest way to help is also quite effective. We also know that if we give cash, the poor won’t smoke or drink it away. In fact, a recent look at 19 studies across three continents shows that when the poor are given money, they are less likely to spend it on “temptation goods” such as alcohol and tobacco. More and more research shows that when the poor come into a windfall, they spend it on productive things — sending their children to school, fixing the roof that’s letting in the harsh weather or investing in a business.”
  2. “Second, innovative health-care delivery can dramatically improve outcomes…The nongovernmental organizations Living Goods and BRAC Uganda have been training women in Uganda to make a living by going door-to-door selling over-the-counter medications and health products. They function as franchisees in an “Avon lady”-style business. But these small-business owners also perform basic health checks for children to look for symptoms that warrant getting the child to a clinic. One randomized evaluation released this year concluded that taking this health care to people’s homes reduced child mortality (for those younger than 5) by an astounding 27 percent and infant mortality (less than a year old) by 33 percent.”
  3. “Third, access to mobile money may lift people out of poverty in large numbers…In Kenya, the M-Pesa mobile money system, introduced in 2007, allows anybody with a mobile phone to transfer money through a text message. Research from this year shows that as M-Pesa became more available in a local area, households became less poor — particularly households run by women. The study estimates that 185,000 women changed professions from subsistence agriculture to business and retail and that 194,000 households were lifted out of extreme poverty.”
  4. “Finally, mobile phone technologies are leapfrogging the reach of traditional telecom infrastructure, and text message reminders are proving to be effective at helping people follow through on things they want to do. One study found that they helped the poor save money. Another in Ghana aimed at combating drug resistance found that such reminders helped people to finish all of their antimalarial drugs. Researchers in Ghana also found that text message quizzes improved girls’ understanding of reproductive health, resulting in fewer reported pregnancies. In Kenya, another interactive text message system offering support for teachers helped reduce student dropouts by 50 percent.”

2017 is looking up.

 

Nation Building From the Ground Up

I’ve written on the social science of military intervention before, noting that they rarely achieve the democratic goals of those intervening. A new study distinguishes between top-down and bottom-up approaches to foreign intervention: “Top-down approaches to foreign intervention emphasise gaining citizen compliance by making it costly for citizens to oppose the state, whereas bottom-up approaches aim to increase the benefits of supporting the state by providing public goods, economic aid, and political opportunities.” Drawing on evidence from the Vietnam War, the researchers find (perhaps unsurprisingly),

Image result for vietnam warEstimates document that the bombing of South Vietnamese population centres backfired, leading more Vietnamese to participate in Viet Cong (VC) military and political activities and increasing VC attacks on troops and civilians. The initial deterioration in security entered the next quarter’s security score, increasing the probability of future bombing and hence leading to sustained increases in VC activity. Moreover, while US intervention aimed to build a strong state and engaged civic society that would provide a bulwark against communism after US withdrawal, bombing instead reduced the probability that the local government collected taxes, decreased access to primary schools, and reduced participation in civic organisations. To the extent that spillover effects of bombing on other locations exist, the impacts tend to go in the same direction as the effects on the locations that were bombed.

Interviews of VC prisoners and defectors provide a potential explanation for why bombing increased VC activity. Grievances against the government – particularly in cases where a civilian family member was killed in US or South Vietnamese attacks – were strong motivators for joining the VC (Denton 1968). Civilian casualties and property damage are plausibly particularly harmful to the trust between government and citizens that underlies an effective social contract.

In order to compare the two strategies, the authors explored

the boundary between Military Region I – commanded by the US Marine Corps (USMC) – and Military Region II – commanded by the US Army. The Marines emphasised providing security by embedding soldiers in communities and winning hearts and minds through development programmes (USMC 2009). Their approach was motivated by the view that “in small wars the goal is to gain decisive results with the least application of force… the end aim is the social, economic, and political development of the people” (USMC 1940). In contrast, the Army relied on overwhelming firepower deployed through search and destroy raids (Krepinevich 1986, Long 2016). Evidence points to this difference in counterinsurgency strategies as a central distinction between the Army and Marines.

Hamlets just to the USMC side of the boundary were less likely to have a VC presence than those just to the Army side, and public opinion data document that citizens in the USMC region reported less anti-Americanism and more positive attitudes towards all levels of South Vietnamese government than did citizens in the Army region. Pre-period VC attacks, pre-characteristics, and soldier characteristics – including Armed Forces Qualifying Test scores – are all relatively balanced across the boundary, suggesting that the effects are driven by differences in military strategy and not by omitted factors.

Civility, trust, and community work better than violence. Fancy that.

AEA Meeting: Minimum Wage Research

The New York Times has a recent article discussing new research on the minimum wage presented at the annual meeting of the American Economic Association:

Image result for minimum wageJohn Horton of New York University conducted an experiment on an online platform where employers post discrete jobs — including customer service support, data entry, and graphic design — and workers submit a proposed hourly wage for completing them.

…At first glance, the findings were consistent with the growing body of work on the minimum wage: While the workers saw their wages rise, there was little decline in hiring. But other results suggested that the minimum wage was having large effects. Most important, the hours a given worker spent on a given job fell substantially for jobs that typically pay a low wage — say, answering customer emails.

Mr. Horton concluded that when forced to pay more in wages, many employers were hiring more productive workers, so that the overall amount they spent on each job changed far less than the minimum-wage increase would have suggested…When the minimum wage increased, employers tended to hire workers who had earned higher wages in the past, suggesting that they were looking for a more productive work force. 

If the pattern Mr. Horton identified were to apply across the economy, it would raise questions about whether increasing the minimum wage is as helpful to those near the bottom of the income spectrum as some proponents assume. The higher minimum wage could cost low-skilled workers their jobs, as employers rush to replace them with somewhat more skilled workers.

Another study found that when the minimum wage increases, employers may be put out of business. After identifying the ratings of thousands of restaurants in the San Francisco area, the researchers

found that many poorly rated restaurants tend to go out of business after a minimum-wage increase takes effect. By contrast, highly rated restaurants appear to be largely unaffected by minimum-wage increases, and over all, there is no substantial rise in restaurant closings after a minimum-wage increase. 

The results are broadly consistent with a 2013 study…showing that a sizable minimum-wage increase in New Jersey resulted in many lost jobs as numerous businesses closed, but an almost offsetting number of new jobs as other businesses opened, which the authors argue were more productive. 

Just add this to the growing evidence of adverse effects of the minimum wage.

Why Therapy Works: Interview with Louis Cozolino

This is part of the DR Book Collection.

Image result for why therapy worksI don’t think I’ve ever mentioned this before on here, but, as some of  you may have guessed, I go to therapy. I haven’t as of late for various reasons, but for a solid two years I went pretty much every other week. My interest in shame and vulnerability has been largely due to my personal work in therapy. This is why as soon as I heard of psychologist Louis Cozolino’s book Why Therapy Works: Using Our Minds to Change Our Brains, I immediately picked it up. Granted, like most of my books, it sat dormant for quite a while until I finally finished it up toward the end of last year.

Cozolino walks the reader through the findings of cognitive neuroscience, discussing the “fast” (i.e., “primitive systems, which are nonverbal and inaccessible to conscious reflection, [that] are referred to as implicit memory, the unconscious, or somatic memory”, pg. 5) and “slow” (i.e., “conscious awareness…[which] eventually gave rise to narratives, imagination, and abstract thought”, pg. 5) systems of the brain. Because of this “fast” system, we often have negative internalizations that we’re not even consciously aware of. This is what Cozolino calls “core shame”:

Core shame needs to be differentiated from appropriate shame and guilt that emerge later in childhood. Appropriate shame is an adaptation to social behavior required by the group. Core shame, on the other hand, is an instinctual judgment about the self, and it results in a sense of worthlessness, a fear of being found out, and a desperate striving for perfection. In essence, core shame is tied to our primitive instinct to be a worthy part of the tribe; it is a failure to internalize a deep sense of bonded belonging. As a result, people with core shame feel damaged, unlovable, and abandoned. Thus, core shame becomes a central factor in the perpetuation of insecure attachment and social status schema (pg. 10).

The brain, according to Cozolino, “is a social organ” and “we can leverage the power of human relationships to regulate anxiety and stimulate learning” (pg. xxii). This makes the relational nature of therapy all the more important and effective:

The reasons for our struggles often remain buried in networks of implicit memory, inaccessible to conscious reflection. Psychotherapy guides us in a safe exploration of our early experiences and helps us create a narrative that associates these early experiences with the ways in which our brains and minds distort our current lives. In the process, our symptoms come to be understood as forms of implicit memory instead of insanity, character pathology, or plain stupidity. This process can open the door to greater compassion for oneself, openness to others, and the possibility for healing (pg.9).

The book is comprehensive and excellent for both laypersons and scholars. You can see short interview clips with Cozolino below.

Is Entrepreneurship Predetermined?

How much is entrepreneurship predetermined by family background? According to a new study,

Image result for parents kids gif
Parent Role-Modelling

recent papers have collectively suggested that entrepreneurship might be more predetermined than previously thought – entrepreneurship education has been proven to be effective in primary school (Huber et al 2014) and, to a lesser extent, in secondary school (Elert et al 2015), but not at all when individuals are older, that is, students (Oosterbeek et al 2010) or adults (Fairlie et al 2015). Moreover, strong intergenerational associations in entrepreneurship have attracted considerable attention. While part of this relationship has been shown to be genetic (Nicolaou et al 2008), parental role-modelling appears to be the main driver of the intergenerational association in entrepreneurship (Lindquist et al. 2015). Additionally, exposure to a dense entrepreneurial environment during formative years also increases the likelihood of entry into entrepreneurship (Guiso et al. 2015).

So the policy-relevant questions arise: To what extent is entrepreneurship predetermined? Have we spent (public) funds wisely by implementing policy measures and education aimed at changing the behaviour of adult people?

In a recent paper, we assess the predetermination of entrepreneurship outcomes by calculating and analysing sibling correlations (Lindquist et al 2016). We argue that sibling correlations are more complete and precise measures of predetermination, including the importance of genes, family background, and neighbourhood effects as determinants of entrepreneurship. Sibling correlations have been used before to study outcomes other than entrepreneurship and provide much broader measures of the importance of family background and neighbourhood effects than intergenerational associations (Solon 1999). Their interpretation is also straightforward – the higher the sibling correlation, the larger the importance of family background.

Their results?:

  • 25% of the variance in individuals’ decisions to become self-employed is explained by family background and community influences;
  • For incorporation, this is close to 35%;
  • These percentages are slightly higher when we consider measures of successful entrepreneurship such as above median years of self-employment and incorporation;
  • Brother correlations are always larger than sister correlations;
  • The largest correlation is for males with above median years of incorporation, which is close to 50%;
  • Mixed sibling correlations are consistently smaller than same-sex correlations.
  • Parental entrepreneurship status is quite important;
  • Parental education and income matter much less; and,
  • Family structure and immigrant status do not matter.
  • Parental self-employment is a prime explanatory force in individual self-employment, but not incorporation; and
  • Parental incorporation explains individual incorporation best, but not self-employment.
  • Between 56–78% of the sibling correlations in self-employment; and
  • Between 38–46% of the sibling correlations in incorporation.

The researchers conclude “that parental entrepreneurship and genes are the two most important factors generating sibling similarities in entrepreneurship.” Policy wise, the authors explain that “children appear to be able to learn about entrepreneurship through their family and community environment, which implies that it may be possible to teach entrepreneurship to young people.”

Check it out.

GMU Interview with Joe Henrich

Joseph Henrich (left), Tyler Cowen (right)

Anthropologist and cultural psychologist Joseph Henrich is an academic whose work I’ve been following over the last couple years. His work has been highlighted multiple times here at Difficult Run. He is a co-author of some of my favorite studies in the last decade or so. And his latest book–The Secret of Our Success: How Culture Is Driving Human Evolution, Domesticating Our Species, and Making Us Smarter–looks absolutely amazing (it’s waiting patiently for me on my Kindle).

He recently sat down with economist Tyler Cowen for a segment of Conversations with Tyler at GMU’s Mercatus Center. The interview is fascinating as they discuss Henrich’s work on cultural evolution and its implications for both today and the future. What perhaps excited me the most was Henrich’s discussion of his work-in-progress on marriage norms and the development of Western individualism:

In my latest project I’m really looking at the kind of spread of the Western church into Europe and how it transformed the social structure in ways that I think led to individualism, it led to a different kind of cultural psychology that would eventually pave the way for secular institutions and economic growth. The church is the first mover in that account…When the church first began to spread its marriage-and-family program where it would dissolve all these complex kinship groups, it altered marriage. So it ended polygyny, it ended cousin marriage, which…forced people to marry further away, which would build contacts between larger groups. That actually starts in 600 in Kent, Anglo-Saxon Kent. Missionaries then spread out into Holland and northern France and places like that. At least in terms of timing, the marriage-and-family program gets its start in southern England.

This project is in its early stages (according to the email Henrich sent me), but it’s something I’m greatly anticipating. The entire interview is worth watching/listening to. Cowen provides both insightful feedback and even pushback, making the discussion a productive one. Check it out.

Geography and Unemployment

Does geography contribute to unemployment? “In a paper published in 1965,” reports The Economist,

John Kain, an economist at Harvard University, proposed what came to be known as the “spatial-mismatch hypothesis”. Kain had noticed that while the unemployment rate in America as a whole was below 5%, it was 40% in many black, inner-city communities. He suggested that high and persistent urban joblessness was due to a movement of jobs away from the inner city, coupled with the inability of those living there to move closer to the places where jobs had gone, due to racial discrimination in housing. Employers might also discriminate against those that came from “bad” neighbourhoods. As a result, finding work was tough for many inner-city types, especially if public transport was poor and they did not own a car.

Is there any data to back up this theory?

A new paper, published by the National Bureau of Economic Research…looks at the job searches of nearly 250,000 poor Americans living in nine cities in the Midwest. These places contain pockets of penury: unemployment in inner Chicago, for instance, is twice the average for the remainder of the city. Even more impressive than the size of the sample is the richness of the data. They are longitudinal, not cross-sectional: the authors have repeated observations over a number of years (in this case, six). That helps them to separate cause and effect. Most importantly, the paper looks only at workers who lost their jobs during “mass lay-offs”, in which at least 30% of a company’s workforce was let go. That means the sample is less likely to include people who may live in a certain area, and be looking for work, for reasons other than plain bad luck.

For each worker the authors build an index of accessibility, which measures how far a jobseeker is from the available jobs, adjusted for how many other people are likely to be competing for them. The authors use rush-hour travel times to estimate how long a jobseeker would need to get to a particular job.

If a spatial mismatch exists, then accessibility should influence how long it takes to find a job. That is indeed what the authors find: jobs are often located where poorer people cannot afford to live. Those at the 25th percentile of the authors’ index take 7% longer to find a job that replaces at least 90% of their previous earnings than those at the 75th percentile. Those who commuted a long way to their old job find a new one faster, possibly because they are used to a long trek.

Governments could seek to “help workers either to move to areas with lots of jobs, or at least to commute to them. That would involve scrapping zoning laws that discourage cheaper housing, and improving public transport. The typical American city dweller can reach just 30% of jobs in their city within 90 minutes on public transport. That is a recipe for unemployment.”

The Benefits of Globalization: Trade & Migration

We sharply disagree with this dismal view of globalisation.

Image result for free tradeSo write three scholars drawing on their latest research on globalization. “Our recent research,” they continue,

indicates that the gains from trade and migration are tremendous and that the world stands to benefit greatly from their further liberalisation (Desmet et al. 2016). The problem with virtually all quantitative and empirical evaluations of trade and migration is their static nature. They completely ignore the dynamic gains from globalisation. As we will later discuss, these dynamic gains quantitatively dwarf any short-run costs. 

After providing the theory of growth behind trade and migration, the researchers present their jaw-dropping conclusions:

Completely lifting all migration restrictions would increase real world output by 126% in present discounted value terms. Since such a policy may be unrealistic, consider instead a reform that liberalises migration so that 10% of the world population moves at impact. This would yield a present discounted value increase in real world output of 14%. Such a reform would cause some extra congestion in Europe and the US, implying that average welfare would increase by 9%, a smaller but still impressive figure. It is hard to think about any other policy that could readily be applied at the world level for which estimated benefits are as large. Migration is uniquely powerful in generating positive effects. In economic terms, having an open-door policy is a no brainer, not because of some abstract theoretical arguments, but because the measurement of the relevant forces tells us so.

Turning back the clock on trade would have equally dire consequences. Increasing trade costs by 40% would lower real world output by 30% in present discounted value terms. Although globalisation might create losers in the short run, allowing the free flow of goods and people across regions and countries is still one of the best ways we know to ensure our long-run wealth and well-being.

These numbers are astronomical. The potential good that can come from liberalized trade and migration makes the rising nationalism all the more disheartening.

Hans Rosling: Combating Ignorance

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Hans Rosling

I’ve mentioned Swedish statistician Hans Rosling in a couple posts here at Difficult Run. A recent article in Nature takes a look at the influence Rosling is having throughout the world as a public intellectual. His graphics-based presentations of world poverty and health have helped audiences visualize the major changes that have taken place over the last couple centuries. Cognitive scientist “[Steven] Pinker admires the animations that Rosling uses. One, which depicts countries as bubbles that migrate over time according to wealth, life span or family size, allows viewers to grasp multiple variables simultaneously. “It’s a stroke of genius,” Pinker says. “He gets our puny human brain to appreciate five dimensions.”” Rosling’s approach was undoubtedly influenced by his feeling that

neither his students nor his colleagues grasped extreme poverty. They pictured the poor as almost everyone in the ‘developing world’: an arbitrarily defined territory that includes nations as economically diverse as Sierra Leone, Argentina, China and Afghanistan. They thought it was all large family sizes and low life expectancies: only the poorest and most conflict-ridden countries served as their reference point. “They just make it about us and them; the West and the rest,” Rosling says. How could anyone hope to solve problems if they didn’t understand the different challenges faced, for example, by Congolese subsistence farmers far from paved roads and Brazilian street vendors in urban favelas? “Scientists want to do good, but the problem is that they don’t understand the world,” Rosling says.

The whole article is worth reading. While some of Rosling’s academic colleagues may not appreciate his work, I certainly do. Combating ignorance about the state of the world is a worthwhile endeavor.

You can test your knowledge of the world with this quiz.