Society

Does Economic Insecurity Lead to Populism?

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From my BYU Studies Quarterly article:

A particularly interesting aspect of public attitudes toward immigration is that of political ignorance. Multiple studies have shown that political ignorance is rampant among average voters, and this holds true when it comes to immigration policy. As legal scholar Ilya Somin explains, “Immigration restriction . . . is one that has long-standing associations with political ignorance. In both the United States and Europe,survey data suggest that it is strongly correlated with overestimation of the proportion of immigrants in the population, lack of sophistication in making judgments about the economic costs and benefits of immigration, and general xenophobic attitudes toward foreigners. By contrast, studies show that there is little correlation between opposition to immigration and exposure to labor market competition from recent immigrants.” One pair of economists found that those voting to leave the European Union in the Brexit referendum, who were motivated largely by a desire to restrict immigration, “were overwhelmingly more likely to live in areas with very low levels of migration.” Similarly, voters who supported Donald Trump during the US election were more likely to oppose liberalizing immigration laws (even compared to other Republicans), but least likely to live in racially diverse neighborhoods. In short, both political ignorance and lack of interaction with foreigners tend to inflame anti-immigration sentiments. These sentiments are what George Mason University economist Bryan Caplan refers to as antiforeign bias: “a tendency to underestimate the economic benefits of interaction with foreigners.” In fact, economists take nearly the opposite view from the general public on immigration (pgs. 80-82).
In short, ignorance and fear of the unknown or “the other” (which ends up manifesting as racial resentment) lead to anti-immigration sentiments. Many have been quick to point out that economic anxieties did not play a significant role in the rise of Trump. Cultural values, for example, played a far more significant role. Evidence from Belgium also suggests that declinism–a negative view of the state and evolution of society–is far more important in predicting populist support than economic insecurities. Nonetheless, there is some evidence that economic downturns and uncertainty do lead to a rise in populism, particularly in Europe.[ref]Check out Rudiger Dornbusch and Sebastian Edwards’ “The Macroeconomics of Populism.”[/ref] Increases in unemployment following the Great Recession eroded trust in mainstream political parties in Europe and led to a rise in support for populist parties.  Harvard’s Dani Rodrik has made a case that economic globalization helped create a populist political backlash. A 2016 study looked at the political results of financial crises from 1870 to 2014. The authors conclude,
The evidence we uncover shows that financial crises put a strain on modern democracies. The typical political reaction is as follows: votes for far-right parties increase strongly, government majorities shrink, the fractionalization of parliaments rises and the overall number of parties represented in parliament jumps. These developments likely hinder crisis resolution and contribute to political gridlock. The resulting policy uncertainty may contribute to the much debated slow economic recoveries from financial crises. Financial crises are politically disruptive, even when compared to other economic crises. Indeed, we find no (or only slight) political effects of normal recessions and different responses in severe crises not involving a financial crash. In the latter, right wing votes do not increase as strongly and people rally behind the government. In the light of modern history, political radicalization, declining government majorities and increasing street protests appear to be the hallmark of financial crises. As a consequence, regulators and central bankers carry a big responsibility for political stability when overseeing financial markets. Preventing financial crises also means reducing the probability of a political disaster (pg. 245).
The same authors conducted a short follow-up study, which found
that financial crises of the past 30 years have been a catalyst of rightwing populist politics. Many of the now-prominent right-wing populist parties in Europe, such as the Lega Nord in Italy, the Alternative for Germany, the Norwegian Progress Party or the Finn’s Party are “children of financial crises”, having made their breakthrough in national politics in the years following a financial crash. We also find that the 2008 crisis triggered a wave of governments in which right-wing populists gained power, often as a coalition partner. As discussed, the crisis is just one of many potential factors explaining the recent successes of right-wing populism in Europe and beyond. Other drivers such as “cultural backlash”, the impact of globalization, rising inequality, and the refugee crisis of 2015 surely played a critical role too. However, “the rise of the right” in Europe since 2008 cannot be fully understood without considering the impact of the 2008 and 2011/2012 financial crises…A first potential explanation is that financial crises are perceived as inexcusable events that result from a failure of policies and regulation, rather than from an external shock. This leads to distrust in government and mainstream politics. Secondly, financial crises typically trigger creditor-debtor conflicts (Mian et al. 2014) and a rise in income and wealth inequality (Atkinson and Morelli 2010, 2011) to levels not observed in normal recessions. Thirdly, we know that financial crashes often involve large-scale bank bailouts and these are highly controversial and unpopular (e.g., Broz 2005). Such bail-out initiatives give traction to extremist ideas at the political fringe. In this environment of distrust, uncertainty and dissatisfaction, right-wing populists have learned to gain votes by offering seemingly simple solutions to complex problems, and by attributing blame to minorities or foreigners (pg. 8).
These findings fit with Martin Wolf’s observations in the Financial Times, which lay populism at the feet of “the financial crisis and consequent economic shocks. These not only had huge costs. They also damaged confidence in — and so the legitimacy of — financial and policymaking elites. These emperors turned out to be naked.” Using “unemployment, fiscal austerity, real incomes per head and private sector credit” as “indicators of post-crisis developments,” Wolf determines, “The four most adversely affected of these economies in the long term were (in order) Italy, Spain, the UK and US. Post-crisis, the most adversely affected were Spain, the US, Italy and the UK. Germany was the least affected by the crisis, with Canada and Japan close to it. It is not surprising, then, that Canada, Germany and Japan have been largely immune to the post-crisis surge in populism, while the US, UK, Italy and Spain have been less so, though the latter two have contained it relatively successfully.”
A more recent study supports these insights, “examin[ing] the role of the 2007–9 global financial crisis and its metastasis in Europe on voting and political beliefs in 220 subnational regions of 26 European countries.” It finds
a strong correlation between rising regional unemployment and voting for non-mainstream and especially populist parties. A one percentage point increase in unemployment is associated with a one percentage point increase in the populist vote. The association is especially strong in the south, where voters turn mostly to radical-left parties. In the north increases in regional unemployment are correlated with a rise in far-right party vote. This pattern is also present in eastern Europe, where people are moving towards xenophobic, anti-European parties. These associations do not necessarily imply causality. To advance on causality we associate voting patterns to the component of changes in unemployment stemming from the pre-crisis share of construction (which is strongly related to falling unemployment pre-2007 and rising unemployment post-2008). This approach also yields a strong correlation between the recent rise of the populist vote and industrial specialization–driven unemployment. We then examine the role of the crisis on the Brexit vote across the UK’s 379 electoral districts. In line with the European-wide results, [the data] show that the increases in regional unemployment before the referendum (2007–15) are strong predictors of the Brexit vote, while the level of unemployment is not much related to Brexit. We then study the evolution of trust, political beliefs and attitudes before and after the 2007–10 crisis and examine whether swings in unemployment are related to changing ideology. We use individual-level data on Europeans’ beliefs and attitudes from the European Social Survey that covers the period 2000–2014. [The data] show that increases in regional unemployment have resulted in a deterioration of trust towards national and European political institutions.
All of this suggests what Wolf stated: “Economic and cultural phenomena are interrelated.”

The Dying Art of Disagreement, or how to disagree well.

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Excellent NYTimes op-ed by Bret Stephens worth the full read, but here are some key passages.

To say the words, “I agree” — whether it’s agreeing to join an organization, or submit to a political authority, or subscribe to a religious faith — may be the basis of every community.

But to say, I disagree; I refuse; you’re wrong; etiam si omnes — ego non — these are the words that define our individuality, give us our freedom, enjoin our tolerance, enlarge our perspectives, seize our attention, energize our progress, make our democracies real, and give hope and courage to oppressed people everywhere.

What a lovely way to think of it.

Socrates quarrels with Homer. Aristotle quarrels with Plato. Locke quarrels with Hobbes and Rousseau quarrels with them both. Nietzsche quarrels with everyone. Wittgenstein quarrels with himself.

These quarrels are never personal. Nor are they particularly political, at least in the ordinary sense of politics. Sometimes they take place over the distance of decades, even centuries.

Most importantly, they are never based on a misunderstanding. On the contrary, the disagreements arise from perfect comprehension; from having chewed over the ideas of your intellectual opponent so thoroughly that you can properly spit them out.

In other words, to disagree well you must first understand well. You have to read deeply, listen carefully, watch closely. You need to grant your adversary moral respect; give him the intellectual benefit of doubt; have sympathy for his motives and participate empathically with his line of reasoning. And you need to allow for the possibility that you might yet be persuaded of what he has to say.

[Emphasis mine.]

According to a new survey from the Brookings Institution, a plurality of college students today — fully 44 percent — do not believe the First Amendment to the U.S. Constitution protects so-called “hate speech,” when of course it absolutely does. More shockingly, a narrow majority of students — 51 percent — think it is “acceptable” for a student group to shout down a speaker with whom they disagree. An astonishing 20 percent also agree that it’s acceptable to use violence to prevent a speaker from speaking.

Well that’s bitterly disappointing.

That’s because the case for same-sex marriage is too often advanced not by reason, but merely by branding every opponent of it as a “bigot” — just because they are sticking to an opinion that was shared across the entire political spectrum only a few years ago. Few people like outing themselves as someone’s idea of a bigot, so they keep their opinions to themselves even when speaking to pollsters. That’s just what happened last year in the Brexit vote and the U.S. presidential election, and look where we are now.

Shaming people doesn’t generally change their minds; it only makes them more difficult to identify, predict, or actually persuade.

One final point about identity politics: It’s a game at which two can play. In the United States, the so-called “alt-right” justifies its white-identity politics in terms that are coyly borrowed from the progressive left. One of the more dismaying features of last year’s election was the extent to which “white working class” became a catchall identity for people whose travails we were supposed to pity but whose habits or beliefs we were not supposed to criticize. The result was to give the Trump base a moral pass it did little to earn.

It’s a game two can play but it’d be great if no one did.

 

 

“Trade Isn’t War. It’s Peace”

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From The Boston Globe:

Nations don’t trade with each other. We speak as if they do out of habit and convenience, but it’s not true. The United States and Canada are not competing firms. America doesn’t buy steel from China, and China doesn’t buy soybeans from America. Rather, hundreds of individual American companies choose to buy steel from Chinese mills and fabricators, and hundreds of Chinese-owned firms make deals to buy soybeans from far-flung American growers. Unlike wars, which really are fought by nation against nation, international trade occurs among countless sellers and buyers, all acting independently in their own best interest.

Tariffs don’t punish countries. They punish innumerable consumers, wholesalers, importers, exporters, farmers, manufacturers — the myriad discrete actors whose choices and preferences are the true substance of international trade. To those individuals, national trade deficits and surpluses are irrelevant. They aren’t competing — they’re cooperating. Buyers and sellers aren’t in conflict with each other, let alone with each other’s countries.

On the contrary: By doing business together, traders create wealth and connections, knitting the world together in mutual interest, making the planet more harmonious.

Trade war is an insidious term. The metaphor notwithstanding, trade isn’t war. It’s peace.

He’s absolutely right. From my paper currently under review at Economic Affairs:

Using data from the World Bank’s Doing Business rankings and the EFW Index, Michael Strong (2009) finds a close connection between peace, economic liberalization, and business-friendly environments. As a case study, Strong looks to Northern Ireland between 1975 and 2000, determining that the increased economic freedom, the consequential economic boom, and the decrease in violence were interconnected…Using a data set of 243,225 country-pair observations from 1950 to 2000, Lee and Pyun (2016) find that the probability of interstate military conflict is reduced with an increase in bilateral trade interdependence and global trade openness. However, proximity matters, seeing that bilateral trade has a greater peace-promoting effect for neighboring countries, while global trade openness has a greater effect on more distant countries. After analyzing data spanning from 1970 to 2005, De Soysa and Fjelde (2010) find that higher economic freedom lowers the risk of civil war. This corresponds with a later study by De Soysa and Flaten (2012), which finds that higher levels of globalization (particularly economic globalization) reduce the risk of civil war as well as state violations of human rights. Other research finds that free-market conditions and economic liberalization are associated with lower levels of various societal insecurities, including open armed conflict, violent crime, murder, societal militarization and political instability (Stringham & Levendis, 2010; Bjornskov, 2015; De Soysa, 2011, 2016).

Social Capital Project

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Last year, Senator Mike Lee launched The Social Capital Project, described as “a multi-year research effort that will investigate the evolving nature, quality, and importance of our associational life. “Associational life” is our shorthand for the web of social relationships through which we pursue joint endeavors—namely, our families, our communities, our workplaces, and our religious congregations. These institutions are critical to forming our character and capacities, providing us with meaning and purpose, and for addressing the many challenges we face.” The initiative has released several reports, whose findings I will highlight below:

  • What We Do Together: The State of Associational Life in America
    • Between 1975 and 2011, the share of three- and four-year-olds cared for by a parent during the day declined from 80 percent to somewhere between 24 and 48 percent. But parents are spending no less time with their children overall.
    • Between 1973 and 2016, the percentage of Americans age 18-64 who lived with a relative declined from 92 percent to 79 percent. The decline was driven by a dramatic 21-point drop in the percentage who were living with a spouse, from 71 percent to 50 percent.
    • In 1970, there were 76.5 marriages per 1,000 unmarried women aged 15 and older. As of 2015, that rate had declined by more than half to 32 per thousand.
    • In 1970, 56 percent of American families included at least one child, but by 2016 just 42 percent did. The average family with children had 2.3 children in 1970 but just 1.9 in 2016. Among all families—with or without children—the average number of children per family has dropped from 1.3 to 0.8.
    • Between 1970 and 2016, the share of children being raised by a single parent (or by neither parent) rose from 15 percent to 31 percent.
    • Between 1970 and 2015, births to single mothers rose from 11 percent of all births to 40 percent.
    • In the early 1970s, nearly seven in ten adults in America were still members of a church or synagogue. While fewer Americans attended religious service regularly, 50 to 57 percent did so at least once per month. Today, just 55 percent of adults are members of a church or synagogue, while just 42 to 44 percent attend religious service at least monthly.
    • In the early 1970s, 98 percent of adults had been raised in a religion, and just 5 percent reported no religious preference. Today, however, the share of adults who report having been raised in a religion is down to 91 percent, and 18 to 22 percent of adults report no religious preference.
    • In 1973, two-thirds of adults had “quite a lot” or “a great deal” of confidence in “the church or organized religion,” and in another survey the same year, 36 percent reported “a great deal” of confidence in organized religion. By 2016, those numbers had fallen to 41 percent and 20 percent, respectively.
    • Between 1974 and 2016, the percent of adults who said they spend a social evening with a neighbor at least several times a week fell from 30 percent to 19 percent.
    • Between 1970 and the early 2010s, the share of families in large metropolitan areas who lived in middle-income neighborhoods declined from 65 percent to 40 percent. Over that same time period the share of families living in poor neighborhoods rose from 19 percent to 30 percent, and those living in affluent neighborhoods rose from 17 percent to 30 percent.
    • Between 1972 and 2016, the share of adults who thought most people could be trusted declined from 46 percent to 31 percent. Between 1974 and 2016, the number of Americans expressing a great deal or fair amount of trust in the judgement of the American people “under our democratic system about the issues facing our country” fell from 83 percent to 56 percent.
    • Between 1974 and 2015, the share of adults that did any volunteering who reported volunteering for at least 100 hours increased from 28 percent to 34 percent.
    • Between 1972 and 2012, the share of the voting-age population that was registered to vote fell from 72 percent to 65 percent, and the trend was similar for the nonpresidential election years of 1974 and 2014. Correspondingly, between 1972 and 2012, voting rates fell from 63 percent to 57 percent (and fell from 1974 to 2014).
    • Between 1972 and 2008, the share of people saying they follow “what’s going on in government and public affairs” declined from 36 percent to 26 percent.
    • Between 1972 and 2012, the share of Americans who tried to persuade someone else to vote a particular way increased from 32 percent to 40 percent.
    • Between the mid-1970s and 2012, the average amount of time Americans between the ages of 25 and 54 spent with their coworkers outside the workplace fell from about two-and-a-half hours to just under one hour.
    • The share of workers living and working in different counties was 26 percent in 1970 and 27 percent in the second half of the 2000s, and commuting time has risen only modestly since 1980.
    • Between the mid-1970s and 2012, among 25- to 54-year-olds, time at work rose 4 percent. The story was very different for men and women though. Hours at work rose 27 percent among women. Among men, hours at work fell by 9 percent between the mid-1970s and 2012.
    • Work has become rarer, in particular, among men with less education. From the mid-1970s to 2012, hours at work fell by just 2 percent among men with a college degree or an advanced degree, compared with 14 percent among those with no more than a high school education.
    • Between 1995 and 2015, workers in “alternative work arrangements” (e.g., temp jobs, independent contracting, etc.) grew from 9 percent to 16 percent of the workforce.
    • Since 2004, median job tenure has been higher than its 1973 level, indicating that workers are staying in their jobs longer than in the past.
    • Between 1970 and 2015, union membership declined from about 27 percent to 11 percent of all wage and salary workers.

 

  • Love, Marriage, and the Baby Carriage: The Rise in Unwed Childbearing
    • Nonmarital sexual activity has risen substantially since the mid-twentieth century. The share of teen-age women who are sexually active, for example, is 2.5 times higher today than in the early 1960s. Increasing use of reliable contraception has mitigated the effect on unwed childbearing. Over the same period, the share of women having used contraception the first time they had sex outside marriage more than doubled. But while marital pregnancy rates have fallen in half as a result of the contraceptive revolution, because of higher rates of sexual activity, improper contraceptive use, and the increasing acceptability of unwed childbearing, nonmarital pregnancy rates are over one-third higher than in the early 1960s.
    • As for abortion, pregnant women—married or single—are less likely to obtain an abortion than they were before the Roe v. Wade decision. That decline also reflects the declining stigma around unwed childbearing and a drop in unintended pregnancy. Since at least the early 1980s, a rising share of births from nonmarital pregnancies are from pregnancies that were intentional; today, half of births from nonmarital pregnancies are intended.
    • Three times as many births today are from unwed pregnancies than in the early 1960s, and only 9 percent of these pregnancies are followed by a shotgun marriage—down from 43 percent in the early 1960s.
    • We trace these trends to the rising affluence of the mid-twentieth century, when a greater prioritization of nonmaterial needs (especially among women, who saw greatly expanded opportunities) met a rising ability to fulfill them. The effect of affluence was felt in the discovery of penicillin (which dramatically reduced the incidence of syphilis); the introduction of the pill (which expanded women’s opportunities by allowing them to control their fertility); the development and increasing affordability of labor-saving home appliances, processed food, and paid child care (which gave women the opportunity to work longer hours outside the home, raising the opportunity cost of childbearing); and the nation’s expansion of a safety net for single mothers (facilitating childbearing without marriage among more disadvantaged women). Rising affluence is an undeniably beneficial development that we should not want to reverse, but it has also led to less stable family circumstances for an increasing number of children.

 

  • The Geography of Social Capital in America
    • The top fifth of states, in terms of social capital scores, are home to just nine percent of Americans, while 29 percent live in bottom-fifth states.
    • We have social capital scores for 2,992 of 3,142 counties, containing 99.7 percent of the American population. Just eight percent of Americans live in the top fifth of these counties, while 39 percent of the population lives in the bottom fifth of counties. Nearly six in ten (59 percent) of Americans live in the bottom two fifths of counties, compared with 24 percent living in the top two fifths.
    • The 12 states with the highest social capital scores are distributed across two continuous blocs: nine states running from Utah, through Wyoming and Colorado, across the Dakotas and Nebraska, and over to Iowa, Minnesota, and Wisconsin; and the three Northern New England states of Maine, New Hampshire, and Vermont. These states tend to rank highly across all seven subindices as well. Utah has the highest social capital score, followed by Minnesota and Wisconsin.
    • Of the 11 states with the lowest levels of social capital, ten of them fall within a contiguous bloc of states running from Nevada, across the Southwest and South over to Georgia and Florida. New York is the only state in the bottom 11 that is outside this group. Louisiana has the lowest social capital score, followed by Nevada, Arizona, and New Mexico.
    • Of the nine states ranked just above this bottom group, seven border and extend the southern bloc, filling out most of the rest of the South. The 17 southern states in the bottom 20 are home to 45 percent of Americans and 74 percent of Americans in bottom-fifth counties. Six in ten (59 percent) of people in the 17 states live in bottom-fifth counties. Only 17 of 1,338 counties in these states are in the top fifth.
    • Our indices are not dominated by any single subindex, and our state and county indices appear to be approximating social capital in the same general way.
    • Among the component variables underlying the state index, the strongest associations with the index itself across states were for the volunteer rate (0.86), heavy television watching by children (-0.81), the share of adults who made charitable contributions (0.80), the share with emotional and social support (0.80), heavy usage of electronics among children (-0.77), the share of adults that are married (0.75), the share of children living with a single parent (-0.72), and the share of births that were to unwed mothers (-0.71).
    • At the county level, the highest correlates of social capital were violent crime (-0.73), the share of children with a single parent (-0.71), the share of adults currently married (0.69), voting rates (0.59), and nonprofits plus congregations (0.57).
    • Despite the outsized role that religious communities have played in social capital investment, indicators of religious adherence and commitment were generally weakly (or even negatively) correlated with our social capital scores, both at the state and county levels. This may suggest that social capital organized around religion may be displaced by secular sources of social capital, that the availability of resources provided by secular social capital weakens religious commitment, or that people in distressed places turn to religious communities for the support that is missing in other parts of their lives. This question is a subject for future Social Capital Project research.
    • Our social capital indices correlate strongly with earlier social capital indices across states and counties, and with other indices such as the Family Prosperity Institute’s Family Prosperity Index, Opportunity Nation’s Opportunity Index, and the Economic Innovation Group’s Distressed Communities Index.
    • We show the correlations of our indices and subindices with 59 state-level and 50 county-level benchmarks reflecting a range of economic, social, demographic, educational, health, and other outcomes.
    • Our index is a clear improvement on the Penn State index, based on this benchmarking, but remarkably, Robert Putnam’s state index from Bowling Alone, published nearly two decades ago, has slightly higher benchmark correlations than ours. Because our index captures the health of family life, and because it is based on up-to-date and freely available data (including at the county level), we still prefer it to the Putnam measure. The fact that the correlation between the two state-level indices is 0.81 reassuringly suggests that very different approaches to social capital measurement capture the same essential construct.

Check them out.

Worldwide Income Inequality

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I’ve highlighted the decline in global income inequality several times before. A new working paper suggests that this trend will continue into the near future:

Considerable recent research has focused on changes in income inequality within countries [Atkinson, Piketty, and Saez 2011; Alvaredo et al. 2013; Saez and Zucman 2016; Assouad, Chancel, and Morgan 2018; Novokmet et al. 2018]. There is substantial variation in income inequality within countries. Income inequality after taxes and transfers is relatively low in Canada, Japan and most western European countries and quite high in Brazil, Egypt, India, Mexico, and South Africa [Solt 2016]. Moreover, within-country income inequality has increased in recent decades in several large economies, including China, Russia, and the United States [Assouad, Chancel, and Morgan 2018].

Recent scholarly research has also addressed cross-country and worldwide income inequality [Bourguignon and Morrisson 2002; Sala-i-Martin 2006; Hellebrandt and Mauro 2015; Milanovic 2013; Bourguignon 2015; Milanovic 2016]. This article makes three major contributions to the literature on global income inequality. First, development as a process is integrated into the analysis of income inequality. Researchers have generally ignored the impact of the development process on demographic changes and income inequality. Changes in demographic factors as countries move through different phases of the development process will be examined and their impact on economic growth and income inequality analyzed. Second, Gini coefficient measures are developed for cross-country income inequality from 1820 to 2015 and for each of the three types of income inequality for 1960 to 2015. Third, the impact of development as a process and changes in other factors that influence economic growth, are used to project future changes in income inequality.

During 1960-2000, demographic changes accompanying the development process contributed to the sizeable increases in cross-country and worldwide income inequality. However, beginning in the 1990s, changing demographic factors accompanying the development process led to a reversal of this situation. Increasingly, developing countries have moved into phases of development associated with high rates of economic growth, while the high-income countries have moved into a development phase that results in slower growth. As a result, there has been a dramatic reduction in income inequality during 2000-2015. Moreover, it is a virtual certainty that the demographic factors underlying the recent reductions in inequality will continue for at least a couple more decades, leading to further reductions in global income inequality (pg. 2-3).

In an interview, Nobel economist Angus Deaton noted, “I both love inequality and am terrified of it. Inequality is partly a marker of success, so that if someone thinks of something, some new innovation that benefits us all, and the market works properly, they get richly rewarded for that. And that’s just terrific. And that creates inequality. So some of the greatest inequalities in the world have come from the greatest successes.” This seems to fit with the phases of development discussed above.

“The Captured Economy” Site

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I picked up Brink Lindsey and Steve Teles’ book The Captured Economy last week at Half-Price Books and added it to my never-ending to-read list. Turns out they’ve created a website based on the book. They describe the site as follows:

Image result for the captured economyIn November 2017, Oxford University Press published The Captured Economy: How the Powerful Enrich Themselves, Slow Down Growth, and Increase Inequality. Coauthored by Niskanen Center scholars Brink Lindsey and Steven M. Teles, The Captured Economy argues that systematic breakdowns in democratic governance have allowed wealthy special interests to capture broad domains of the policymaking process and twist the rules for their own benefit. Steadily worsening “upward redistribution” via “regressive regulation” has contributed significantly to the American economy’s twin woes of stagnating growth and sky-high inequality.

This website builds on and expands the analysis provided in The Captured Economy. In the book, Lindsey and Teles briefly examined four broad policy areas that showcase the problem of regressive regulation: financial regulation, intellectual property protection, occupational licensing, and land-use regulation. They admitted, though, that space constraints permitted them to cover “only the tip of the iceberg.” This website is dedicating to explore the phenomenon in all its murky depths.

We begin by focusing on the four policy areas covered in the book, but over time we plan to include additional, related policy and issue areas. For each covered area, capturedeconomy.com will serve as a comprehensive repository of analysis and news, including not only academic research and journalistic analysis but also the latest news on policy developments. Our goal is to make capturedeconomy.com an indispensable resource for journalists, policymakers, and concerned citizens interested in better understanding and remedying the deep structural problems that afflict American policymaking and economic performance.

Seems like an exciting development.

WEIRD Origins

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“Thou art weird.”
Anthropologist and cultural psychologist Joseph Henrich has defined our peculiar subset of the world population as WEIRD: Western, Educated, Industrialized, Rich, Democratic. How did this psychological variation arise? A new working paper offers a very interesting answer:

A growing body of research suggests that populations around the globe vary substantially along several important psychological dimensions, and that people from societies characterized as Western, Educated, Industrialized, Rich and Democratic (WEIRD) are particularly unusual (1–6). Often at the extremes of global distributions, people from WEIRD populations tend to be more individualistic, independent, analytically-minded and impersonally prosocial (e.g., trusting strangers) while revealing less conformity, obedience, in-group loyalty and nepotism (3, 5–13). While these patterns are now well documented, efforts to explain this variation from a cultural evolutionary and historical perspective have just begun (13–20). Here, we develop and test a cultural evolutionary theory that aims to explain a substantial portion of this psychological variation, both within and across nations. Not only does our approach contribute to explaining global variation and address why WEIRD societies so often occupy the tail ends of global distributions, but it also helps explain the psychological variation within Europe—among countries, across regions within countries and between individuals with different cultural backgrounds within the same country and region.

Our approach integrates three insights. The first, drawing on anthropology, reveals that the institutions built around kinship and marriage vary greatly across societies (21–23) and that much of this variation developed as societies scaled up in size and complexity, especially after the origins of food production 12,000 years ago (22, 24–29). In forging the tightly-knit communities needed to defend agricultural fields and pastures, cultural evolution gradually wove together social norms governing marriage, post-marital residence and in-group identity (descent), leading to a diversity of kin-based institutions, including the organizational forms known as clans, lineages and kindreds (21, 27, 30). The second insight, based on work in psychology, is that people’s motivations, emotions, perceptions, thinking styles and other aspects of cognition are heavily influenced by the social norms, social networks, technologies and linguistic worlds they encounter while growing up (31–38). In particular, with intensive kin-based institutions, people’s psychological processes adapt to the collectivistic demands and the dense social networks that they interweave (39–43). Intensive kinship norms reward greater conformity, obedience, holistic/relational awareness and in-group loyalty but discourage individualism, independence and analytical thinking (41, 44). Since the sociality of intensive kinship is based on people’s interpersonal embeddedness, adapting to these institutions tends to reduce people’s inclinations towards impartiality, universal (non-relational) moral principles and impersonal trust, fairness and cooperation. Finally, based on historical evidence, the third insight suggests that the branch of Western Christianity that eventually evolved into the Roman Catholic Church—hereafter, ‘the Western Church’ or simply ‘the Church’—systematically undermined the intensive kin-based institutions of Europe during the Middle Ages (45–52). The Church’s marriage policies and prohibitions, which we will call the Marriage and Family Program (MFP), meant that by 1500 CE, and likely centuries earlier in some regions, Europe lacked strong kin-based institutions, and was instead dominated by relatively weak, independent and isolated nuclear or stem families (49–51, 53–56). This made people exposed to Western Christendom rather unlike nearly all other populations.

Integrating these insights, we propose that the spread of the Church, specifically through its transformation of kinship and marriage, was a key factor behind a cultural shift towards a WEIRDer psychology in Europe. This shift eventually fostered the creation of new formal institutions, including representative governments, individual rights, commercial law and impersonal markets (17, 57). This theory predicts that (1) societies with less intensive kin-based institutions should have a WEIRDer psychology and (2) historical exposure to the Church’s MFP should predict both less intensive kin-based institutions and, as a consequence, a WEIRDer psychology.

To illuminate these relationships for diverse populations, we (1) developed measures of the intensity of kin-based institutions, (2) created historical databases to estimate the exposure of populations to the Church (along with the MFP) and (3) compiled 20 different psychological outcomes, including laboratory experiments, validated scales, survey questions and ecologically-valid observational data. We examine the predicted relationships from three complementary perspectives. Across countries, we can observe the broadest range of variation in the largest number of psychological outcomes. Across regions, we can track the historical Church as it lumbered across Europe and detect its footprints on the psychological patterns and marital arrangements of modern Europeans. Finally, by comparing second-generation immigrants in Europe based on their links to the kin-based institutions of their ancestral communities around the world, we eliminate many alternative hypotheses for the relationships we’ve illuminated.

Check it out.

Does Loneliness Lead to Pornography Consumption or Vice Versa?

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According to a new study, the answer is “yes” to both:

Image result for shame laptop gifOur study suggests a close and painful partnership between pornography and loneliness for some users. From our survey of over 1,000 individuals around the world, we developed a statistical model that suggests an association between pornography use and loneliness, each increasing in tandem with the other. Each incremental increase in loneliness was associated with an increase in pornography use (by a factor of 0.16), and each incremental increase in pornography use predicted a significant increase in loneliness (by a factor of 0.20). While the magnitude of effects was small, they were statistically significant. Interlocking partnerships like this are worrisome since they represent an entrapment template associated with addiction—where the consequences of coping with loneliness through pornography use only increase loneliness, potentially locking the two in a self-fueling cycle.

If loneliness can lead to pornography use, and pornography use may bring about or intensify loneliness, these circular linkages may create a vicious cycle, pulling the user even further from health-promoting relationship connections. In the cultural context of emotionally-disconnected sexual hookups scripted by pornography, loneliness may deepen and become increasingly painful, yet in response, pornography use may only intensify.

While the gender gap in pornography use is closing, men still use pornography more than women, and married persons use pornography less than single persons. The fact that pornography use decreases after marriage may hint at a link between pornography, relational success, and loneliness. Are those who use pornography less likely to achieve relational success and marry? Or does relational success in marriage remove the loneliness trigger for pornography use—or both?

How do porn and loneliness work in tandem?

Image result for shame michael fassbenderPornography triggers the sexual system, providing a physical “feel-good” experience overshadowing negative feelings. Sexual arousal and climax offer a quick “feel-good” fix. Pornography also expands the sexual system’s escape through creating sexual anticipation, bringing a person “under the influence” of sexual arousal for as long as they care to be before acting out.

Additionally, the sexual system is biologically and neurologically tied to a relationship experience. The human sexual system is carefully designed to support both conception and bonding. First, there’s the physical pleasure of arousal, intercourse, and climax—the engine designed to ensure offspring. Then, after climax, partners experience the brain’s “love” plan for pair bonding, when oxytocin (or what researchers refer to as the “cuddle chemical”) is released, producing feelings of comfort, connection, and closeness. In the context of a caring attachment relationship, this release and “after-play” support emotional bonding.

When pornography is used to trigger the sexual system, the biology of the sexual system produces a false relationship experience, offering temporary “relief” from lonely feelings, but soon enough, the user again faces a real-world relationship void. That emptiness may trigger loneliness. Additionally, porn invites the mental fantasy of a relationship experience. Thus, the mind fantasizes and biologically the sexual system tricks the brain into imagining it’s having a relationship experience and can thus mask loneliness—but only temporarily. In this way, pornography exploits the sexual system but only tricks the brain for a while. The user can’t escape the fact that when the experience is over, they’re still alone in an empty room. So, when sexual intoxication wears off, the experience may only end up excavating a deeper emptiness—a setup for a vicious cycle. We hypothesize that this experience could create the potential for getting trapped in the short-term, feel-good escape of pornography joined with long-term loneliness.

Image result for shame crying gif…Recent scholarship suggests that pornography’s sexual scripts of eroticism, objectification, promiscuity, and misogyny (domination) are, on their face, fundamentally anti-relationship and anti-attachment and “conceptually linked to loneliness.” Pornography promotes an understanding of sexuality and relationships that is corrosive to connection because it doesn’t promote people, only parts. Hence, in the most intimate of circumstances, actual intimacy is elusive—because pornography doesn’t support or advocate emotional connection and whole relationships.

…In the recent research conducted with my colleagues, we raise the possibility of pornography use compulsivity or addiction, pointing to how pornography use fits this entrapment template. The potentially habitual “fix” of pornography may consist in using it to relieve loneliness (or other troubling emotions). The sexual system’s combination of two very different rewards—intense sensual gratification during arousal and climax, followed by oxytocin’s relief and comfort during the resolution period—could be thought of like a combined cocaine-valium experience and “hook.”

Sex therapist and friend Mark Bird lists pornography addiction as one of “ways people try to cope ineffectively: [one of] the negative symptoms associated with connective disorders.”[ref]Mark Bird, In Tandem: Recovering Me, Recovering Us, pgs. 20-21.[/ref] The above research seems to back this claim.

Income vs. Consumption Inequality, 1961-2016

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I’ve highlighted this before, but Bruce Meyer has an article in the NBER Reporter on consumption vs. income inequality. He explains,

The debate over inequality relies almost exclusively on income data that indicate that inequality has increased sharply in recent decades. Yet economists generally prefer using consumption rather than income to measure well-being…Income typically fluctuates more than economic well-being, because people can save when income is temporarily high and borrow when it is temporarily low. Income also fails to reflect the flow of services received if one already owns a house or a car, and has no expenditures but significant consumption. A retired couple in their own home living off the savings accumulated over a lifetime may be living quite comfortably even if they have no income. Consumption measures will reflect the loss of housing-services flows if homeownership falls, the loss in wealth if asset values fall, and the belt-tightening that a growing debt burden might require — all of which an income measure would miss. Furthermore, consumption is more likely than income to be affected by access to public insurance programs, and to capture the effects of changes in access to credit or the government safety net. Consumption is better than income at reflecting deprivation. In a series of papers, Sullivan and I show that measures of material hardship or adverse family outcomes are more severe for those with low consumption than for those with low income.

What does inequality look like when viewed through the lens of consumption?

Official measures of income inequality suggest a steady rise in the U.S. since the early 1970s. An important limitation of the official statistics is that they are based on pre-tax money income, which does not account for tax credits and in-kind transfers, such as housing benefits and food stamps, which have increased sharply over time. Income inequality still rises for measures of income that more closely reflect family resources available for consumption, but the rise is less noticeable. Using our improved measure of consumption, however, a very different story emerges.

These differences are evident in Figure 1, where we report the ratio of the 90th percentile to the 10th percentile (the 90/10 ratio) for pre-tax money income, after-tax money income, and well-measured consumption. Since the early 1960s, the rise in after-tax income inequality as measured by the 90/10 ratio (26 percent) has significantly exceeded the rise in consumption inequality (7 percent). Furthermore, this much smaller percentage increase in consumption inequality started from a considerably lower base. In some decades, such as the 1960s and 1990s, income and consumption inequality moved in parallel, but in other decades the differences were sharp. In the 1980s, inequality for both measures rose, but the increase was much greater for income (28 percent) than for consumption (5 percent). After 2005, these measures moved in opposite directions: income inequality rose sharply while consumption inequality fell.

The center and right panels of Figure 1 show that income inequality has risen for the top (90/50 ratios) and bottom (50/10 ratios) of the distribution, but increases in consumption inequality are only evident for the top. The finding that the patterns of consumption and income inequality at the top are fairly similar from the early 1960s through 2005 suggests that underreporting of consumption by the rich is not behind the differences in inequality over time.

Our evidence of only a modest rise in consumption inequality over the past five decades contrasts sharply with evidence from tax data that an increasing share of the nation’s income is going to the very highest income families, though several papers using broader and more consistent measures of income reported on income tax forms do not show large increases in the top 1 percent’s income share. Our analyses are distinct from these studies that focus on the highest income households. We do not include the extreme tails of the distribution because resources are likely to be poorly measured in survey data for these observations. Tax returns alone are also unsuitable for measuring incomes at the bottom, since they miss non-filers and important sources of income such as TANF, SSI, SNAP and housing benefits, which are not taxable.

Meyer1

Meyer concludes,

Most of the discussion around recent trends in inequality highlights growing dispersion. However, the evidence from consumption data indicates that changes in inequality in economic well-being are more nuanced than a simple story of rising income dispersion would suggest. In the bottom half of the distribution there is little evidence of rising consumption inequality, and in the top half of the distribution the rise in consumption inequality has been much more modest than the rise in income inequality, particularly since 2000.

Do Undocumented Immigrants Commit More Crime?

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From the Oxford Research Encyclopedia of Criminology and Criminal Justice,

Despite recent research that shows the lack of a direct connection between immigration and increases in crime, the American public still believes that immigrants are a dangerous group…Illegal immigration occurs when a person unlawfully enters the United States or overstays their visa once in the country; it is estimated that between 30 and 50% of undocumented immigrants in the United States have overstayed their visas (Blondell, 2008; Metcalf, 2011). The perception that “all” undocumented immigrants have nefariously crossed the U.S. border is not accurate. More refined analysis regarding legal and illegal immigration and crime has been done by researchers in recent years.

Researchers in the United States have begun to distinguish between the act of being an undocumented immigrant, which is illegal, and crimes committed by immigrants. Metcalf (2011), for example, found that if an undocumented immigrant is processed by an immigration court for deportation, deportation is most likely to actually occur if the person committed a serious felony. In other cases, the individual is likely to be released and will continue to unlawfully reside in the United States. Concern about crimes committed on or near the U.S. border has also resulted in some studies about the nexus among migration, victimization, and criminal offending. Hickman and Suttorp (2015) analyzed whether undocumented immigrants were more likely to be a recidivist one year after release from jail than nondeportable immigrants. Analyzing a month of data from the Los Angeles County Jail in 2002, they found that 21% of inmates were “foreign born.” For those whose immigration status was known, and for which the inmate was not released to another agency, about 60% of the inmates were nondeportable and 40% were deportable immigrants. One year after release from the county jail, deportable immigrants were no more a threat to public safety than immigrants who were nondeportable (Hickman & Suttorp, 2015). Hickman and Suttorp concluded that the fear that undocumented immigrants are a disproportionate threat to a community’s safety is not empirically supported by analysis of data for the immigrants subjected to criminal justice sanctions at a local jail level. The re-arrest rate for all the immigrants (both deportable and nondeportable) in their study was relatively low (about 38%).

I’ve covered this topic before, but it is worth revisiting. The above ORE article is from 2017, but is there even more recent evidence? As reported by NPR,[ref]The charts are from The Washington Post.[/ref]

Michael Light, a criminologist at the University of Wisconsin, Madison, looked at whether the soaring increase in illegal immigration over the last three decades caused a commensurate jump in violent crimes: murder, rape, robbery and aggravated assault. “Increased undocumented immigration since 1990 has not increased violent crime over that same time period,” Light said in a phone interview. Those findings are published in the current edition of the peer-reviewed journal Criminology.

In a separate study, these same researchers previously looked at nonviolent crime. They found that the dramatic influx of undocumented immigrants, similarly, did not drive up rates of drug and alcohol arrests or the number of drug overdoses and DUI deaths. “We found no evidence that undocumented immigration increases the prevalence of any of those outcomes,” Light said.

A third study, by the libertarian Cato Institute, recently looked at criminality among undocumented immigrants just in Texas. The state records the immigration status of arrestees, creating a gold mine for criminologists. Cato found that in 2015, criminal conviction and arrest rates in Texas for undocumented immigrants were lower than those of native-born Americans for murder, sexual assault and larceny.

Finally, a research paper appearing in the current edition of the U.K. journal Migration Letters shows that youthful undocumented immigrants engage in less crime than do legal immigrants or U.S.-born peers.

As The Washington Post notes, “These two studies are far from the only ones showing that immigration, legal or otherwise, does not lead to rising crime. But the evidence they present is some of the strongest offered to date. The Trump administration, however, does not seem to be listening.”