Do Bumps in the Minimum Wage Increase the Number of Job Seekers?

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Some argue that increasing the minimum wage will increase the number of job seekers and, consequently, employment. From a new NBER paper:

Do minimum wage increases affect search effort by job seekers?

…We investigate the effect of minimum wage increases on job search effort utilizing data from the Current Population Survey (CPS) and the American Time Use Survey (ATUS). We exploit the staggered nature of CPS and ATUS interviews and use an event-study approach, leveraging within-state variation in the adoption of minimum wage changes. We account for shocks affecting a particular state in a given year as well as month effects to control for seasonality, and individual demographic characteristics. Intuitively, we compare the outcomes in each month near the treatment date to the outcomes for otherwise-identical individuals in the same state and year whose survey period was not near a treatment date.

We find no evidence that the minimum wage has persistent effects on search effort; the likelihood of searching does not increase in the aftermath of minimum wage increases. However, there is a large yet transitory increase in the intensive margin of search effort, concentrated
in the month of the minimum wage increase, that fades almost immediately. There is no short-run increase in the employment rate nor changes in observable characteristics of searchers, suggesting that our results are not driven by changes in the composition of job seekers. These findings are robust to the inclusion of demographic controls, the duration of unemployment benefits, and month-by-year fixed effects that account for any idiosyncratic national-level variation in a given month. We also conduct a permutation test for our search duration results in which we randomly assign minimum wage increases across time periods and show that these results do not appear to be due to chance.

Our results call into question the assumption underpinning search-and-matching models as applied to analysis of the minimum wage – namely, that more workers will enter the labor market and each worker will search harder, increasing the returns to firm vacancy postings. Importantly, we find minimum wage increases do not induce individuals to begin searching. While we find that minimum wage increases yield significant increases in worker search effort on the intensive margin, they are transitory (pg. 2-3).


What Kind of Immigration Fuels Nationalism?

From a recent NBER Digest:

In Skill of Immigrants and Vote of the Natives: Immigration and Nationalism in European Elections 2007-16 (NBER Working Paper No. 25077), Simone Moriconi, Giovanni Peri, and Riccardo Turati explore the relationship between immigration and European elections. They develop an index of “nationalistic” attitudes of political parties to measure the shift in preferences among voters when confronted with influxes of skilled and unskilled immigrants. They find that larger inflows of highly educated immigrants dampen nationalistic sentiments, while larger inflows of less-educated immigrants heighten them. Their results imply that a more balanced inflow of high-skilled and low-skilled immigrants could attenuate voters’ nationalistic attitudes.

...The new study tracks voter attitudes and behavior for all political parties and elections in 12 European countries for a decade. It relies on demographic and political data from the European Social Survey and a number of other sources. In addition, the researchers collected and classified the political manifestos of 126 parties for 28 elections, focusing in particular on how frequently these materials mentioned nationalistic subjects, the European Union, and other indicators of where parties stood on the political spectrum.

The researchers found “that highly educated native voters are less nationalistic in their attitudes towards immigrants than less-educated natives. The data also show strong nationalistic sentiments in regional pockets in the United Kingdom, Ireland, France, Germany, Demark, Sweden, Norway and, especially, Italy.”

The results suggest that a 1 percent increase in the share of a country’s population who are immigrants in highly educated, highly skilled groups was associated with a 0.1 standard deviation voting change away from nationalism. An increase of comparable size in the number of less-educated and lower-skilled immigrants led to a 0.12 standard deviation voting change towards nationalism. The same patterns emerged when the researchers analyzed voter sentiment expressed in surveys. In this case, a 1 percent increase in high-skilled immigrants led to a 0.07 standard deviation decrease away from nationalism, while a 1 percent increase in lower-skilled immigrants lead to a 0.07 standard deviation increase in nationalism. The results were broadly similar regardless of whether the analysis focused on all immigrants or only on immigrants from non-EU nations.

Immigration is not only about ethnicity, but class as well.

What’s Behind Cuba’s Health Outcomes?

The above comes from Michael Moore’s Sicko. Cuba’s healthcare system is a common talking point among those of Moore’s persuasion. However, a recent study should give us pause regarding some of the overly positive claims about Cuba’s system. First, what people like Moore get right:

How is Cuba healthy while poor? Most attribute the fact to Cuba’s zero monetary cost health care system. There is some truth to that attribution. With 11.1% of GDP dedicated to health care and 0.8% of the population working as physicians, a substantial amount of resources is directed towards reducing infant mortality and increasing longevity. An economy with centralized economic planning by government like that of Cuba can force more resources into an industry than its population might desire in order to achieve improved outcomes in that industry at the expense of other goods and services the population might more highly desire (pg. 755).


Centralized planning has disadvantages. Physicians are given health outcome targets to meet or face penalties. This provides incentives to manipulate data. Take Cuba’s much praised infant mortality rate for example. In most countries, the ratio of the numbers of neonatal deaths and late fetal deaths stay within a certain range of each other as they have many common causes and determinants. One study found that that while the ratio of late fetal deaths to early neonatal deaths in countries with available data stood between 1.04 and 3.03 (Gonzalez, 2015)—a ratio which is representative of Latin American countries as well (Gonzalez and Gilleskie, 2017). Cuba, with a ratio of 6, was a clear outlier. This skewed ratio is evidence that physicians likely reclassified early neonatal deaths as late fetal deaths, thus deflating the infant mortality statistics and propping up life expectancy. Cuban doctors were re-categorizing neonatal deaths as late fetal deaths in order for doctors to meet government targets for infant mortality.

Using the ratios found for other countries, corrections were proposed to the statistics published by the Cuban government: instead of 5.79 per 1000 births, the rate stands between 7.45 and 11.16 per 1000 births. Recalculating life expectancy at birth to account for these corrections (using WHO life tables and assuming that they are accurate depictions of reality), the life expectancy at birth of men by between 0.22 and 0.55 years (Gonzalez, 2015) (pg. 755).

But that’s not the only thing driving low infant mortality rates:

Coercing or pressuring patients into having abortions artificially improve infant mortality by preventing marginally riskier births from occurring help doctors meet their centrally fixed targets. At 72.8 abortions per 100 births, Cuba has one of the highest abortion rates in the world. If only 5% of the abortions are actually pressured abortions meant to keep health statistics up, life expectancy at birth must be lowered by a sizeable amount. If we combine the misreporting of late fetal deaths and pressured abortions, life expectancy would drop by between 1.46 and 1.79 years for men. In Figure 1 below, we show that that with this adjustment alone, instead of being first in the ranking of life expectancy at birth for men in Latin America and the Caribbean, Cuba falls either to the third or fourth place depending on the range (pg. 755-756).

The researchers explain, “Other repressive policies, unrelated to health care, contribute to Cuba’s health outcomes” (pg. 756) These include:

  • Restrictions in car ownership leading to low automobile fatalities.
  • Rationing combined with physically demanding transportation (e.g., cycling) contributing to reductions in obesity and deaths caused by diabetes, coronary heart diseases and strokes.

The researchers conclude,

Cuban mortality and longevity statistics appear impressive. They are a result of some combination of the government’s choice to allocate more resources into the health care industry (at the expense of other industries that could produce needed goods) and from coercive measures through both health delivery and economic planning that improve health statistics at the expense of other spheres of life.

Although the USA and other countries re-examine how to design health care delivery they should not uncritically accept the myth that the Cuban health care system has been the sole, or even the most important, cause of Cuba’s abnormally high longevity statistics. The role of Cuban economic and political oppression in coercing ‘good’ health outcomes merits further study (pg. 756).

The Effects of Corporate Taxes on Innovation

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I’ve looked at some of the negative effects of corporate taxes in previous posts. These largely had to do with wages and employment. But a new study based on Chinese data finds that they can have negative effects on innovation:

Theoretically, taxes can have either positive or negative impacts on firm innovation. On the one hand, lower taxes can increase the after-tax profit of firms, so that they have better capacity to invest in new technologies or products. Moreover, lower taxes may reduce the resources that firms spend on tax evasion, such as the costs of bribing tax officers, which can be instead used on innovation activities. On the other hand, lower taxes may also have a negative impact on innovation because they decrease government revenue, and in turn may reduce government spending on public goods such as research, education, and infrastructure. As a result, whether providing tax incentives can improve firm innovation is ambiguous. 

In a new study, we investigate the impact of taxes on firm innovation using a natural experiment in China (Cai et al. 2018). In November 2001, China implemented a tax collection reform on all manufacturing firms established on or after January 2002, which switched the collection of corporate income taxes from the local tax bureau to the state tax bureau. After the reform, similar firms established before or after 2002 could pay very different effective tax rates because of the differences in the management and incentives of those two types of tax bureaus…[T]he reform changed the enforcement of tax collection, resulting in a reduction of effective corporate income tax rates by almost 10% among newly established firms.

…To test the impact of taxes on innovation, we combine a comprehensive dataset of all medium and large enterprises in China between 1998 and 2007 with patent data from the State Intellectual Property Office (SIPO), including all patents applied in China by the year 2014. We use the data to measure three dimensions of innovation activities – input (R&D expenditure and skilled labour ratio), output (number of patent application), and quality (type and characteristics of patent application). 

Our analysis yields several interesting results. First, we show a strong and robust causal relationship between tax rate and firm innovation. Decreasing the effective tax rate by one standard deviation (0.01) increases the average number of patent application by a significant 5.7% (see Figure 2 for the graphical evidence). The reform also stimulated R&D expenditures and increased the skilled-labour ratio by 14%. Second, a lower tax rate also improves the quality of patents. The impact of tax reform on patent applications mainly comes from its effect on invention and utility patents – decreasing the effective tax rate by one standard deviation improves the probability of having an invention patent application by 4.4% and increases the number of utility patent applications by 4.7%. This suggests that the improvement in innovation outcomes is not merely driven by the low-quality design patents. We also use the detailed information on patent applications as proxies for the patent quality, including number of claims, number of independent claims, and the amount of effort that was spent on the patent application (length of the application document, number of figures, and length of abstract). In our patent data, only invention and utility patents have the above information, and results suggest that a reduction in the tax rate significantly improved patent quality, and the effect is significant for both invention and utility patents. 

Another study drawing on datasets from the 20th century had similar results:

We use new data from the 20th century to show a negative effect of high taxes on innovation. We use three newly constructed datasets consisting of: (1) the universe of corporate and non-corporate inventors who patented since 1920, as well as the citations to their patents; (2) the patents, research employment, and location of laboratory facilities of firms active in R&D; and (3) an historical state-level database of corporate income taxes linked to personal income tax rates from Bakija (2017).

…At the macro level, we find that the effects of taxes are strongly negative and quantitatively important. For example, a one percentage point increase in either the median or top marginal tax rate is associated with an approximately 4% decline in patents, citations, and inventors, and a close to 5% decline in the number of superstar inventors in the state. A one percentage point higher top corporate tax rate leads to around 6-6.3% fewer patents, 5.5-6% fewer citations, 4.6-5% fewer inventors, and 8.5-9.3% fewer superstar inventors.

Furthermore, we find that the share of patentsassigned to corporations appears to be extremely sensitive to the corporate tax rate. A one percentage point increase in the top corporate tax rate is associated with close to 1.2 percentage points fewer patents assigned to companies.      

Individual case studies of tax regime changes underscore how important the effect of taxation could be. As one example, Figure 4 shows the depressing impact on innovation of Michigan’s 1967 and 1968 tax reform bills. In 1967, Michigan introduced its personal income tax, at a rate of 2.6%. In 1968, it then introduced its corporate income tax, at a rate of 5.6%. In the subsequent years, the state experienced a substantial decline in innovative output relative to its peer states.

…At the micro level, we similarly find that taxation negatively affects innovation. To estimate the effect, we assign inventors to their tax brackets based on their productivity, which we observe in the patent data. A one percentage point higher tax rate at the individual level decreases the likelihood of having a patent in the next three years by 0.63 percentage points, even controlling for inventor quality and all other state-level policy changes. The likelihood of having high-qualitypatents with more than ten citations decreases by 0.6 percentage points for every percentage point increase in the personal tax rate. We also show that corporate inventors — inventors who appear on at least one patent assigned to a company — are much more responsive to personal and corporate income taxes than non-corporate inventors, consistent with the profit-sharing narrative posited above, as well as with different motives for innovation. 

Inventors prefer to locate in places where other inventors are active in their particular technology area. This suggests there are particular characteristics which may matter to inventors, and which can ultimately dampen their responses to taxation. Silicon Valley, for example, still attracts an abundance of tech inventors due to its rich network of capital and labour resources for innovation, despite California being a high tax state.          

At the firm level, we find consistently negative effects of taxation on patents and citations. We also find that the top corporate tax rate has a significantly negative effect on the decision of a firm to locate its R&D laboratory in a given state.

Innovation is critical to improvements in human well-being. Something for policymakers to consider.

The Benefits of Walmart

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Walmart catches a lot of grief. For example, as reported by CNN, Bernie Sanders recently “introduced a bill, titled the Stop Walmart Act, that would prevent large companies from buying back stock unless they pay all employees at least $15 an hour, allow workers to earn up to seven days of paid sick leave and limit CEO compensation to no more than 150 times the median pay of all staffers.” Yet, many don’t consider the massive benefits produced by Walmart: 

A 2005 Global Insight study commissioned by Wal-Mart and overseen by an independent panel suggested that a new Wal-Mart would create, on net, 137 jobs in the short term and 97 jobs in the long term (Global Insight 2005: 2). Studying Pennsylvania counties, Hicks (2005, discussed by Vedder and Cox 2006: 110) found that the company led to a net increase of fifty new jobs with a 40% reduction in job turnover. Hicks (2007: 93-94) uses data from Indiana to estimate that Wal-Mart increases rural retail employment from 3.4% to 4.8% after correcting for endogeneity. After correcting for endogeneity of urban Wal-Mart entry, Hicks argues that Wal-Mart leads to a 1.2% increase in employment but points out that this estimate is statistically insignificant.

…Wal-Mart’s most obvious effect on the retail sector comes through its policy of Every Day Low Prices. Basker (2005b) and Basker and Noel (2009) estimate that WalMart has a substantial price advantage over competitors with the effect being that prices among incumbent competitors fall after Wal-Mart entry. Hausman and Leibtag (2007: 1147) argue that the compensating variation from Big Box retailers’ effect on prices leads to welfare increases of some 25% of total food expenditure for people who enjoy the direct and indirect effects of Big Box stores. Further, they argue (Hausman and Leibtag 2009) that the Consumer Price Index is over-estimated because it fails to account properly for price effects of supercenters, mass merchandisers, and club stores. Evaluating estimates of the price effects of Big Box retailers and adjusting for foreign sales, Vedder and Cox (2006: 18-19) argue that “the annual American-derived welfare gains are probably still in excess of $65 billion, or about $225 for every American, or $900 for a typical family of four.”

…Jason Furman (2005) called Wal-Mart a “progressive success story” because of its impact on prices. He notes that if the 2005 Global Insight estimate of annual average household savings of $2,329 is accurate, the annual Wal-Mart related consumer savings of $263 billion dwarfs Wal-Mart-generated reductions in retail wages of $4.7 billion estimated by Dube et al. (2005). Hicks (2007: 82) notes that reductions in nominal retail wages are likely offset by larger price reductions, which translates into higher real wages. Courtemanche and Carden’s (2011a) estimate of $177 per household in savings attributable to the effects of Wal-Mart Supercenters in 2002 multiplied by the 105,401,101 households in the 2000 census yields household savings of $18.7 billion, which is still substantially higher than Dube et al.’s estimate of lost wages. 

Hausman and Leibtag (2007: 25) argue that the compensating variation—i.e., welfare increase—attributable to supercenters, mass merchandisers, and club stores is some 25% of food expenditures. Since poorer households spend more of their income on food, the effect (as a percentage of income) is higher toward the bottom of the income distribution (Furman 2005: 2-3). Hausman and Leibtag (2007: 1172, 1174) further argue that compensating variation from access to non-traditional retailers is higher at lower income levels, which would make the effect even more progressive (pgs. 8-9).

A brand new study demonstrates even more benefits provided by Walmart:

We estimate the effects that Walmart Supercenters have on food security using data from the 2001–2012 waves of the December Current Population Study Food Security Supplement (CPS-FSS). Narrow geographic identifiers available in the restricted version of these data enable us to compute the distance from each household’s census tract to the nearest Walmart Supercenter. Our outcomes are counts of the number of affirmative responses on the household and child-specific portions of the food insecurity questionnaire, along with binary variables for household food insecurity, household very low food security, child food insecurity, and child very low food security. We estimate instrumental variables (IV) models that leverage the predictable geographic expansion patterns of Walmart Supercenters outward from corporate headquarters. Specifically, we instrument for Walmart Supercenters with the interaction of distance from Bentonville, Arkansas (Walmart’s headquarters), with time. For both households in general and children specifically, the results show that a closer proximity to the nearest Walmart Supercenter leads to sizeable and statistically significant improvements in all food security measures except the indicator for very low food security. Subsample analyses reveal that the effects are especially large for low-income households and children, though they are also sizeable for middle-income children.

As journalist John Tierney asked, “How could any progressive with a conscience oppose an organization that confers such benefits?”

What Innovative Cultures Are Really Like

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Innovation is a must for both organizations and economies. At least, if one cares about the continued well-being of both. When it comes to creating an innovative organizational culture, several factors stand out. Gary P. Pisano at Harvard Business School lists some of the more popular ones:

  • Tolerance for failure: “Given that innovation involves the exploration of uncertain and unknown terrain, it is not surprising that a tolerance for failure is an important characteristic of innovative cultures. Some of the most highly touted innovators have had their share of failures.”
  • Willingness to experiment: “Organizations that embrace experimentation are comfortable with uncertainty and ambiguity. They do not pretend to know all the answers up front or to be able to analyze their way to insight. They experiment to learn rather than to produce an immediately marketable product or service.”
  • Psychological safety: “Psychological safety is an organizational climate in which individuals feel they can speak truthfully and openly about problems without fear of reprisal. Decades of research on this concept by Harvard Business School professor Amy Edmondson indicate that psychologically safe environments not only help organizations avoid catastrophic errors but also support learning and innovation. For instance, when Edmondson, health care expert Richard Bohmer, and I conducted research on the adoption of a novel minimally invasive surgical technology by cardiac surgical teams, we found that teams with nurses who felt safe speaking up about problems mastered the new technology faster. If people are afraid to criticize, openly challenge superiors’ views, debate the ideas of others, and raise counterperspectives, innovation can be crushed.”
  • Collaboration: “Well-functioning innovation systems need information, input, and significant integration of effort from a diverse array of contributors. People who work in a collaborative culture view seeking help from colleagues as natural, regardless of whether providing such help is within their colleagues’ formal job descriptions. They have a sense of collective responsibility.”
  • Flat hierarchy: “In culturally flat organizations, people are given wide latitude to take actions, make decisions, and voice their opinions. Deference is granted on the basis of competence, not title. Culturally flat organizations can typically respond more quickly to rapidly changing circumstances because decision making is decentralized and closer to the sources of relevant information. They tend to generate a richer diversity of ideas than hierarchical ones, because they tap the knowledge, expertise, and perspectives of a broader community of contributors.”

Much of this is appealing to the liberal mind. It touches on a number of Western democratic values: tolerance, openness to new experience, equality. One might even see echoes of social justice activism: “come as you are,” safe spaces, communalism, anti-establishment. However, Pisano couples these elements with others that may seem rather old school:

  • Intolerance for Incompetence: “[Innovative organizations] set exceptionally high performance standards for their people. They recruit the best talent they can. Exploring risky ideas that ultimately fail is fine, but mediocre technical skills, sloppy thinking, bad work habits, and poor management are not. People who don’t meet expectations are either let go or moved into roles that better fit their abilities…The truth is that a tolerance for failure requires having extremely competent people. Attempts to create novel technological or business models are fraught with uncertainty. You often don’t know what you don’t know, and you have to learn as you go. “Failures” under these circumstances provide valuable lessons about paths forward. But failure can also result from poorly thought-out designs, flawed analyses, lack of transparency, and bad management.”
  • Highly Disciplined: “A willingness to experiment…does not mean working like some third-rate abstract painter who randomly throws paint at a canvas. Without discipline, almost anything can be justified as an experiment. Discipline-oriented cultures select experiments carefully on the basis of their potential learning value, and they design them rigorously to yield as much information as possible relative to the costs. They establish clear criteria at the outset for deciding whether to move forward with, modify, or kill an idea. And they face the facts generated by experiments. This may mean admitting that an initial hypothesis was wrong and that a project that once seemed promising must be killed or significantly redirected. Being more disciplined about killing losing projects makes it less risky to try new things.”
  • Brutal Candidness: “We all love the freedom to speak our minds without fear—we all want to be heard—but psychological safety is a two-way street. If it is safe for me to criticize your ideas, it must also be safe for you to criticize mine—whether you’re higher or lower in the organization than I am. Unvarnished candor is critical to innovation because it is the means by which ideas evolve and improve. Having observed or participated in numerous R&D project team meetings, project review sessions, and board of directors meetings, I can attest that comfort with candor varies dramatically. In some organizations, people are very comfortable confronting one another about their ideas, methods, and results. Criticism is sharp. People are expected to be able to defend their proposals with data or logic…When it comes to innovation, the candid organization will outperform the nice one every time. The latter confuses politeness and niceness with respect. There is nothing inconsistent about being frank and respectful. In fact, I would argue that providing and accepting frank criticism is one of the hallmarks of respect. Accepting a devastating critique of your idea is possible only if you respect the opinion of the person providing that feedback.”
  • Individual Accountability: “[T]oo often, collaboration gets confused with consensus. And consensus is poison for rapid decision making and navigating the complex problems associated with transformational innovation. Ultimately, someone has to make a decision and be accountable for it. An accountability culture is one where individuals are expected to make decisions and own the consequences…Accountability and collaboration can be complementary, and accountability can drive collaboration. Consider an organization where you personally will be held accountable for specific decisions. There is no hiding. You own the decisions you make, for better or worse. The last thing you would do is shut yourself off from feedback or from enlisting the cooperation and collaboration of people inside and outside the organization who can help you.”
  • Strong Leadership: “Lack of hierarchy…does not mean lack of leadership. Paradoxically, flat organizations require stronger leadership than hierarchical ones. Flat organizations often devolve into chaos when leadership fails to set clear strategic priorities and directions. Amazon and Google are very flat organizations in which decision making and accountability are pushed down and employees at all levels enjoy a high degree of autonomy to pursue innovative ideas. Yet both companies have incredibly strong and visionary leaders who communicate goals and articulate key principles about how their respective organizations should operate.”

I remember making a point to my therapist–who uses a lot of Brene Brown’s work–that authenticity can be easily warped. “You are enough” is absolutely true if we are talking about the inherent dignity of people. However, when it used as license for “take me as I am” and “I don’t have to change,” it becomes a moral cancer. The same can be said of concepts like empathy or mindfulness. Similarly, focusing on only a few select traits of an innovative culture can be undermine the very innovation they are meant to promote.

Transformation is a balancing act. And a hard one at that.

What Drives Political Violence?

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This is disturbing, if not really all that surprising. From the Greater Good Science Center:

Earlier this year, political scientists Lilliana Mason and Nathan Kalmoe presented a paper at the American Political Science Association’s annual meeting, titled “Lethal Mass Partisanship.” With data from two different national surveys, they found that 24 percent of Republicans and 17 percent of Democrats believe that it is occasionally acceptable to send threatening messages to public officials. Fifteen percent of Republicans and 20 percent of Democrats agree that the country would be better if large numbers of opposing partisans in the public today “just died,” which the authors call a “shockingly brutal sentiment.” Nine percent of both Democrats and Republicans agree that violence would be acceptable if their opponents won the 2020 presidential election.

So drives political violence? First and foremost, aggression:

By far the biggest predictor of lethal partisanship across the board was having aggressiveness as a personality trait. This isn’t surprising, of course—aggression and violence go hand in hand. But a deeper look at aggression reveals how it fits together with other traits and shapes human behavior. Aggression all by itself is not good or bad; any of us can become aggressive when we face a direct threat. But aggression can go too far when inner and outer restraints are absent.

In neurological studies, more aggressive people tend to show less activation of the default mode brain network, which is associated with empathy and emotion regulation, which in turn helps suppress aggressive impulses. As psychologist Scott Barry Kaufman notes in Scientific American, aggressive people are more likely to retaliate when treated unfairly by others, which is not necessarily a bad thing (“although they tend to care much less about whether others are treated unfairly”).

However, aggression also shapes political outcomes. “Politicians who are more antagonistic get more media attention and are more often elected than more agreeable politicians,” he writes. “In the general population, antagonistic people are more likely to distrust politics in general, to believe in conspiracy theories, and to support secessionist movements.” In a series of experiments published in 2014, Kalmoe found “that exposure to mildly violent political metaphors such as ‘fighting for our future’ increased general support for political violence among people with aggressive personalities.”

Next, party identity:

After aggressiveness, Mason and Kalmoe found that “partisan identity strength”—how much being Democrat or Republican is part of who they are—is the most important factor in endorsing violence.

There are many studies—mostly from political science and sociology—showing that more Americans are using their political party affiliation as a source of meaning and social identity, with these identities linked to differences in “leisure activities, consumption, aesthetic taste, and personal morality,” as Daniel DellaPosta and colleagues write in their 2015 paper, “Why Do Liberals Drinks Lattes?

Worse, the Republican Party has become whiter in recent decades, while the Democratic Party has become more racially diverse—which could be intensifying party antagonism. A recent study of survey data by political scientist Diana Mutz found that nothing predicted support for Donald Trump more than a feeling of threatened status among white Christians—an insight ratified by several studies from Robb Willer at Stanford Universityand the Public Religion Research Institute.

…“All of the research to date was pointing in this direction,” adds Mason in an interview. “But we have a long tradition of treating partisanship like a largely benevolent force. It makes sense that as an identity grows stronger, and conflict intensifies, people will begin to approve of violence.”

Third, emotions like anger, contempt, and disgust:

While Mason and Kalmoe’s study gives us some sense of how common the tendency to accept political violence is—and some of the personality traits and belief structures that may be associated with it—a 2015 study points us in the direction of the emotions involved. In “The Role of Intergroup Emotions in Political Violence,” San Francisco State University researchers David Matsumoto and Hyisung C. Hwang and the University at Buffalo’s Mark G. Frank tried to figure out which emotions can drive violence by a group against an outgroup.

They examined the emotional tone of major political speeches that occurred prior to political events throughout history, looking at the emotions expressed in words, the judgments underlying the emotions, and the nonverbal expression of the emotions that could be seen in video form.

They also examined speeches made by “ideologically driven” leaders who despised opponent outgroups that resulted in violence, such as Hitler’s; and they studied those that did not, like Gandhi’s Salt March and pro-Tibet protests at the Beijing Olympics in 2008.

They found that speeches which preceded violent events tended to express more anger, contempt, and disgust (ANCODI)—but not fear, happiness, sadness, or surprise. These negative emotions tended to target specific “outgroups”—Jews, in the case of Hitler’s speeches.

Fourth, moralizing language:

Earlier this year, a team of five researchers searched the popular social media platform Twitter for tweets about the Baltimore protests. They wanted to investigate “moralizing” tweets—that is, tweets that viewed the protests as a moral issue rather than as a political disagreement. A moralizing tweet might, for example, refer to people as “disgusting” or “evil” or “traitorous.”

In fact, they did find a positive association between the number of moral tweets and the occurrence of violent protests (gauged with arrest data). “The days in which there were violent protests, we saw that there was a lot more moral language being used,” says study co-author and University of Southern California Ph.D. student Joe Hoover. “Which was consistent with the idea that morality and violence in these contexts might be linked.”

The team also ran an experiment using another prominent protest marred by violence: the far-right rally in Charlottesville, Virginia, in 2017. Respondents were asked to what extent they thought protesting against the far-right demonstrators was a moral issue; they were then asked how acceptable it was to use violence against these far-right activists. What they found is that people were more likely to embrace violence the more they saw it as a moral issue.

In an additional experiment, the participants were given the same prompts, but they were told either that the majority of Americans agreed with their view of the protest, or that few Americans agreed with their view. They found that “moralization predicted violence only when participants perceived that they shared their moralized attitudes with others.”

In other words, when it comes to violence, there’s validation and safety in numbers. The researchers dubbed this phenomenon “moral convergence,” when many people come together around a strong idea of what’s right and what’s wrong. The “risk of violent protest, in other words, may not be simply a function of moralization, but also the perception that others agree with one’s moral position, which can strongly be influenced by social media dynamics,” they write. 

Finally, group leadership:

There are many, many studies—starting with Stanley Milgram’s classic electric-shock experiments—which show that people are much more likely to inflict pain on others when an authority figure tells them to. When leaders engage in violent rhetoric, so do their followers; when they urge calm, people do calm down. Research has documented that words do have an impact on both beliefs and behaviors.

For example, a 2017 Polish study found “frequent and repetitive exposure to hate speech leads to desensitization to this form of verbal violence and subsequently to lower evaluations of the victims and greater distancing, thus increasing outgroup prejudice.” As part of the study, researchers surveyed participants on how frequently they encountered hate speech against refugees; they found that those who were more exposed to hateful words were more prejudiced against the group and more accepting of restrictive immigration policy.

Taken together, these studies suggest that our political leadership—everyone from pundits on cable news to the President of the United States—would do well to avoid promoting the political tribalism that leads people to strongly identify with one group and demonize the other.

In short, watch your aggression, avoid identity politics, keep your emotions in check, lay off the moral grandstanding, and quit putting so much stock into political leaders and pundits.

Economic Growth and Corruption

In my latest paper in Economic Affairs, I wrote,

Drawing on the EFW Index, Brennan (2016a)…points to a strong positive correlation between a country’s degree of economic freedom and its lack of public sector corruption. Granted, a lack of corruption could very well give rise to market reforms and increased economic freedom instead of the other way around. However, recent research on China’s anti-corruption reforms (Ding et al. 2017; Li et al. 2017) suggests that markets may actually pave the way for anti-corruption reforms (pg. 425).


Market liberalisation can also have indirect effects on war and violence. For example, Neudorfer and Theuerkauf (2014) explore the effects of public sector corruption on ethnic violence by analysing 81 to 121 countries between 1984 and 2007. They find that corruption has a robust positive effect…on the risk of ethnic civil war. When the evidence provided in the previous sections by Brennan (2016a) and Lin et al. (2017) is considered, we find that market liberalisation deters corruption and, consequently, ethnic violence (pg. 429).

Research suggests that economic growth may reduce corruption:

The traditional explanation for this relationship has been the theory articulated by Wolfenson above – corruption increases the cost and risk of business activity, thereby deterring investment and depressing growth that could have lifted citizens out of poverty (Mauro 1995, Wei 1999).

However, there is an alternative possibility that has received less attention among development practitioners and academics. The strong relationship between income and growth may result from exactly the opposite causal relationship – countries may be growing out of corruption (Tresiman 2002). Over time, economic growth reduces both the incentives for government officials to extract bribes and firms’ willingness to pay them. Some scholars of developed countries have discussed this possibility in terms of a ‘life cycle’ theory with corruption peaking at early stages of development and declining as countries industrialise (Huntington 1968, Theobald 1990, Ramirez 2013). However, there has been little work either testing for this empirical link from growth to corruption, or laying out the specific mechanisms that could generate the link.

The authors continue:

The key theoretical insight of our argument is that the share of bribes that officials will choose to extract as rents depends on a firm’s ability to move and set up business in a different location. Ask for too much, and firms that have the ability to do so, will simply pull up anchor and head to safer harbours. Because officials know this, they are likely to set a bribe amount that is just below the cost of moving.

Building on that insight, we show that as firms grow the cost of moving should decline relative to firm size. The fixed cost of moving becomes less expensive relative to revenue, and more and more firms have the opportunity to escape the bribe requests of officials in their locality. Corrupt officials faced with a sudden growth surge must lower their bribe rates, or face losing their key providers of employment and tax payers to competitors.

…The theory we propose has important policy implications. To the extent this theoretical mechanism is important, rather than focusing on politically difficult institutional changes to combat corruption, resources might be better spent on policies that facilitate capital mobility across subnational jurisdictions. Providing clear titles to business premises, for instance, enables entrepreneurs to sell and recoup the full market value of land. Such businesses are more mobile than renters or owners with insecure titles, who risk significant losses if they try to escape corruption by fleeing across the border.

Drawing on “an annual survey funded by USAID and administered by the Vietnamese Chamber of Commerce and Industry,” the researchers find “that the average bribe rate decreases as GDP per capita increases” and “that large firms actually pay lower bribe rates, which is what our theory predicts. Firms with higher revenues are more put out by a high bribe rate, since it increases the amount of bribes they must pay dramatically. To retain them then, officials must push their bribe rate lower.” 

Then, using “a census of firms conducted by Vietnam’s General Statistical Office (GSO) [to] calculate aggregate employment at the province-industry-year level,” the authors

show that exogenous industry-wide performance is indeed a strong predictor of a firm’s performance. A doubling of total employment in the industry is associated with a 1.6 percentage point reduction in the bribe rate, or about 42% of the mean level. Moreover, the effect is more pronounced for highly mobile firms. The magnitude of the effect of growth on bribe reductions is 17% larger for firms in possession of a Land Use Rights Certificate, which facilitates the sale of their business premises. Similarly, the effect is 20% greater for firms that already have branch operations in other provinces, and therefore possess knowledge and experience that could facilitate movement.

These effects survive a battery of robustness tests and alternative specifications, providing compelling evidence that growth can directly reduce corruption.

In short, economic growth can decrease corruption by undermining the power of officials to extract bribes. But this is likely part of a virtuous feedback loop. For example, a 2017 paper 

exploit[s] spatial variation in randomized anti-corruption audits related to government procurement contracts in Brazil to assess how corruption affects resource allocation, firm performance, and the local economy. After an anti-corruption crackdown, regions experience more entrepreneurship, improved access to finance, and higher levels of economic activity. Using firms involved in corrupt business with the municipality, we find that two channels explain these facts: allocation of resources to less efficient firms, and distortions in government dependent firms. The second channel dominates, as after the audits government dependent firms grow and reallocate resources within the organization (pg. 31). 

As I state in the beginning of my paper,

Of course, it is far easier to demonstrate correlation than causation, and while some studies do find markets playing a causal role in moral development, most simply establish a positive relationship. However, findings that ‘merely’ demonstrate positive correlations should be interpreted in light of the feedback loops: even if moral behaviours are foundational and give rise to market systems (instead of vice versa), market systems in turn reinforce these virtues by imbuing them with value. As Paul Zak (2011, p. 230) explains, ‘Markets are moral in two senses. Moral behavior is necessary for exchange in moderately regulated markets, for example, to reduce cheating without exorbitant transaction costs. In addition, market exchange itself can lead to greater expression of morals in nonmarket settings’ (pg. 423).

The Gender Wage Gap: Union Edition

Image result for union woman

Similar to previous research, a new working paper shows that the gender wage gap is driven largely by the amount of hours men and women choose to work. The authors draw on data from the Massachusetts Bay Transportation Authority (MBTA), explaining that the “bus and train operators are all represented by the same union, Carmen’s Local 589, and are all covered by the same bargaining agreement. The agreement specifies that seniority in one’s garage is the sole determinant of one’s work opportunities. Conditional on seniority, men and women face the same choice sets of schedules, routes, vacation days, and overtime hours, among other amenities” (pg. 2).

What do they find?

We show that a gender earnings gap can exist even in a controlled environment where work tasks are similar, wages are identical, and tenure dictates promotions. The gap of $0.89 in our setting, which is 60% of the earnings gap across the United States, can be explained entirely by the fact that, while having the same choice sets in the workplace, women and men make different choices. Women use the Family Medical Leave Act (FMLA) to take more unpaid time off than men and they work fewer overtime hours at 1.5 times the wage rate. At the root of these different choices is the fact that women value time and flexibility more than men. Men and women choose to work similar hours of overtime when it is scheduled a quarter in advance, but men work nearly twice as many overtime hours than women when they are scheduled the day before. Using W-4 filings to ascertain marital status and the presence of dependents, we show that women with dependents – especially single women – value time away from work more than men with dependents.

When selecting their work schedule for the following quarter, women try to avoid inconvenient days, like weekends, and shifts, like split-shifts, more than men. Prioritizing schedule related amenities over route quality-related amenities, women select routes with higher probabilities of assaults and collisions in order to avoid unfavorable schedules. When faced with having to work an unfavorable schedule, like a weekend, holiday, or split shift, women take more unpaid time off. Men also take more unpaid time off in those circumstances, but they more than make up for lost earnings with overtime. While constrained schedules lead to lower earnings for women, they result in higher earnings for men. In an effort to reduce absenteeism and overtime expenditures, the MBTA oversaw two policy changes: one that made it harder to take unpaid time off with FMLA and another that made it harder to be paid at the overtime rate. While the policy changes reduced the gender earnings gap from $0.89 to $0.94 and made it harder for operators to trade off regular hours for overtime, they also decreased women’swell-being by further constraining the work environment (pg. 34-35).

Texico: The Texas-Mexico Economy

Michael Cox and Richard Alm of SMU’s O’Neil Center have an essay in D Magazine based on the latest report from the Center. The two

imagine Texas and Mexico as one economy, connected by exports, imports, migration, cross-border business investments, transport infrastructure, tourism, and knowledge transfers. As a combined economy, Texas and Mexico churn out an annual GDP of more than $4 trillion, enough to rank as the world’s sixth-largest economy, just behind Germany and ahead of Russia.

We denote this sprawling and diverse economy by the portmanteau word: Texico. The name captures the reality that over the past quarter-century the Texas and Mexico economies have emerged as highly integrated, making an often-unsung contribution to Texas’ reign as America’s top-performing state economy.

The explain how trade has deeply integrated the two countries: 

An often-cited gauge of integration is trade—exports moving south, imports moving north. They totaled $188 billion last year, or more than 11 percent of gross state product, separating Texas from all other states in doing business with Mexico.

Texas companies are finding business opportunities in Mexico—among them, cosmetics-maker Mary Kay Inc. and telecommunications giant AT&T Inc., both based in Dallas-Fort Worth. At the same time, Mexican companies are heading northward and expanding their businesses, including Mission Foods in Irving and the movie theater chain Cinépolis in Addison.

The Texas and Mexico economies are more formidable combined rather than separate. Binational supply chains, for example, take advantage of low production costs in Mexico and highly skilled professional labor in Texas. The companies emerge more competitive in the global marketplace, able to sell their wares at a better price.

Automobile production comes to mind—for good reason. Plants in the Dallas-Fort Worth area are on the northern edge of the Texas-Mexico Automotive SuperCluster region, which includes close to 30 assembly plants and more than 230 parts suppliers in Texas and Mexico’s northern states.

Texas and Mexico have already profited a great deal from their binational economy, even though work began in earnest only recently. Mexico didn’t open its energy and telecom markets until just a few years ago. During negotiations that led to the North American Free Trade Agreement, Mexico clung to its monopolies in these industries. With its oil output falling, Mexico finally lifted its ban on foreign oil and gas companies three years ago. If all goes well, this should be a bonanza for Texas, with its deep roster of oilfield services and exploration companies. The telecom monopoly expired about the same time—and AT&T rushed in with its wireless service.

The annual report provides a few more interesting insights:

The report explains the slow convergence above: “Other factors like low levels of education shouldn’t be ignored, but the ongoing plague of corruption, cronyism and rising violence go a long way toward explaining why Mexican growth and income haven’t converged with the United States or kept pace with the likes of Chile, South Korea and China” (pg. 13). 

Cox and Alm conclude,

Texans are well aware of Mexico’s shortcomings, including corruption and drug-cartel violence. None of these problems will get any better by enacting policies that build barriers against Mexico and harm the Texas and Mexico economies. Perhaps Trump and Obrador will decide that the best course lies in expedient practicality—recognizing the fact that Texico has been working and building a large constituency. If these two leaders don’t make a mess of things, the businesses of Texas and Mexico can take it from there.