Edward Conard

Top Ten New York Times Bestselling Author

  • “There are an amazing number of good ideas and interesting points made in Unintended Consequences. The thinking underlying it, and the obvious depth of understanding of the author, are very impressive.” - Steven Levitt, coauthor of Freakonomics; 2004 John Bates Clark Medal
  • “A full-throated defense of economic dynamism.” - The Wall Street Journal
  • “…a very valuable contribution.” - Larry Summers, former Secretary of the Treasury and director of the National Economic Council, president emeritus, Harvard University
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “Unintended Consequences is full of substance, it is one of the must-read books of the year, and once I finish it I will be giving it a second read through right away.” - Tyler Cowen, Professor, George Mason University
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
Upside of Inequality Oxford Unintended Consequences

Macro Roundup


Monday, June 21, 2021

AI Summary. Boys raised in the lowest-income fifth of families show worse adult outcomes than girls from similar backgrounds: 14% earn a college degree by 25, they are less likely to be employed at 30, 10x more likely to be incarcerated, and 29% are married by 32 versus 33% of girls.

Sarah Nzau Brookings Institution
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Boys raised in low-income families face significantly worse adult outcomes compared to their female counterparts. Data from Opportunity Insights reveals that only 14% of boys from the bottom income quintile attain a college degree by age 25, compared to higher rates for girls.

Do boys from low-income families fare worse as adults than girls?

Core argument: Only 14% of boys from the bottom income quintile earn a college degree by age 25, a lower rate than girls from the same backgrounds, according to Opportunity Insights data.

Boys raised in low-income families face significantly worse adult outcomes compared to their female counterparts, highlighting a critical intersection of class and gender inequalities. Data from Opportunity Insights reveals that only 14% of boys from the bottom income quintile attain a college degree by age 25, compared to higher rates for girls. Employment rates at age 30 also show a reverse gender gap, with boys from low-income backgrounds less likely to be employed than girls. Incarceration rates further underscore this disparity, as boys from the bottom quintile are 10 times more likely to be incarcerated than their female peers. Additionally, only 29% of these boys are married by age 32, compared to 33% of girls. The persistence of these trends suggests that poverty disproportionately impacts boys, potentially perpetuating a cycle of disadvantage across generations. Addressing these disparities requires targeted policy interventions that consider both class and gender dimensions.

Takeaways by Macro Roundup® AI

  1. Only 14% of boys from the bottom income quintile earn a college degree by age 25, a lower rate than girls from the same backgrounds, according to Opportunity Insights data.
  2. Boys raised in the bottom income quintile are 10 times more likely to be incarcerated than their female peers, and are less likely to be employed at age 30, a reverse gender gap.
  3. Among those raised in low-income families, 29% of men are married by age 32, compared with 33% of women.

Richard Reeves and Sarah Nzau, "Poverty hurts the boys the most: Inequality at the intersection of class and gender," Brookings Institution, June 14, 2021, https://www.brookings.edu/research/poverty-hurts-the-boys-the-most-inequality-at-the-intersection-of-class-and-gender/

Poverty hurts the boys the most: Inequality at the intersection of class and gender

One of the cognitive curses of the human mind is the tendency to chop everything into two: black and white, rich and poor, men and women, North and South, and so on. By instinct, we tend to lump people together into clear and distinct categories, preferably just two. The world seems simpler that way.

But of course, the world is not simple. People are not sorted into neat boxes. One unfortunate consequence of this binary worldview is what public health expert and “factfulness” advocate Hans Rosling calls the “gap instinct…to divide all kinds of things into two distinct and often conflicting groups with an imagined gap in-between (e.g., rich vs poor countries).”

In the real world, the distributions of two different groups on most measures almost always overlap, rather than having a clear gap between them. So, while the median man is 5 inches taller than the median woman, not all men are taller than all women. Therefore, it is often a mistake to look at one kind of inequality in isolation from another. For example, we cannot look at gender gaps in isolation from inequalities by race and class.

This is the central insight offered by the intersectionality framework pioneered by Kimberlé Crenshaw. The position of individuals in society should be examined considering a range of intersecting identities and distributions. As we wrote in a previous analysis of the unique disadvantages faced by Black men, breaking the cycle of their intergenerational disadvantage requires a deeper understanding of the gendering of their race—and the racialization of their gender.

POOR BOYS = STRUGGLING MEN

In this paper we focus on the intersection of class and gender, and how being raised in families on different rungs of the income ladder influences the outcomes of girls and boys. Our principal finding is that boys raised in low-income families do worse, in terms of adult outcomes, than girls raised in low-income families. Most strikingly, boys raised in families in the bottom fifth of the income distribution are less likely than girls either to be employed or to move up the income ladder once they become adults.

With bottom quintile boys struggling, the danger is of knock-on effects for the next generation. As Autor and Melanie Wasserman warn in another paper, Wayward Sons: “A vicious cycle may ensue, with the poor economic prospects of less-educated males creating differentially large disadvantages for their sons, thus potentially reinforcing the development of the gender gap in the next generation.”

It is particularly important to examine the intersection of class and gender inequalities because the distributions have been moving in opposite directions in recent decades. Gender inequality has been reducing while income inequality has been widening. It hardly needs adding that of course there remain many areas where much more progress is required to close gaps between men and women—not least in terms of political representation, where I have called for the introduction of gender quotas in line with many other nations.

But as The Economist magazine correctly points out, “the fact that the highest rungs have male feet all over them is scant comfort for the men at the bottom.” This is one reason why we have launched a new project on Boys and Men here at Brookings, in order to examine the challenges facing many boys and men, in the context of progress toward gender equality, and potential policies and norms to promote greater male flourishing and agency. We are paying particular attention to Black boys and men, and boys and men from disadvantaged backgrounds.

Boys seem particularly most strongly influenced by the family environment, as well as by school quality or neighborhood poverty. These findings are consistent with research showing the particularly sharp impact of poverty and disadvantage for boys, which also has implications for race equity—since Black boys are much more likely to be raised in lower income or socially disadvantaged households.

BOTTOM QUINTILE BOYS: GENDER GAPS DIFFER AT VARIOUS POINTS OF THE PARENT INCOME DISTRIBUTION

Here we draw on data from Opportunity Insights to examine gender gaps in early adulthood for children raised by parents on different rungs of the household income ladder, specifically rates of:

College degree attainment (BA) by age 25
Employment at age 30
Incarceration at age 30
Marriage at age 32
Upward mobility from bottom quintile by the mid-thirties age range.

For clarity of presentation, we show these outcomes by gender for those from families in the bottom, middle and top quintiles. (The trends are the same for the missing two quintiles, and the full data is available on the Opportunity Insights page). On all five measures, girls from the bottom quintile outperform boys from the bottom quintile. In other words, class and gender intersect. Policymakers should take note.

Boys less likely to be BAs, especially if raised poor

It is well known that college attendance and completion is much higher among women than men, and at least in terms of enrollment the gap. College enrollment for male students in fall 2020 dropped by 5.1%, according to National Student Clearinghouse figures, several times more than the fall for female students (0.7%). There is also a very steep class gradient in college completion. Figure 1 highlight both of these inequalities, showing the share of those raised in the bottom, middle and top income quintiles get a four-year college degree by the age of 25.

Poverty hurts the boys the most: Inequality at the intersection of class and gender: Extended Excerpt Image 1


So there is a both a class gap and a gender gap. But it is noteworthy that the gender gap is biggest at the bottom. Only 14% of boys from low-income families (bottom quintile) will get a BA. The main challenge is clearly to reduce the yawning class gap in higher education, not least given the relationship between a lower level of education and lower employment rates and poorer health. But the particularly poor outcomes for the most disadvantaged males may warrant particular attention.

Boys raised poor less likely than girls to be in paid work as adults

While girls and women are now significantly outperforming boys and men at every stage of the education system, men are still generally more likely than women to be in paid employment as adults. With one exception: boys from the bottom quintile. Figure 2 shows employment rates at age 30 by family income background and gender:

Poverty hurts the boys the most: Inequality at the intersection of class and gender: Extended Excerpt Image 2


Although the reverse gender gap in employment rates is small, it is nonetheless striking given the size of the gaps in the other direction for the other quintiles. Again, the class gaps dwarf the gender gaps—with men and women raised in the middle and top income quintiles having much higher rates of employment (interestingly slightly lower at the top than in the middle, especially among men). But again, the intersection of class and gender is an important part of the story. The overall picture of higher employment rates for men does not apply to those raised at the bottom of the income ladder.

Incarceration is a poor boy story

There has been a substantial rise in the male incarceration rate during the last three decades—especially among Black men—and almost no increase in incarceration rates among women. There is a large gender gap in incarceration rates. But again, as well as race and gender, it is important to look at class. Incarceration is most common among boys raised in low-income families. Figure 3 shows that boys with parents in the bottom quintile of the parent household income distribution are 10 times more likely to be incarcerated than low-income girls, but 22 times as likely to be incarcerated as boys with parents in the top quintile. (Note that these figures are for the proportion of the cohort in prison on a specific day - April 1st, 2010, when they were between 27 and 32 years of age). There is in fact essentially no gender gap for the top quintile, since the incarceration rate is close to zero in any case:

Poverty hurts the boys the most: Inequality at the intersection of class and gender: Extended Excerpt Image 3


The marriage gradient by class, and by gender

There is a class gradient in marriage rates, with children from different backgrounds having different odds of ending up married as adults. Children from low-income families are less likely to be married than those raised in high-income families. However, male children from low-income families are the least likely of all to be married at age 32, including by comparison to girls raised in low-income families. Figure 4 shows that the marriage rate for boys raised in families in the bottom quintile is 29%, compared to 33% for girls raised in the same quintile.

Poverty hurts the boys the most: Inequality at the intersection of class and gender: Extended Excerpt Image 4


Again, the class gradient is the big story here, and in fact the gender gap in marriage rates is similar at different background income levels. But again, the group with the lowest rates of all are bottom quintile boys.

Boys raised poor less likely than girls to escape poverty

Reducing intergenerational poverty is a key policy goal, that has animated much of our own work here in the Center on Children and Families. The question of who moves up and down the income ladder is an important one for judging the fairness and openness of our society. Again, using Opportunity Insights data, in Figure 5 we show the proportion of those raised in families in the three income quintiles (bottom, middle, and top) and who end up in the bottom quintile as adults. Importantly the measure here is individual income, not household income. Men raised in the bottom quintile (29%) are slightly more likely to remain stuck in that quintile as adults than women (26%). Less Horatio Alger, more Harriet Alger:

Tries to run, but he don't get far…. Using Chetty’s data Richard Reeves and Sarah Nzau find that growing up in poverty has a disproportionate impact on men versus women in terms of college attainment, employment, mobility and marriage and incarceration rates"... Our principal finding is that boys raised in low-income families do worse, in terms of adult outcomes, than girls raised in low-income families. Most strikingly, boys raised in families in the bottom fifth of the income distribution are less likely than girls either to be employed or to move up the income ladder once they become adults..."

Conclusions, "…Many American policy analysts point to Denmark as a model welfare state with low levels of income inequality and high levels of income mobility across generations. It has in place many social policies now advocated for adoption in the U.S. Despite generous Danish social policies, family influence on important child outcomes in Denmark is about as strong as it is in the United States.More advantaged families are better able to access, utilize, and influence universally available programs. Purposive sorting by levels of family advantage create neighborhood effects. Powerful forces not easily mitigated by Danish-style welfare state programs operate in both countries…."

Note the increased spending had no impact on mobility btw cohorts in Denmark“….Fig. 4b shows cognitive test score ranks for the all males born in 1958 and 1988 in Denmark by their parents’ income percentiles,22 along with cognitive test score ranks across parents’ income percentiles for children from the CNLSY data. The figure illustrates two points: First, no striking differences appear when comparing the association between children’s test scores and parents’ income percentiles in Denmark and the U.S. Second, the association between children’s cognitive test scores and parents’ income is strikingly similar for Danish cohorts born 30 years apart. Although the 1988 cohort is born after the rapid welfare state expansion previously described and the 1958 cohort is born just before the expansion took off, the associations between test scores and parents’ resources are practically identical. Family influence retains its tight grip….”

First, “…. Intergenerational educational mobility is about the same in both countries for the most recent cohorts. Transmission of skills across generations is equally strong in both countries, despite stark differences in income inequality and offered public services….”
Second“….The traditional literature on the intergenerational transmission of economic status compares snapshots of lifetime incomes of parents and children. This approach gives only a limited picture of the transmission of lifetime well-being across generations. Using Danish register data on lifecycle income, we find that intergenerational elasticities of income (IGE) of lifetime well-being are much higher than those estimated using incomes measured over a small window of ages. Accounting for uncertainty and credit market restrictions increases estimated dependence across generations. Well-being is much more tightly linked across generations in Denmark than conventional snapshot measures of lifetime income indicate….”

Third, “….We expand the analysis of family influence beyond the traditional analysis of IGEs of income to include choices of neighborhood, peers, and schools as parental investments in their children. We present compelling evidence of purposive sorting by parents in making neighborhood choices. Our evidence calls into question the assumptions underlying the recent neighborhood influence literature - that timing of residential choice is random with respect to the lifetime gains for children….”
The key evidence, "...Despite the generosity of the Danish welfare state and equality in access for all citizens, substantial inequality of child outcomes remains across social and economic classes. Figure 1 documents these gaps and compares them to their U.S. counterparts. Children of college-educated women do substantially better than children of secondary school dropouts on many dimensions in both countries...."

Their core findings:

Despite interventionist Danish social policy family influence on child outcomes in Denmark is ~ as strong as it is in the United States. Inequality of child outcomes remains across economic classes, for example children of college educated women do better in both Demark and the US. Their bottomline, "...However,if equal Danish provision of services does not eliminate inequality in many important life outcomes, the origins of inequality and social immobility lie elsewhere..."

In terms of mobility by test scores, I don’t think I have that for the US, but let me confirm that, this new Heckman implicitly does in demonstrates the limited utility of social policy to change mobility outcomes for children by their parents education attainment (which on some level is a proxy for skill).

The numbers are from his "Race and Economic Opportunity in the United States: An Intergenerational Perspective (Data Set)"

30% of poor white boys ended up as poor adults. 48% of black boys did.

23% of poor white boys ended up as lower middle class adults. 28% of black boys did.

21% of poor white boys ended up as middle class adults. 15% of black boys did.

17% of poor white boys ended up as upper middle class adults,, 6% of black boys did.

9% of poor white boys ended up as rich adults, 2% of black boys did.

Ed Comment 1/2:I don’t find the differences between boys and girls that compelling. Do Reeves or chetty show the outcomes for poor white boys vs poor black boys? Does anyone show outcomes by test scores? In the case of mobility, what we care about is the upward mobility of poor kids with high scores. Although we would suspect that poor parent with high scores pass negative hidden variables to their children. They are likely poor for reasons.

Steve Comment: Yes Chetty’s data does show outcomes for poor white boys versus poor black boys (this is all fornative born mothers,using household income)

Ed Comment 2/2:I'm not surprised by the chetty findings. We saw in the appendix to that paper we used to plot wages against test scores, that poor black test scores are much lower than poor white scores despite the 2 groups earning similar wages. For the same reason, I'm surprised Denmark's outcomes of the poorest aren't less correlated than the US given the blended test scores of America's poor are surely lower than Denmark's. As you recall, in my second book I compared poor whites to poor Scandinavians to show there was no difference. There was a difference between poor Scandinavians and poor black americans.

Tuesday, June 22, 2021

AI Summary. Research finds that measures of competitiveness are correlated with higher education levels, prestigious college majors, and better occupational positions, with competitive individuals 13% more likely to earn higher incomes and 50% more likely to hold high-level managerial roles. Gender differences in competitiveness account for 5-10% of gender gaps in education and labor market outcomes.

Thomas Buser National Bureau of Economic Research
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Research by @ThomasBuser highlights competitiveness as a key predictor of educational & labor market outcomes, strongly correlated with higher education levels, prestigious college majors & superior occupational positions.

Does competitiveness predict education and labor market outcomes?

Core argument: Individuals exhibiting competitive traits are 13% more likely to earn higher incomes and 50% more likely to hold high-level managerial roles.

Recent research highlights competitiveness as a key predictor of educational and labor market outcomes. Both incentivized and unincentivized measures of competitiveness are strongly correlated with higher education levels, prestigious college majors, and superior occupational positions. Individuals who exhibit competitive traits are 13% more likely to earn higher incomes and 50% more likely to hold high-level managerial roles. Gender differences in competitiveness account for 5-10% of observed disparities in education and labor market outcomes, with competitiveness explaining up to 25% of the gender gap when combined with other traits. The study underscores the importance of competitiveness as a distinct trait, separate from risk preferences and confidence, in predicting economic success. This suggests that incorporating competitiveness into large-scale surveys could provide valuable insights for policymakers and economists.

Takeaways by Macro Roundup® AI

  1. Individuals exhibiting competitive traits are 13% more likely to earn higher incomes and 50% more likely to hold high-level managerial roles.
  2. Gender differences in competitiveness account for 5–10% of observed disparities in education and labor market outcomes, rising to as much as 25% of the gender gap when combined with other traits.
  3. Both incentivized and unincentivized measures of competitiveness correlate strongly with higher education levels, prestigious college majors, and superior occupational positions, and competitiveness stands apart from risk preferences and confidence in predicting economic success.

Research attempts to gauge the impact of competitiveness as a character trait, paper finds it is predictive of educational and labor market outcomes though they note the relationships"... are (conditional) associations and cannot be interpreted causally..."

Their takeaway, “…In this paper we introduce such measures of competitiveness. The first is incentivized and is an online adaptation of the original Niederle-Vesterlund measure. The second is a single and general unincentivized survey question which can be quickly elicited in any setting. The two measures arestrongly correlated at the individual level and both measures are strong and consistent predictors of completed level of education, field of study in college, occupation and income. The predictive power of the unincentivized measure for these outcomes is robust to controlling for other traits, including risk seeking, confidence and the big five personality traits. For most outcomes, the predictive power of competitiveness exceeds that of the other traitsWe also contribute to the literature on gender differences in the labor market. We find that gender differences in competitiveness can explain 5-10% of the observed gender differences in education and labor market outcomes and that gender differences in competitiveness, risk seeking, confidence and the big five personality traits combined can explain up to 25% of gender differences. Our results are also relevant to the ongoing discussion in the experimental economics literature on whether gender differences in willingness to compete in the lab are due to individual differences in preferences for competition or rather due to differences in beliefs and risk preferences. We show that competitiveness and risk attitudes predict a separate set of outcomes. Risk attitudes are only weakly related to career outcomes. On the other hand, risk attitudes, but not competitiveness, predict choices that are intrinsically risky but not competitive (investing in stock, self-employment and smoking..”

Thomas Buser, Muriel Niederle and Hessel Oosterbeek, "Can Competitiveness predict Education and Labor Market Outcomes? Evidence from Incentivized Choice and Survey Measures," National Bureau Of Economic Research, June 2021, https://www.nber.org/papers/w28916

Gender Differences“…While 34 percent of working-age men choose to compete in the experiment, only 22 percent of working-age women do so (p=0.000; chi-squared test).24 65 percent of men and 47 of women rate their competitiveness as at or above the median (p=0.000).25 In the right-most panel, we show a histogram of competitiveness levels by gender which reveals large gender differences in the tails. 11 percent of men but only 5 percent of women rate themselves as extremely competitive (9 or 10 on a 0-10 scale).On the other hand, 9 percent of women but only 5 percent of men rate their competitiveness as very low(0-2)...In Figure 9, we ask whether our unincentivized measure of competitiveness, as well as the other trait measures, can explain a significant part of these gender gaps. To do so, we estimate the percentage reduction in the gender gap upon controlling for each of the traits separately and jointly.26 Controlling for the unincentivized competitiveness measure reduces the gender gap in income by 4.3 percent. Competitiveness is among the traits which explain most of the gender gap in income, together with stability (5.3 percent) and general confidence (3.6 percent). In the rightmost graph in each panel, we estimate the proportion of the gender gap that is explained by all traits together. We estimate that around 12 percent of the gender gap in income in our sample can be explained by the psychological traits we consider. Following previous results that the potential of competitiveness for explaining differences in educational career choices is highest at the top of the ability distribution (Buser, Peter, and Wolter, 2018), we repeat this exercise for collegeeducated individuals. Here, competitiveness explains 7.6 percent of the gender gap, while stability explains 9.9 percent and confidence 6.2 percent. All traits jointly explain roughly 18 percent of the gender difference in income for college-educated individuals. Competitiveness also has the most explanatory power for the gender gap in holding a high-level professional position conditional on education level (8.7 percent) followed by stability (7.3 percent), risk seeking (6.3 percent), confidence (5.9 percent), and intellectual openness (5.8 percent). All psychological traits jointly explain around 25 percent of the gender gap. For those who graduated from college, competitiveness (6.1 percent), agreeableness (7.5 percent) and risk seeking (3.4 percent) are the only significant explanatory factors for the gender gap in major choice. All traits jointly explain 18 percent of the gender gap..."

Impact on risk taking, “…. Our results indicate that competitiveness, risk and confidence are three separate traits which predict outcomes independently or even predict different outcomes. For example, Figure 5 shows that our measure of competitiveness significantly predicts education and labor market variables even when controlling for risk preferences, confidence, self-esteem and personality. Neither the effects of risk preferences nor of confidence are consistently robust to controlling for the other traits…. In Figure 7 shows the difference in outcomes between individuals in the top 30% and individuals in the bottom 30% on each trait, controlling for age and gender. We replicate the Dohmen et al. (2011) result that risk seeking is a significant predictor of all four outcomes. As expected, competitiveness does not predict investing in stocks, being self-employed or smoking. On the other hand, competitiveness is the strongest predictor of practicing sports. This analysis further underlines that competitiveness and risk attitudes are both relevant individual traits which predict different economically important outcomes and should therefore be accounted for separately…”

Can Competitiveness predict Education and Labor Market Outcomes? Evidence from Incentivized Choice and Survey Measures: Extended Excerpt Image 1


Survey measures, “…In Figure 4, we show the relationship between unincentivized competitiveness and outcomes, repeating the analysis in Figure 3.To make the graphs comparable, we dichotomize our 11- point measure by splitting the sample into people whose competitiveness is below or above the median.20 The unincentivized survey measure is strongly related to income. For both men and women, individuals who are above-median competitive are substantially more likely to be in the highest quintile (86 percent more likely for men and 49 percent for women) and less likely to be in the lowest quintile (28 percent for men and 28 percent for women) than individuals who are below-median competitive. Looking at occupational level, we again find that the results from the incentivized measure replicate quite closely. Individuals who are above-median competitive are around three times as likely to work in a high supervisory position and 60 percent more likely to work in a high academic or independent position. They are also 70 percent more likely to work in an intermediary supervisory position. Looking at education, above-median competitive individuals are 70 percent more likely to have graduated from a university and 26 percent more likely to have graduated from a university of applied sciences. The unincentivized measure is also related to the choice of college major. As with the incentivized measure, more competitive individuals tend to have graduated from more lucrative majors. Nevertheless, the picture looks slightly different compared to the incentivized choice. When using the incentivized measure, competitive people were much more likely to have chosen medicine or STEM (and less likely to have chosen nursing or humanities and art). Using the unincentivized measure, we again find a much higher likelihood of having a degree in medicine and a much lower likelihood of having a degree in nursing or humanities and art, but we now also find that individuals who judge themselves to be more competitive are about twice as likely to have a degree in economics and business or law (on the other hand, they are only slightly more likely to have a STEM degree). Overall, the graphs indicate that the unincentivized survey measure is related to education and labor market outcomes in ways that are very similar to the patterns observed for the incentivized measure….”

Incentivized measure, “…Figure 3 shows how respondents who chose the tournament option and respondents who chose the piece-rate option are distributed across different levels of each of the four education and labor market variables. In the two upper-most panels, we divide the sample into income quintiles. Because the income distributions of men and women are very different, we do this separately by gender. For each gender, the income distributions of individuals who chose to compete and individuals who chose not to compete differ strongly. Individuals who compete are more than twice as likely to be in the highest quintile and much less likely to be in lowest two quintiles…”

The evidence:“…Our results confirm that both the incentivized and the unincentivized measures are strong predictors of the same education and labor market outcomes. Conditional on performance in the task, gender, age, education level, risk preferences, confidence and the big five personality traits, individuals who compete in the experiment earn roughly 13 percent more, and are around 50 percent more likely to hold a high-level managerial or professional position. Individuals who compete are also 13 percentage points more likely to go to college and, conditional on going to college, choose more prestigious study majors that lead to higher salaries. We find the same effects for people who score themselves higher on competitiveness in our survey question. Comparing the predictive power of different traits, competitiveness is consistently among the strongest predictors. The fact that the incentivized and unincentivized measures predict the same outcomes justifies the use of the unincentivized survey question as a valid measure of competitiveness. This makes it possible to elicit competitiveness in large-scale representative national or cross-country surveys and survey panels in the future….”

Core results: First, “…willingness to compete as measure by an incentivized choice experimentstrongly predicts earnings and occupation conditional on education level, as well as education level and college major choice in a representative sample….”Second, “… unincentivized survey question predicts the same outcomes in the same sample with comparative predictive power….”Third, “…our survey measure of competitiveness predicts these outcomes over and above other unincentivized trait measures that the education economics literature has typically focused on, including risk seeking, confidence and the big 5 personality traits, indicating that competitiveness is a separate influential trait that is not captured by these other, more traditionally used traits…”