Category Archives: income distribution-wealth-poverty

People vs. Percentiles

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Russ Roberts writes,

This first study, from the Pew Charitable Trusts, conducted by Leonard Lopoo and Thomas DeLeire uses the Panel Study of Income Dynamics (PSID) and compares the family incomes of children to the income of their parents.⁴ Parents income is taken from a series of years in the 1960s. Children’s income is taken from a series of years in the early 2000s. As shown in Figure 1, 84% earned more than their parents, corrected for inflation. But 93% of the children in the poorest households, the bottom 20% surpassed their parents. Only 70% of those raised in the top quintile exceeded their parent’s income.

A lot of studies of income distribution track percentiles. That is, they will compare the bottom 20th percentile in, say, 1970, with the bottom 20th percentile today. Those are not the same people. Yet the press almost always reports such studies as if they were the same people. Even worse, many social scientists do this, also.

There is much more at the link.

Genes and cognitive ability

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Nicholas W. Papageorge and Kevin Thom write,

we utilize a polygenic score (a weighted sum of individual genetic markers) constructed with the results from Okbay et al. (2016) to predict educational attainment. The markers most heavily weighted in this index are implicated in neuronal development and other biological processes that affect brain tissue. We interpret the polygenic score as a measure of one type of endowed ability.

Perhaps a newer version of the paper is here.

The paper finds that gene-environment interaction matters. But I think it is important that we now have a genetic score that can serve as a proxy for IQ. Also, this genetic score affects economic outcomes even when educational attainment is controlled for.

By the way, Robert Plomin’s forthcoming book is on my radar. This review points out the obvious, which is that the book will not be well received.

And also, Tyler Cowen points to this paper, which says that it is liberals who attribute outcomes more to genetic factors.

I can only imagine genetic effects being powerful if you hold constant the cultural context. Suppose it were possible to create reliable polygenic scores for the Big Five personality traits, plus cognitive ability. I can imagine that these scores would be useful in predicting outcomes among a group of American teenagers. But if you were to take a random sample of teenagers around the world and use nothing but these scores to predict long-term outcomes, I cannot imagine that this would work. To carry the thought experiment even further, think in terms of plopping people with identical polygenic scores into different centuries.

Adult marshmallow-test winners do better

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William H. Hampton1\, Nima Asadi and Ingrid R. Olson write.

Participants engaged in a delay discounting task adapted from O’Brien et al. (2011). In the task, participants were asked to make choices between a smaller sum of money offered now versus a larger sum of money (always $1,000) offered at five different delays.

They then use this variable along with other variables to predict the person’s income.

The results of each model were quite consistent, with occupation and education paramount in each case. On average, the next most important factors were zip code group and gender. While zip code group was highly associated with income, it is worth noting that our data do not adjudicate directionality. Logically, a person’s income is more likely a determinant of where they live than vice versa. Nonetheless, zip codes are a useful proxy for socioeconomic status, which is also related to income (Winkleby et al., 1992). As our zip codes were binned by average income, the association between zip code and income is not surprising, but does suggest that the individuals in our sample had incomes roughly representative of the incomes from their respective zip code group. Regarding gender, we found that males earned more money than females, a result consistent with a corpus of research on the gender wage gap (Nadler et al., 2016). The fifth most important variable was delay discounting, a factor closely related, but distinct from impulsivity. Although previous research had indicated that discounting was related to income (Green et al., 1996), it was unclear to what extent, relative to other factors, this variable mattered. Interestingly, delay discounting was more predictive than age, race, ethnicity, and height

Pointer from Tyler Cowen.

Oy. It would be nice to be able to cite their comment that “delay discounting was more predictive than age, race, ethnicity, and height.” But the flaws I perceive in the study are just too fatal to allow me to do that.

1. Most of the variables that they use to “predict” income are not plausibly exogenous to income. For that matter, it is possible that your level of income helps determine your willingness to delay receiving money, so even their key delay-discounting variable is plausibly endogenous.

2. When you compare the strength of different predictors (hardly ever a valid exercise), measurement error is everything. A variable that is measured unambiguously will do much better than a variable that is measured subject to errors, even if the latter variable has more influence in reality. So gender has the advantage of being unambiguous*, while self-reported ethnicity can be ambiguous.

*all right, some people insist that gender is ambiguous, but I don’t think those people find their way to this blog.

My case for the UBI

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This essay elaborates on the issue of implicit tax rates that Greg Mankiw highlighted.

I am starting to get annoyed with the left-wing bias at Medium. It is one thing for the readers of the site to lean left. Fine. But my articles seem to get much, much less play than a lot of essays that offer nothing but left-wing drivel. And hardly anyone seems to come out of the left-wing echo chamber to read what I write. I get the sense that I am mostly being presented to the (few) people who already are sympathetic. It’s somewhat demotivating.

Greg Mankiw’s case for the UBI

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He writes,

To put it another way, the effective marginal tax rate when a person moves from the bottom to the middle quintile is . . . 76 percent.

The blog post explains how he arrives at this. He is comparing incomes before taxes and transfers with incomes after taxes and transfers. The high implicit tax rate comes from the loss of eligibility for food stamps, Medicaid, and other benefits.

If you replaced all current low-income subsidies with a Universal Basic Income, you could come up with a more rational tax rate for people. Even if the current system doesn’t discourage work effort (although I suspect that it does), just the way that it retards upward mobility strikes me as wrong.

Thinking about privilege

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A friend’s son has a job orienting college students on the subject of privilege. The highlighted sources of privilege are primarily race and sexual orientation. Parental wealth also may get throw in.

The sources of privilege that are not mentioned, as far as I can tell, include:

–being tall
–having attractive features (or at least not being extremely unattractive)
–being naturally outgoing (extroverted)
–not having mental disorders, such as autism, depression, or schizophrenia
–not having debilitating physical ailments or physical handicaps
–growing up with your biological father (particularly if you are male). See Autor and Wasserman.
–having artistic gifts

Like race or sexual orientation, these characteristics are generally given to a person at birth and during childhood. On average, and other things equal, someone with one of these characteristics will wind up higher on the social scale than someone without them. I would bet that some of them have stronger impacts on average outcomes than race or sexual orientation. So to me, these characteristics look like privilege.

Is there a non-politically-motivated justification for only looking at race, sexual orientation, and economic class as sources of privilege?

Talent effects and inequality

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My latest essay concludes,

In many industries nowadays, small teams of talented individuals can out-compete larger collections of mass workers. Elite skills, reputations, and connections can create barriers to entry that produce high returns. In some important fields, the stars get the best jobs, which in turn enables them to enhance their know-how and their reputations. And the most talented people in one field are likely to work in firms with the most talented people in other fields, creating synergies that increase their rewards even further.

Family breakdown and malaise

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Mary Eberstadt writes,

Traditionalists and other contrarians have been right to argue that the revolution would lead to rising trouble between the sexes and a decline in respect for women — just as James Q. Wilson remains right that family, and lack of family, have replaced money itself as the nation’s most accurate measures of real wealth and poverty.

She attempts to tie nearly every contemporary social problem to the sexual revolution and family breakdown.

Student debt and inequality

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From a reader:

Is the massive student debt impairing US social mobility? If someone takes out large student debt to get a sociology or history degree and then gets a job that makes it difficult to pay off the debt, doesn’t this make it hard to climb the social ladder? On the other hand if your parents fund your schooling, you’re more able stay in the upper middle class or climb higher.

You can inherit from your parents: genes; social norms (coming from them and also from the peers with which they surround you); wealth. School funding is a fairly significant component of inherited wealth nowadays, but it is not all of it. Moreover, I suspect that the other two types of inheritance matter more.

But suppose you do not have wealthy parents. Is going to college your ticket to upward mobility? My guess is that for some it is, but for many it is not. And for those who take on a lot of student debt, the net effect may be adverse.

For several years, I have believed that the higher education system impairs economic mobility. It certainly serves to segregate affluent young adults from non-affluent young adults.

Interesting take on wealth distribution

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From Matthew Stewart.

Let’s suppose that you start off right in the middle of the American wealth distribution. How high would you have to jump to make it into the 9.9 percent? In financial terms, the measurement is easy and the trend is unmistakable. In 1963, you would have needed to multiply your wealth six times. By 2016, you would have needed to leap twice as high—increasing your wealth 12-fold—to scrape into our group. If you boldly aspired to reach the middle of our group rather than its lower edge, you’d have needed to multiply your wealth by a factor of 25. On this measure, the 2010s look much like the 1920s.

He arrives at the “9.9 percent” by taking the top 10 percent and lopping off the top 0.1 percent. I think most economists would like to see an age breakdown. That is, take the 9.9 percent from among, say those aged 45-55.

Stewart talks about heritable wealth, and he rightly looks at elite colleges and universities as part of the process. Journalists who write about inequality generally do a lousy job, but I think this piece actually gets things more right than wrong.