How much does effort contribute to the measures of inequality that we gather when we look at the data?
That’s the central question explored in this episode. Host Russ Roberts welcomed Ed Leamer to discuss a recent paper in which he investigated the role of effort in measuring inequality and the transformation in manufacturing over the last several decades.
According to Leamer, creative destruction, globalization, and technology have combined to destroy the value of a high school diploma in an era in which we’ve experienced tremendous increases in both product and process innovation. He wonders whether we can rebuild our middle class using a more effective educational system that pushes people beyond the high school level. Roberts, this time the more optimistic of the parties to the conversation, is less concerned with growing absolute inequality and less with relative inequality. With whom do you agree?
1- Why is “raw natural talent” more important in manufacturing than ever before? What does Leamer mean when he says that workers “have an implicit rental cost that has to be recovered,” and how does this implicit cost affect the pace of work that’s incentivized? How does this differ between picking strawberries and working in a factory?
2- Roberts and Leamer spend some time discussing the metaphorical question: Is a computer a forklift or a microphone? What does this mean, and how does it illustrate Leamer’s findings regarding manufacturing work and income inequality?
3- Are we turning most of our labor markets from Detroit-style labor markets into Hollywood-style labor markets because of the computer? Explain.
4- Why aren’t former manufacturing employees being RE-employed today as they have been in the past, according to Leamer? Why hasn’t the educational system been more responsive? What sort of changes to the educational system does Leamer think are needed to reverse this trend? To what extent do you think such changes are feasible and efficacious?
5- How much of the gap in income between high and low income earners is due not to the hourly wage, but to how many hours that people are working? How do hours worked over time compare between the highest and lowest income earners? How can income and substitution effects explain these differences?
READER COMMENTS
SaveyourSelf
Apr 30 2020 at 8:24am
Regarding the analysis of an income gap:
There is the truism that those who work more, on average, earn more. That simple fact alone could explain an income gap. And it does, but it is not the only reasonable explanation. Supply and demand affect income. Supply of low income work is high–especially with China in the world market–whereas demand for that work is, relatively speaking, low. Demand for low skill labor is made even less by minimum wage requirements and employee benefits requirements. Both minimum wage requirements and employee benefits requirements are typically government regulations designed to help low income workers. And it probably does help those low income workers who can get a job. But, like all hurdles, they make getting a job more difficult, leaving more people unemployed or even unemployable. And, as already stated but from the other end, not working is likely a strong contributor to any income gap (just as working more than other people is likely a strong contributor to the high end of the income distribution). Continuing the supply and demand analysis, demand for some skill sets is very high, driven, no doubt, by a world-spanning open markets. High demand but limited supply of say, chemical engineers or medical doctors, would predictably lead to higher earnings for people who could meet said demand. Here again, the government plays a part. Quotas on the number of doctors educated each year keeps supply of medical doctors low. Quotas created by or enforced by government. And the government runs the K-12 school system. If there are not many children capable of undergoing training in chemical engineering following 12 years of schooling in the government run system, then the activities of the government are, by definition, contributing to the scarcity of chemical engineers—driving the income of those few who do enter chemical engineering higher.
In my experience, drugs play an HUGELY under-appreciated role as a causal factor in income differences. Of course they would. The benefits of participating in a market are often far off and risky. I only get paid once a month for my work, for example. But the “benefits” of dopamine release triggered by heroine injection is instantaneous and large. Market participation, which are the activities that produce income, cannot compete with drugs when it comes to motivating people to action. And, no surprise, government intervention makes drug use worse. Food stamps, housing subsidies, unemployment and disability benefits, free medical treatment—just to name a few—all reduce the down side risks of drug use. A dose of heroine is, I’m told, about $12. Even a small check from the government can buy a lot of heroine.
In my understanding, drug use, genetic/birth defects, mental illness, and unintended consequences of government intervention are the only solid explanations for chronic long term poverty and they also help explain a large and widening income gap. Short term poverty we don’t care about. Because it’s “short term” and will fix itself. Teenagers, on first entering the workforce, for example, are “poor” by definition. But we don’t worry much about them because they will predictably earn more as they learn more skills from participation in the market.
In summary, modern microeconomics has a lot of tools for explaining and predicting causes of a real income gap. Importantly, microeconomic models could help us avoid government macro policies which make poverty and that gap more likely.
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