The Real Causes of Income Inequality

The administration loves to beat the drum about income inequality.  Every chance they get, they point out that the rich are getting richer and the poor are getting poorer.

Their solution; higher taxes and more government spending.  More government programs.  More transfer payments.

We know that doesn’t work.  The data is clear, and so is the condition of the neighborhoods where most of the transfer payments wind up.

One way the income gap can be explained is via immigration.  When people migrate to the US, they generally have lower incomes than existing US citizens.  Once here, they work their way up.   They take low skilled jobs, and many times it’s the second generation that begins to build wealth.  It’s a time honored story in the US, and why the demand to come here exists today.  Demand wouldn’t be there if it wasn’t true.

Unfortunately analyzing the income gap is not as simple as the administration would like you to believe.  It is also not as simple as citing immigrants and wiping our hands thinking we solved the problem.

Professor John Taylor has a nice opinion column in the WSJ today about the causes of it.

The poor economic policies of the past few years is a reasonable explanation for today’s weak economy. Fiscal policy has at best provided temporary stimulus before fading away with no sustainable impact on growth. More costly and confusing regulations—including the many mandates in the Affordable Care Act and the Dodd-Frank Act—have reduced the willingness of firms to invest and hire. The Federal Reserve has employed a variety of unconventional and unpredictable monetary policies with not very successful results.

Sir David Moritz in Silicon Valley sees it differently.  He blames Facebook ($FB).

Instead, the data factories get free labor. They distribute what seem like useful services to the world, things like YouTube, Facebook, Twitter, LinkedIn, Etsy, or Kickstarter. Those services help people share, connect, find jobs, sell their own goods, or fund a project. But in actuality, they also collect troves of data and earn tons of money for the tech giants without forcing them to do much work. That money stays concentrated around the data factories and their limited staff instead of distributing it like traditional factories.

What’s the impact? “It means that life is very tough for most everyone in America” says Moritz. That’s not just some ambiguous sense of hardship. The median American household has stagnated. The absolute minimum wage value has decreased significantly. “It’s tough if you’re poor, it’s tough if you’re middle class. It means you have to have the right education to work at [the tech giants]. If you’re not like us, it’s tough” said the highly successful venture capitalist.

Moritz is correct that software is eating up a lot of jobs.  Andy Kessler has made that point perfectly clear many times.  Alan Andreesen says “software is eating the world.”.  It is.  But, like Carl says when he chomps on the Baby Ruth bar in Caddyshack, “It’s no big deal.”.

Moritz is correct, education is a huge issue.  If you don’t have a good education, it’s tougher.  Taylor correctly identifies education as a driver of wealth.  He points out the data show returns to education started diverging in the 1980′s.  Economist Gary Becker has said the same.

The only way to fix education is to blow up the existing system we have today.  The revolution has to come from the top down, not the bottom up.  It’s the wealthy that can afford to pay for education innovation. Once they pay, the innovation will become more efficient, and the ability for it to become commoditized will allow innovation to reach more people, eventually reaching the poorest of the poor. So far, it is government bureaucracy, entrenched education administrators,  teacher’s unions and the Democrats that are killing education innovation.

Because of technology, a revolution that reaches everyone can happen a lot faster than it used to.

Here is one example. It used to be that only the wealthy could pay for one on one tutoring for standardized tests.  It was highly expensive. One paid pro could create a customized program to meet the individual needs of one child.

Then, companies like Kaplan started commoditizing the process.  They offered  in person expensive classes. If you paid a pretty penny, you got instruction in how to take tests.

With the advent of technology, companies like PrepMe and BenchPrep brought that individual customized program to anyone who wanted it.  But, they also charge for their services.

Brilliant goes one step further.  It creates an entire marketplace of ideas.  An international social network of people teaching and interacting with other people for math and science. Not only are there students there, but professors, teachers, interested people.  Level up high enough, and you have the opportunity to get paired with a university professor.  Free.   All you need is internet access.  The masses have access.

PrepMe and BenchPrep were started around 2006-2009.  Brilliant started last year.  This revolution can move very quickly.

Moritz is correct in many ways.  Many tech companies are getting free labor and free data.  In exchange for that, they are creating value.  Do these applications eat people?  Sure.  So did ATM machines.  But, those tech companies are creating far more high quality jobs than they destroy.

Taylor is also correct.  Federal Reserve policy has been totally irresponsible.  It not only is destroying the middle and lower classes, but is destroying the elderly in the US.  It’s stagnating the growth of wealth at every class level in the US.  Combine poor Fed policy with the terrible job killing regulatory policy enacted since Obama has been elected and things get worse.  Sprinkle in some bad fiscal policy out of the Congress and we have the recipe for disaster.

The solution is to fix our policy problems.  At the same time, we need to embrace technology to radically disrupt our legacy systems.  The companies that survive will do so because they create value for the people that use them.

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