In spite of Liberty contributing editor Mark Skousen’s observation that “income isn’t distributed, it’s earned,” much handwringing has followed recent reports that income distribution in the US is becoming increasingly unequal.
To a libertarian, how much one earns or owns — so long as it’s acquired honestly and honorably — is nobody’s business. But at the other extreme are the still-influential Rawlsian redistributionists. They believe that since each person’s station in life is due to little more than a roll of the existential dice, income distribution ought to cluster tightly. If it doesn’t, it’s an indication of an unjust society, and something must be done about it. That’s the ideology.
Nevertheless, there’s a pea under that ideological mattress: the fear of revolution if the rich get richer, the poor get poorer, and the middle class disappears. Though probably a reductio ad absurdum, it is nonetheless a theoretical possibility under a laissez-faire economic system.Friederich Hayek understood this, which is why — to the consternation of many libertarians — he advocated a minimal welfare state as a worst-case scenario safety net.
Whatever the chances might be that a just economic system — laissez-faire capitalism — could lead to the penury of a majority, income distribution is a concern to the inner Hobbesian in all of us. So when income inequality rears its ugly head, it bears critical investigation.
In 1912 Italian statistician and sociologist Corrado Gini devised the eponymous Gini Coefficient, a statistical formula based on the Lorenz curve, to measure variability and mutability among data in any discipline. The index is now widely accepted as a measure of income inequality in economics. Values range from 0, total equality, to 1, maximal inequality.
As of 2009, Sweden scored .23, the lowest Gini Coefficient, indicating the highest income equality; while Namibia rated a .74, indicating a large income inequality. Most first-world nations have Gini coefficients in the high point-twenties to the mid-thirties, with a .31 for the EU average. Back in 1980, the US rated a .40 Gini; today we rate around .47, a figure comparable to Russia or Turkey and a trend that is alarming to many.
The fear of revolution, though probably a reductio ad absurdum, is nonetheless a theoretical possibility under a laissez-faire economic system.
Paul Krugman, who could be considered the Linus Pauling of economics — for his previous Nobel-recognized genius, followed by descent into crankhood for his advocacy of snake-oil remedies: vitamin C in the latter case, dirigisme in the former — refers to the period after 1979 as the “Great Divergence,” because of the rapid increase in inequality that had occurred. According to a 2011 Congressional Budget Office report, “Real income (adjusted for inflation) in the US grew by 62% for all households between 1979 and 2007. However, after-tax income of households in the top 1% of earners grew by 275%, while income growth for the bottom fifth of earners was 18%.”
If, instead of income distribution, we look at wealth, the disparity is even greater. While the bottom 60% of the US population lost about 6% of its wealth, the net worth of the top 5% increased by 40% between 1983 and 2009.
Why the increasing inequality in a political and economic system deemed among the freest by classical economists?
* * *
Before addressing that question we must deal with a concept clamoring for immediate attention: fuzzy numbers.
Nearly all the figures quoted in this article come from Wikipedia compilations replete with references, from various other internet sites, The Economist,Scientific American, Money,Chris Martenson’s The Crash Course, and PuruSaxena’s Money Matters. Although these sources are ostensibly reliable, please take them with a pinch of salt. Some figures purporting to measure exactly the same thing vary wildly.
For instance, that 275% of after-tax household income growth for the top 1% earners, derived from 2011 Congressional Budget Office figures of 1979 to 2007, becomes a 176% increase — from 1979 to 2005, nearly the same time range — in a 2006 New York Times article.
Exactly what is being measured, how it is defined, over what period of time it is measured (a variable often manipulated for calculating equity returns down to the day), and what statistical tools are employed can have considerable impact on the figures. Just the difference between ‘”household” and “individual” income measurements can affect income inequality figures substantially.
Dodgy numbers can also lead to convertibility problems and out-of-this-world results — literally out of this world. Composite numbers (such as indices, among others), which are built up from subsidiary numbers, can become statistical black holes, swallowing endless data but illuminating little. As The Economist reports, “In theory, countries’ current-account balances should all sum to zero because one country’s export is another’s import. However, if you add up all countries’ current-account transactions, the world exported $331 billion more than it imported in 2010, according to the IMF. Are aliens buying Louis Vuitton handbags?”
And of course, ideology plays a big part. As the old saw goes, “He who frames the question determines the shape of the answer.”
On top of this are myriad unexamined assumptions. Statistician Joseph Locascio has identified what he calls “publication bias,” which means that academic journals “often give greater weight toward publishing articles that report statistically significant findings over those that don’t.” With this kind of review process, if out of 20 studies one shows a slight significance (perhaps because of chance), while the other 19 show none, that one will be published and the others ignored.
Not all people are driven to make the most money they can, all the time. Many earn and live below their possibilities, and spend the rest of their time pursuing their passions.
Hoover Institute economist Thomas Sowell suggests that many discussions of income equality are based on fallacious reasoning. For example, “an absolute majority of the people who were in the bottom 20% [of income] in 1975 have also been in the top 20% at some time since then. Most Americans don’t stay put in any income bracket. At different times, they are both ‘rich’ and ‘poor’ — as these terms are recklessly thrown around in the media.”
Finally, somewhere between the last two observations, lies individual choice. Not all people are driven to make the most money they can, all the time. Many earn and live below their possibilities, earning what they consider a sufficient amount, and spending the rest of their time pursuing their passions: music, rock climbing, walking around the world preaching the gospel . . . whatever.
So, to that pinch of salt, add a squeeze of lime and, what the hell, a shot of tequila.
* * *
But back to the ostensible causes of inequality, which remain unknown to many, even to theNew York Times, as proclaimed in an article onJune 5, 2005. Let’s consider these causes.
1. The rich work more than the poor. As of 2005, 42% of all US households had two or more income earners. However, in the top quintile of households, nearly twice as many (76%), had dual-earners. Among the lower class, the most common source of income is not occupation but government welfare (according to the leftish Winner-Take-All Politics by Hacker and Pierson, 2010).
2. The rich are more educated than the poor. In the top quintile, 62% of householders are college graduates; while many at the bottom half of earners hold at most a high school diploma. Educational and occupational achievement and the possession of scarce skills correlate with higher income.
3. People of modest means keep giving their money to the rich. George Mason University economist Walter E. Williams recently recognized that “the millions of people who watch LeBron James play are the direct cause of LeBron’s earning $43 million and are thereby responsible for — in Paul Krugman’s terms — ‘undermining the foundations of our democracy.’” The same can be said of the millions of Walmart and Microsoft shoppers who keep enriching the Walton and Gates families.
4. Government policies. Among the usual partisan suspects — such as decreased expenditure on social services and labor’s diminishing political clout, suffering from declining union membership — are Republican tax policies, specifically the “low” progressivity of US tax rates. Reversing these factors through government diktat is a crude cure that doesn’t address the underlying ecology (Thomas Sowell’s term) of the marketplace. The enforcement of legislation such as higher redistributive taxes and the imposition of closed shops would require force, a road down which classical liberals would prefer not to travel. Might there be another cause of the increasing income inequality that hasn’t yet been identified? One whose correction does not require coercion?
I believe there is, and that culprit is inflation — in spite of the fact that nearly all of the above statistics are adjusted for inflation. And, as Milton Friedman recognized, since “inflation is always and everywhere a monetary phenomenon,” it is a direct result of government policy. Inflation is a word often misunderstood. It is the decreased purchasing power of currency, caused by the expansion of the money supply, and not to be confused with price increases caused by scarcity.
Krugman’s “Great Divergence” begins soon after America’s divorce from the gold standard and the subsequent collapse of the Bretton Woods currency exchange system in the early 1970s. After that, the Federal Reserve instituted a Keynesian monetary expansionist policy. In 1972, the price of a new house averaged $27,600; in 2010 (despite 2008’s deflation of the housing bubble), the average price was $272,900. A 1972 Coke cost a dime; today it’s a buck. By 1973, gold hit a high of $126 per ounce; in 2009 it topped $1,212. In 1972 the Dow Jones Industrial Average hit 1,000; by 2010 it had reached 11,000 — a ten-fold increase in only four decades. A $10 Hamilton from 1972 is today’s $100 Franklin. How does this stark change affect the disparity between rich and poor?
* * *
But first, more fuzzy numbers.
Without an objective anchor such as gold, the value of money is subject to fluctuation according to the active “monetarist” policy set by the central bank. That policy is based on many variables — prominently including the consumer price index (CPI), with a nod to gross domestic product (GDP), processed through complex formulae and topped with a generous dollop of intuition. The objective is a stable currency — a very difficult goal with such a capricious policy, and one whose results always lag policy implementation.
For a variety of reasons, the central bank considers deflation a greater evil than inflation. So, wishing to avoid deflation at any cost, the Federal Reserve sets an inflation goal of 1–2%. It often misses this goal. The October 2011 rate was 3.53%, according to the Bureau of Labor Statistics (BLS), as measured by the CPI.
How reliable is this number? Not very — as it is neither accurate nor even precise. Like an aging diva afflicted with weight gain, wrinkles, fatigue, loss of figure and overexposure, the CPI has been massaged, injected with Botox, subjected to fad crash diets, over-cosmetized, face-lifted, repackaged, and rebranded. Richard Nixon, for example, bequeathed us the so-called “core inflation” measure, which strips out food and fuel — a bit like weighing yourself without your belly. In 1996 Bill Clinton implemented three oddities in the measure of inflation: substitution, weighting, and hedonics.
Krugman’s “Great Divergence” begins soon after America’s divorce from the gold standard and the Federal Reserve’s institution of a Keynesian monetary expansionist policy.
With substitution, it is now assumed (for example) that if the price of salmon goes up too much, people will switch to something cheaper, such as hot dogs. So as the price of an individual item within a representative basket of thirty goods rises, that item is removed and substituted with something cheaper, chosen by a trained bureaucrat. According to the BLS, food costs rose 4.1% from 2007 to 2008. But according to the Farm Bureau, which tracks exactly the same shopping basket of 30 goods from one year to the next without substitution, food prices rose 11.3% for the same year.
Weighting is an even sharper tool for cutting the measure of inflation. Anything that rises too quickly in price is undercounted in the CPI, under the assumption that people will use less of those things. For example, although healthcare is about 17% of the economy, it is weighted as only 6% of the CPI basket.
But the most creative way to fiddle with inflation is hedonics. This adjustment is supposed to reflect quality improvements. Here’s how it works, based on a presentation by a commodity specialist at the BLS and explained by Chris Martensen:
In 2004, the commodity specialist at the BLS noted that a 27-inch television selling for $329.99 was selling for the same price in 2007, but was later equipped with a better screen. After taking this subjective improvement into account, he adjusted the price of the TV downwards by $135, concluding that the screen improvement was the same as if the price of the TV had fallen by 29%. The price reflected in the CPI was not the actual retail store cost of $329.99, which is what it would cost you to buy, but $195. Bingo! At the BLS, TVs cost less and inflation is heading down. But at the store, they’re still selling for $329.99.
Hedonics rests on the improbable assumption that new features are always beneficial and are synonymous with falling prices (never mind that most old rotary phones still work, while modern cell phones seldom seem to last three years). Hedonics is now used to adjust as much as 46% of the total CPI.
What would the inflation rate have been for, say 2008, before all the fuzzy statistical manipulation gussied it up? John Williams of shadowstats.com, using early 1980’s formulas, computed the figure at 13%: the BLS reported a 5% inflation rate for the same year — a stunning 8% difference.
But that’s not all. During Alan Greenspan’s tenure at the Federal Reserve — particularly while the real estate bubble was growing gangbusters — some economists bemoaned that, without asset prices such as real estate and equities being included in the CPI, true inflation rates would be misleading, thereby skewing monetary policy.
While inflation has been massaged down, GDP has been steroided up, by similar sleight-of-hand manipulations — further inflating the money supply.
So, at this point, brace yourself with another shot — this time of hedonic Cuervo Añejo.
* * *
Inflation affects the poor and the rich in completely different ways, though both lose wealth. No one benefits — except for government and banks, which, having access to newly created money before it hits the streets and raises prices, can buy goods and services at the old, cheaper rate. By the time the surplus money has permeated the economy and reached the masses, prices have usually risen significantly.
Broadly speaking, the poor — for the purposes of this essay, people in the lower 40% of income distribution — have fewer assets, lack financial sophistication, and tend to hold, at most, a high school diploma. They deal in cash and its derivatives and equivalents — CD’s, bonds, and interest-bearing accounts. In an inflationary regime, these lose value. In an underreported inflationary regime, the effect is not only obviously greater but, because wages only grudgingly and loosely track the “official” inflation rate of the CPI (if at all), “much of the developed world’s workforce has been squeezed on two sides, by stagnant wages and rising costs,” as The Economist opined in its November 19, 2011 issue.
There is one factor leading to wealth disparity that Rawlsians and Marxists most seem to ignore, but classical economists believe is fundamental — productive innovation.
As if this situation were not bad enough, many of the poor were lured into buying homes by dodgy loans and government social engineering policies (such as the Community Redevelopment Act, Fannie Mae and Freddie Mac practices, and lower than historic interest rates) in the middle of a bubble. When the bubble burst, these folks lost whatever equity they had managed to cobble together, as well as ending up with ruined credit. And they couldn’t even rely on their savings (what little they might have saved between stagnant wages and rising costs), as these too had dwindled along with the higher interest rates that made savings more attractive.
So, without a doubt, the poor are getting poorer. What about the rich?
While cash loses its value, real goods such as commodities, equities, and real estate track the changing value of money and, long term — with the dips and highs of the business cycle evened out — generally keep pace. The rich, with more education, more financial sophistication, and more discretionary income, invest. The poor, on the other hand, save (if they can afford to). All other things being equal, inflation makes investments tread water, but savings lose. Without inflation, income inequality might not have become so pronounced over the last 40 years.
Though the above analysis might go a long way toward explaining the increasing income inequality in the United States, it still isn’t the full picture.
There will always be income inequality, if for no other reason than the fact that people’s work habits, education, and ambition vary tremendously. But the one factor leading to wealth disparity that Rawlsians and Marxists most seem to ignore, but classical economists believe is fundamental — productive innovation — also plays a big part.
A study done by University of Texas economists James K. Galbraith and Travis Hale found that
During the technology boom of the late 1990s, most of the gains enjoyed by the top 1% came from a small number of counties, rather than a national trend. Almost all of the richest 1%’s gains occurred in the economic hotbeds of Silicon Valley, and also New York City. If the top four counties in those regions are removed, there is almost no trend towards income inequality during the years studied (1994–2000). On this basis, the researchers ascribe the growth in income inequality in the late 1990s to the growth of information technology.