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Tony Quain
Tony Quain is a commentator on free-market economic theory and policy. He has a Ph.D. in economics from George Mason Univ. More >>
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Inequality today
Redistribution today
Taxes today
Sep 12, 2014 9:07am, by Tony Quain, 259 words

Link: http://equitablegrowth.org/news/new-useful-measure-inequality/

The linked article by Nick Bunker argues that we should take the Palma Index (which measures inequality as a ratio of the percent of income received by the top decile (10%) over the percent of income received by the two bottom quintiles (40%)) more seriously, and if not replace the Gini with it, make it an equal partner in explaining unequal outcomes. His reasoning:

But in some cases it can show increases in inequality that the Gini misses. Case in point: the Palma for post-tax income in the United States for 2010 was 1.98, a 43 percent increase since 1979. The larger increase compared to the Gini (21 percent) shows how much of the rising inequality was due to changes at the tails.

You can see its appeal to the left. For those who bemoan the earnings of the "1%", chasing tails has been an obsession. But the Palma exposes their base motivation: they are only obsessed with one tail (the "rich"), not two, and are thus more occupied with envy than with sympathy for the poor. Why is it not 10%/10%? Or 40%/10%?

Another reason they like it is because total inequality, as the author admits, is just not that stunning. Tail inequality has more statistical backing for being an urgent concern, which means that middle inequality has actually improved.

The Palma Index gives four times as much weight to the top 10% as it gives to the bottom 40% and gives no weight at all to the middle five deciles. For a measure of inequality, propounded by supposed defenders of equality, it is a truly discriminate and unequal statistic.


Sep 11, 2014 11:37am, by Tony Quain, 658 words

Link: http://www.pieria.co.uk/articles/on_inequality_-_with_any_search_for_answers_it_helps_if_people_can_first_agree_on_the_question

An excellent article.

Murphy identifies three definitional frames that discussions of income inequality must come to terms with before they start talking statistics:

1) Are we looking at inequality of households or individuals?
2) Are we considering annual income (dispensing with age) or lifetime income (adjusting for age, dynamics)?
3) Are we looking at market (pre-government) income or disposable (post-government) income?

I won't go into the reasoning behind each one of these, but Murphy would appear to agree with me that household inequality is a bogus measure: unfairness if it happens is due to individuals' income, not their choice of who they live with. He would also agree that upon reflection, most people wouldn't care if there is vast inequality due exclusively to age: everybody will get his share if that is the case. The first two items are pretty close to being open-shut cases where the only two reasons for not looking at the right data is the absence of such data (which is certainly a concern, especially for getting lifetime income statistics) or the nefarious intentions of the researcher (which is a larger concern).

On the third item, it is more about what the purpose of the research is. If you are trying to assess how economic inequality really is, as exhibited by people's conspicuous consumption, then you should use post-government data. That would be the case 90% of the time. But if you are trying to assess how economic inequality would be, without some or all of the government interferences, you may need to use pre-government data, possibly in conjunction with post-government data. With that caveat out of the way, I agree with Murphy that in general researchers make the mistake/offense of using pre-tax, pre-benefit data all too often.

Then there is this big revelation:

Once we make all these important distinctions and definitional changes ? that is, we adjust for age and consider post-tax and post-distribution income at the individual rather than household level ? we reach an interesting conclusion. Between 1987 ? before which time the US data is less reliable ? and now, real spending per person by income quintile shows income inequality has not changed at all. That of course says nothing about whether it is too high or low ? merely that it has not deteriorated the way that is frequently argued.

Looking at the correct statistics, the supposed "rise in income inequality in recent years" is a sham. There is no rise in income inequality.

Some further questions for Murphy (and others) to consider, beyond the three he identifies:

1) Are we looking at inequality of (implicit) wages or of income regardless of work effort? Do people really feel it is unfair for someone working twice as many hours to get twice as much pay? Or is it just unfair if they are getting twice the (explicit or implicit) wage? Income inequality statistics almost never adjust for work effort. And if they did, would they include previous work effort to acquire skills and education?
2) Are we looking at income inequality as a proxy for consumption inequality? Would income inequality irk people if everyone consumed the same amount, but those with higher incomes saved the rest (or gave it away)? Or does it all come down to conspicuous consumption?
3) Are we looking at income (or consumption) inequality as a proxy for utility inequality? Discussions of inequality are often peppered with language such as "well off" or "better off", which are terms only appropriate for utility comparisons (and then maybe not interpersonal comparisons). But maybe the question of being better off is the one people are after, no?

Murphy finishes his article saying that the only real solution is equality of opportunity through better or more even-handed education. That may be where a middle-road political solution develops (though whether that means more or less state intervention is not pre-determined), but the improvement of education is an on-going battle anyways. With respect to economic inequality, the best policy is simply to ignore it.


Sep 9, 2014 2:48pm, by Tony Quain, 170 words
Tags: ,

Link: http://online.wsj.com/articles/casey-b-mulligan-the-myth-of-obamacares-affordability-1410218437

Excellent article in today's WSJ.

As with so many left-wing projects, the title (in this case, Affordable Care Act) is unintentionally Orwellian.

Some of the nice points:

Although the ACA helps specific populations by giving them a bigger slice of the economic pie, the law diminishes the pie itself. It reduces the amount that Americans work, and it makes their work less productive. This slows growth in both personal income and gross domestic product. ... By the end of this decade, nearly 20 million additional Americans will have health insurance as a consequence of the law. But the ultimate economywide cost of their enrollments will be at least double what it would have been if these people had enrolled without government carrots and sticks; that is, if they had decided it was worth spending their own money on health insurance. In effect, people who aren't receiving assistance through the ACA are paying twice for the law: once as the total economic pie gets smaller and again as they receive a smaller piece.


Sep 3, 2014 1:28pm, by Tony Quain, 107 words

Link: http://econlog.econlib.org/archives/2014/08/government_work_1.html

Prof. Caplan seems in a charitable mood ...

Before you get your eyes checked, or think Caplan has gone lefty on us, read the crux of his argument:

[Government enterprises'] performance is almost always disappointing. But contrary to Rothbard's story, their performance is rarely disastrous. ... Am I damning with faint praise? Sure. Even the best government enterprises are slow to cut costs. They're bad at innovation. And they're almost uniformly terrible at putting aside Social Desirability Bias to answer every enterprise's most fundamental question: Is this worth doing at all? Yet the anomaly remains: Simple economics implies that government enterprises should be far worse than they really are.


Aug 29, 2014 4:42pm, by Tony Quain, 349 words

Link: http://economics.mit.edu/files/9834

Sorry I forgot to post this earlier in the week (this article came out last week and was published on RealClearPolicy on Monday).
Two Harvard/MIT economists take apart Piketty's "laws of capitalism".

Thomas Piketty’s recent book, Capital in the Twenty First Century, follows in the tradition of the great classical economists, Malthus, Ricardo and Marx, in formulating “general laws”to diagnose and predict the dynamics of inequality. We argue that all of these general laws are unhelpful as a guide to understand the past or predict the future, because they ignore the central role of political and economic institutions in shaping the evolution of technology and the distribution of resources in a society. Using the economic and political histories of South Africa and Sweden, we illustrate not only that the focus on the share of top incomes gives a misleading characterization of the key determinants of societal inequality, but also that inequality dynamics are closely linked to institutional factors and their endogenous evolution, much more than the forces emphasized in Piketty’s book, such as the gap between the interest rate and the growth rate.

And the conclusion:

Piketty’s ambitious work, fashioning itself after Marx’s Capital, has focused a great deal of new attention on inequality. Piketty pro¤ers a bold, sweeping theory of inequality applicable to all capitalist economies. Though we believe that the focus on inequality and the ensuing debates are very healthy and constructive, we have argued that Piketty goes wrong for exactly the same reasons that Marx, and before him Malthus and Ricardo, went astray: his approach and general laws ignore both institutions and the ‡exible and multifaceted nature of technology shaped by institutions. We have further suggested that the history of inequality over 20th century in economies such as South Africa and Sweden shows why the focus on top 1% inequality is unsatisfactory and why any plausible theory of inequality has to include political and economic institutions at the center stage. We have also provided a brief outline of a framework that squarely puts the spotlight on institutions, their nature and evolution in the study of inequality.


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Featured Article
Aug 19, 2014 2:59pm, by Tony Quain, 2123 words

Here's a riddle for you.

Andy and Brett both started work at the same age. They both earned the same starting salary. They both got a $1,000 raise every year. Both are still alive and still work for the same company they started with, and have no additional income. But Andy earned twice as much as Brett last year. How is this possible?

If you are confounded by this puzzle, don't despair. You fall into the same trap that intelligent and even Nobel-prize winning economists fall into all the time. Hint: Brett is following in Andy's footsteps. Give up? Andy is 60 years old and Brett is 30.

The obvious fact that annual income statistics will necessarily include people who are young and old, inexperienced and experienced, part-time and full-time, is routinely ignored or dismissed in the one area of economics where differences in income among people are the primary focus: studies of economic (in)equality.

Consider another mental exercise.

Everyone in society E starts work at age twenty with a salary of $20,000. Everyone receives a raise of $1,000 each year (so that, their annual salary is always their age times $1,000). They retire at age 60, earning $60,000 in their final working year. In total, each and every person earns $1,640,000 in their working lives.

Economically, is E an equal society? One could argue that this society is by definition equal. Let us also assume that there are an equal number of people in this society of each working age (one million people of age twenty, one million of age twenty-one, etc.). Now, if in any given year we gather the annual income statistics, we shall find disparities of income: one million people earn $20,000 while another million earn $60,000, with many levels in between. Using annual income statistics without separating for age gives the appearance of an unequal society. The Gini coefficient (a summary statistic used extensively in economic equality studies, where 0 is perfect equality and 1 is perfect inequality) is 0.171. But in our fictitious society of equals this is terribly misleading. Yes, there is income inequality, but it is because people are at different stages of their lives and careers, not because of any permanent or chronic economic disparities among them. If we measured income on a lifetime basis, rather than (the somewhat arbitrary) annual basis, the Gini coefficient would be zero.

Of course, some of the inequality measured by annual income statistics is due to differences among people apart from age. Some people make more money over their lifetime than others. Even though lifetime income differences may be deserved, or may be the result of choices these individuals intentionally make, it is this kind of disparity that concerns most people.

What if a researcher told you that there were vast differences of height among people in America? Would you be thinking, "Oh, that's because babies are short and adults are taller"? Probably not. A normal person would think that fully grown people had height disparities. Would you expect that the researcher had limited the data to adults? You probably would. And the researcher probably would. Yet this is the same sort of problem involved with annual income data. When economists make claims about inequality based on data that is not normalized for age, they are either being incompetent or deceptive. They are making people believe there are differences between the skilled and unskilled, or the lucky and unlucky, or the "rich" and the "poor," when much of these differences are between the old and the young—differences that most everyone will experience.

How much of measured inequality is due to age and how much is due to real differences in lifetime earnings? American economist Morton Paglin tried to figure this out. In a ground-breaking journal article, he took the standard inequality summary statistic, the Gini coefficient, and broke it into two parts: (1) the "Age-Gini," which measured income differences attributable to age, what he called "intrafamily" inequality; and (2) the "Paglin-Gini," which measured real income differences among people, what he called "interfamily" inequality. He suggested that use of cross-section data such as annual income statistics should be broken down in this way to separate innocuous inequality due to annualized statistics from true inequality which reflects differences among people apart from age. Further, he found that "estimates of inequality have been overstated by 50 percent" and concluded that "the overstatement of inequality has lent false urgency to the demand for rectification of our income distribution."

That article was published in 1975. Paglin's method was subjected to criticism, both from a technical standpoint and a conceptual one. There was concern that the method did not make the split cleanly enough, and critics said that in any case inequality in the broader sense (inclusive of differences due to age) was what economists wanted to measure. The dispute between Paglin and his critics was never resolved. As a result, through confusion and willful ignorance, Paglin's method was shelved by most economists who measure inequality, though it does reappear from time to time.

Some might say that the absolute size of inequality, as measured by statistics like the Gini coefficient, is not really at issue. Rather, how the Gini of one country compares to another, or the increase in the Gini in recent years, is the real story. Yet here we have a fallacy of division. Increases in overall annual income inequality do not necessarily imply an increase in true income inequality alone, or an increase in both age-income inequality and true income inequality of equal or similar degrees. It is possible that much of the increase in measured income inequality in recent years is due to age-inequality, i.e. that the ratio of average income of people in middle-age over income of people in their early 20s has been increasing. In fact, it is possible that age-inequality is responsible for all of the increased inequality, and that true inequality has not changed at all. Or that true inequality has actually decreased, and age-inequality increases have been more than total measured inequality increases.

Not only is age-related inequality innocuous, but we might even consider it good. I believe that the differences between these two components of inequality are so distinct that we might call the intra-family (age-related) component "good inequality" and the inter-family component "bad inequality."

Why is "good inequality" good? First, it his how we as individuals get richer, even if society on average does not. Consider again society E above. Would anyone in society E bemoan the development (e.g., through a technological breakthrough, or a better work ethic) of everyone getting a $2,000 raise each year instead of $1,000? And yet, the $2,000 raise is all age-related inequality that increases inequality measured by annual income statistics. Inequality, as measured today, will never be meaningfully reduced or eliminated unless people stop earning more. To achieve equality, as it is commonly defined and measured, there can be no raises, no higher pay for experience or seniority, no personal growth. That entry-level pay you got at your first job at Wendy's is all you can ever aspire to. Second, numerous studies have shown that people derive happiness from personal growth, and specifically income growth. But growth and inequality go hand-in-hand. In a society of differently-aged people, you can not have income growth without inequality. In a growing economy, the more inequality of annual incomes there is, the more growth there is. Ergo, to have happiness there needs to be annual income inequality due to age, i.e. good inequality.

Why is "bad inequality" bad? To the extent that it occurs, some may say that it simply reflects different efforts and abilities, that it is deserved. That may be true, or it may not. But it is hardly arguable that the differences in people's abilities or efforts that cause these inequalities are not lamentable. Some may argue that we should attack the causes of these inequalities, but not the symptom of inequality itself, while others may argue that we should redistribute income to ameliorate the symptom. But this kind of inequality is certainly the inequality that people have in mind when the topic is discussed, and it is this kind of permanent class inequality that is bemoaned, justly or not. Therefore, inequality among lifetime incomes may be considered a "bad inequality."

There is good reason to think that a large portion of measured inequality increases are due to age-inequality. One approach is to use age-cohort income data to see if income differences among age groups have been increasing. And they have. Consider the graph at the top of this column constructed from US Census CPS income data. The figures are in constant 2012 dollars. I included the entire date range (1974-2012) of the Census dataset, but let's look at the generally alleged time period of inequality expansion, 1980-2010. The 15-24 age cohort's average income has stayed essentially flat over this period ($14,265 to $14,305, an increase of 0.3%). But the more aged (and thus more experienced) wage-earners have seen substantial income growth: 25-34 saw 14.2%, 35-44 got 25.6%, 45-54 got 29.1%, and 55-64 got 41.9%. (These were the increases, over 30 years, of the average income for the age cohort, not for incomes of people within the cohort; those were much larger. For instance, people in the 15-24 cohort in 1980 would be in the 45-54 cohort in 2010, so the average income of those actual people increased from $14,265 to $51,712, an increase of 162.5%. That is some perspective for the "income stagnation" thesis. More on that in a later column.) What this shows, then, is that as the U.S. economy grows, people at the beginning of their working lives, with entry level experience, can expect the same pay for their unskilled jobs as people in that same position thirty years ago; and since it is entry level work, this is hardly surprising. But to the extent that people have more job experience, and are closer to the end of their careers, they have seen real rewards to their experience increase by a much greater amount than the premium for experience received thirty years ago.

To some readers, this should cause the metaphorical light-bulb to blink over their heads. The graph also shows that the cohort plots are bunched closer together in 1980 than in 2010. This (roughly) illustrates the inequality due to age in 2010 is greater than in 1980. And this inequality appears not because any one age group is losing out. Rather, it is because as people age they are making more money at a faster rate than they did in the past.

This is pretty solid evidence that at least some (and perhaps most) of the income inequality increase over the past thirty years is age-related and not "timeless" inequality among classes or individuals per se.

The age-income relation is a real problem for using standard annual income data when discussing income inequality or when deriving inequality summary statistics like the Gini. But it is not the only problem. Economists have also pointed to problems with using "market income" rather than "disposable income", i.e. using pre-tax and pre-benefit income data. They have pointed to problems with using "households" or "families" instead of "individuals" as the unit of analysis. Then there is the problem of including part-time workers along with full-time workers. Or the misuse of statistics, such as starting with cyclical economic nadirs and ending with cyclical peaks (among other deliberate tricks). All of these are valid criticisms. But the age-income relation is perhaps the biggest, least reported, and least appreciated problem for the income inequality hysterics. And while there are some economists who may intentionally ignore it, there are others who may be ignorant of it.

There is bad inequality and good inequality. Bad inequality is the differences between people's skills and consequent earning ability that results from differences in their education, effort, and serendipity. Though these differences may be deserved, it is hard to argue that they are not regrettable. Good inequality is the opportunity for growth that results in all people earning more as they grow older with more experience and productivity. It is mathematically impossible to have income growth in a society of differently-aged people and not have greater inequality.

Progressives often use a ladder analogy to describe what they see as growing inequality: "the rungs on the ladder are getting farther apart." The analogy is not inapt, but their interpretation is. Everyone generally starts at the bottom rung of the economic ladder. But increases in annual income inequality, where they do occur, may be the result of people climbing more rungs faster than in the past. Progressives see a rise in annual income inequality and see what they want to see: an ugly story of one class in society dominating another. But what if it simply means that people are getting more rich over their lifetimes than they were before? What if it is the beautiful story of people starting off poor and becoming rich?


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