In this April 26th, 2005, column in the Pittsburgh Tribune-Review, I dispute the widely believed notion that rising income inequality – or, rather, rising differences in annual monetary incomes – are undesirable. The full column is below the fold.
Income inequality
Is income inequality bad?
Most Americans think so. But this question is deceptively ambiguous, and answers to an ambiguous question range all over the map. That’s not only because different people understand the question differently, but also because each person answering it often interprets it in ways that he finds most ideologically suitable.
To appreciate the ambiguity of questions about income inequality, start by asking what is meant by “income.” Is it a worker’s annual gross pay or annual take-home pay? Does income include the value of fringe benefits, such as employer-provided health insurance? Does it include the value of government-provided benefits such as welfare payments?
And how to account for income earned in black- and gray-markets? By their nature, transactions in these markets are hidden from the gaze of government officials and gatherers of statistics.
Also, what’s the appropriate unit whose income should be measured? Is it each worker or each household? And what, exactly, is a household? Is a college student who lives four months of the year with her parents and eight months in an off-campus apartment part of her parents’ household? Or is she her own household?
STATISTICAL NUANCE
None of these questions has an obviously correct answer. But measured income statistics will differ greatly depending upon the particular ways that statisticians answer them.
For example, if college students who live in off-campus apartments for eight months of the year are counted as separate households — instead of as part of their parents’ households — the measure of average household income will be lower than it would be if these students are counted as part of their parents’ households.
The reason is that most students earn less than their parents.
Suppose that 10 college students from 10 different families each lives in an off-campus apartment for eight months of the year and with their parents the other four months. During the year each student earns $10,000 by waiting tables, while each of their sets of parents earns $70,000 at their jobs. If each of these students is counted as a separate household, average household income of these 10 families (living in 20 different households) is $40,000. But if these students are counted as part of their parents’ households, then average household income is $80,000.
Quite a difference.
More importantly, at least for those concerned with income distribution, if the students are counted as part of their parents’ households, then among the 10 families in this example there is complete equality of household income ($80,000 per household). But if the students are counted as separate households, significant economic inequality of households appears, with the top half of these 20 households earning an average income ($70,000) that is a whopping seven times larger than the average income ($10,000) earned by the bottom half.
As this example shows, the particular ways that statisticians define “income,” “household,” and other factors that must be defined and measured in order to paint a statistical portrait of people’s economic well-being will significantly affect reported measures of income inequality. Define these things one way, and income inequality is small; define them another way, and income inequality is large.
Bear these definitional challenges in mind when you encounter discussions of income distribution.
INCOME MOBILITY
Also bear in mind that people are economically mobile. Many of today’s low-income workers will be tomorrow’s middle-income workers; and many of these will be among the country’s highest-income earners sometime in the future.
My own case isn’t unusual. When I was in graduate school, I lived completely independently of my parents and, thus, was counted as my own household. My annual income was paltry. I survived by taking out student loans. I was definitely among America’s lowest-income households.
Twenty years and a wife and a child later, my household income now is in the top 10 percent.
One lesson is that people who today are “poor” according to economic statistics are not necessarily poor in any meaningful sense.
I wasn’t really poor 20 years ago, even though a snapshot taken of my income and financial position then made it seem as if I were. But I never doubted then what proved to be true: If you get a good education and work hard, your lifetime economic prospects are bright. And surely our prospects over the course of years and decades are more important than where we happen to be at any one particular moment.
In fact, the greater the dispersion of incomes, the greater the gain awaiting those who are poor today but who will move, as they acquire experience and skills, into higher-income categories.
