Reconsidering Income Statistics

The measure most often used to track prosperity is some form of income statistic. Although this intuitively makes sense, the devil can be in the details. Income statistics, in general, can be misleading in many ways. Furthermore, some measures of income seem to be better than other measures. Nevertheless, measures of prosperity are likely to continue comprising of income measures and, therefore, it is important to understand their flaws and limitations.

The limitations of income statistics as a measure of prosperity fall into two categories. First, income is only one part of the picture. Second, it is not always clear that changes in income statistics accurately reflect changes that occur in actual per-capita income.

To begin with, income is not an all-encompassing measure. Other contributors to prosperity include job satisfaction, health, and leisureliness, which income statistics do not typically capture. In addition, certain aspects of the economy remain unaccounted for using income statistics, such as volunteer work, the black market, the household division of tasks, and other activities that do not appear on an individual’s tax return. As a result, using income on its own to measure prosperity is clearly misrepresents an individual’s level of affluence.

There is yet a deeper flaw in the measurement of income statistics, which lies in the imperfect science of trying to draw conclusions using statistical abstractions.

For instance, a common way to measure, and think about, income statistics is to consider the household unit. After all, most people are familiar with their household’s monthly budget and use this to help their understanding of the economy.

Household income, however, is, perhaps, the worst way to measure income. This is fundamentally a result of household variation, not only over time, but also between different demographics and income brackets. Thus, changes in household composition often cause variations in household income. Economist Thomas Sowell has studied this phenomenon extensively, offering three general observations:

1) Household size has decreased over time. Between 1967 and 2005, real per-capita income in the United States grew 122% (whereas household income grew 31%). In this case, shrinking household size has “weighed down” apparent income growth
2) Household composition, including the number of working household members, varies between groups. For instance, the highest earning 20% of American households consists of 64 million people, while the lowest earning 20% of households consists of 39 million people, including single-parent families, single-earner families, and so on. It is therefore easy to speculate that differences in household income can partially be attributed to differences in households
3) Most household income statistics do not follow flesh-and-blood individuals over time. This is important because a given income bracket does not perpetually consist of the same individuals, despite some narratives. While many people are surely living in conditions of poverty, individuals gradually climb the income ladder throughout their career. Sowell’s research suggests that individuals in the bottom 20% of households are more likely to end up in the top income bracket than to remain in the bottom bracket after ten years.

In any case, ‘household income’ is an abstract measure. Consider a fictional economy, for instance, consisting of a married couple living in a single dwelling. If said couple separates, however, “household” income decreases by 50%. Although per-capita income does not change, using household income as a measure would not lend that impression. This is precisely the rationale for distinguishing per-capita income from other statistical categories, such as household income.

Overall, it is important to recognize the limitations of income statistics when attempting to assess the wellbeing of specific groups, entire populations, or whole nations. While household income is particularly flawed, it is unlikely that any single income measure wholly measures prosperity or happiness.

Michael Craig is a 2013-2014 Atlantic Institute for Market Studies’ Student Fellow. The views expressed are the opinion of the author and not necessarily the Institute

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