Inequality is a fascinating subject, one that provokes discussion and makes it hard to settle the apparently simple question of whether income inequality in the US has increased since 1988. In his essay Alan Reynolds presents evidence in favor of his thesis that income inequality has not increased, Gary Burtless and Mark Thoma present evidence in favor of the opposite view that inequality has significantly increased, while Richard Burkhauser concludes that there has been an increase, but a modest one. In our reply we will bring additional facts to this discussion. Our main point, however, is to argue that to focus only on the evolution of current income inequality is insufficient if one is interested in the evolution of the distribution of living standards in the U.S.
Why only look at current income inequality?
The material sources of a household’s well-being are the flow of consumption and possibly the flow of its leisure enjoyed over its lifetime. Thus if one is ultimately interested in the distribution of well-being across U.S. households, the object of study ought to be the joint distribution of lifetime consumption and leisure across them.
Measuring inequality in lifetime consumption and leisure is an impossible task as it would require data on consumption for many households, each followed for a very long period of time. Such data unfortunately do not exist. What is then a feasible and appropriate way of measuring inequality in lifetime consumption?
If people would earn constant income throughout their lives, current income would be a very good approximation of lifetime consumption. In the data, though, current income fluctuates substantially over the life cycle and thus it is a potentially poor indicator of lifetime resources. Fortunately, we can use simple theories of consumption decisions of households over time (pioneered by Nobel prize winners Milton Friedman and Franco Modigliani), which show that if households can borrow and lend on financial markets, then there is a strong link between the lifetime resources of a household (sometimes also called its permanent income) and its current consumption. Current income shocks that are not fully permanent (such as seasonal shocks, job losses, bonus payments) strongly affect current income (and thus have a strong impact on the distribution of current income), but only have a moderate impact on permanent income and thus consumption.
While current consumption is not always perfectly connected to permanent income (this connection for example is weakened in the presence of borrowing constraints), it is, under many circumstances, a better proxy for it than current income. Under those circumstances documenting trends in consumption inequality is more informative about the inequality in lifetime resources.
Let’s illustrate the point further with a simple example. Think of a world with two households, the White and the Reds, whose monthly income has two parts: a fixed part and a fluctuating bonus. Suppose that the Whites have a fixed part of $100 and a bonus that alternates between $10 and $30, while the Reds have a fixed part of $50 and the same bonus structure. Both households realize that their bonuses fluctuate but they both dislike fluctuating consumption. As a consequence they will save part of their high bonus and run down their bank account when their bonus is low. This will lead the White to consume around $120 and the Reds to consume around $60.
Now suppose that bonuses become more volatile and go from a $10-$30 structure to a $0-$40 structure. What happens to current income inequality? The higher volatility of bonuses makes it more likely to observe larger differences in income and thus current income inequality will go up. Should we worry about this increase in inequality? Not really, since the lifetime distribution of resources between White and Red has not changed (as reflected in the unchanged consumption inequality). If anything inequality will have a positive effect on incentives as both will work harder to get the high bonus.
Suppose instead that the bonus structure is eliminated and White receives a permanent raise of $5 while Red takes a $5 permanent cut. What happens to income inequality? Since the very volatile bonuses have disappeared, current income inequality is likely to be unchanged or even diminish. Should we be happy about it? Not really, because the decline in current inequality masks an increase in inequality in lifetime resources and thus in well-being. Note that since the cut and the increase are permanent they will be fully reflected in consumption, and thus tracking consumption inequality will fully reveal the increase in lifetime inequality, with its adverse distributional consequences.
The example above, although very stylized, suggests that focusing only on inequality in current income can lead to very misleading conclusions regarding the welfare effects of inequality. Looking also at consumption inequality can help us avoid these conclusions. The example also stresses the role of financial markets (the bank account in our stylized example) as the key link between inequality in lifetime resources and inequality in current consumption. It suggests that in these days of very developed financial markets, consumption, and not current income, should be the cornerstone of empirical and theoretical inequality studies.
Income and Consumption Inequality in the US
One important reason for the popularity of using income inequality for measuring the distribution of living standards in the U.S. is the availability of several data sets collecting household income data. These differ in their sample size, quality, and ability to capture a representative sample of the U.S. population, as spelled out in the Reynolds essay. However, comprehensive and detailed household-level consumption data is available for the U.S. for the period under question (which, following Reynolds, we take to be 1988 to 2005). While other authors involved in the public debate have questioned the quality of the Consumer Expenditure Survey (CES), which is administered by the U.S. Bureau of Labor Statistics, a number of prominent scholars have now used this data set to document trends in consumption inequality over the last 25 years.
One bonus of using the CES is that it also contains information on income, and hours worked. Thus we can look at inequality from different angles for the same set of households. One drawback is that the CES is a relatively small survey (between 5,000 and 10,000 households per quarter) and thus does not contain very precise information about the top 1% of the population. In Figure 1 (from Krueger and Perri, 2006) we report the evolution of several measures of income (the green lines) and consumption inequality (the blue lines), all computed from the CES sample for the 1980-2003 period. The bottom two panels, for example, report the 90/10 ratio and the 50/10 ratio for income and consumption. The 90/10 and 50/10 indicators have the desirable properties that are not affected by changes in top-coding procedures and are easy to interpret: an income 90/10 ratio equal of 5 suggest that the per capita income in the household at the top 10% of the income distribution is 5 times the income of the household at the top of the bottom 10% of the income distribution. The key message from our figure is that the increase in income inequality in the U.S. has been much more pronounced than the corresponding increase in consumption inequality.
Let us come back to the original question posed by Reynolds. Has US current income inequality increased over the period 1989-2003? Looking at CEX data suggests that yes, it did. As also suggested by Gary Burtless, one main source of the increase has been the increase of incomes at the top part of the income distribution relative to incomes at the bottom and middle of the distribution. The 90/10 ratio increases from around 5 in 1989 to around 6 in 2003.
The consumption data suggest, though, that the consequences of this increase have not caused an increase in the dispersion of the distribution of lifetime resources; if it did it would have showed in increased consumption inequality. Consumption inequality, however, has remained substantially stable.
Is the stability of the consumption distribution simply caused by a massive and increasing measurement error and/or misreporting of consumption? We can’t rule out this possibility, but there is some additional evidence that makes us think this is not the case. An increasing income inequality coupled with a stable consumption inequality implies that, according to economic theory, the larger income fluctuations are now smoothed through stronger use of credit markets. Therefore we should expect to observe a significant increase in the volume of household credit in the US over the last 15 years. Many credit indicators point exactly in that direction. This seems to indicate that the stability of the consumption distribution is indeed informative about the trend of inequality in lifetime resources.
One conclusion we would not like the readers to take home is the generic one that we should not worry about income inequality. Rather we would like to convince them that understanding the welfare effects of changes in measured inequality, and possibly the appropriate policy measures to deal with it, is a complex task that involves more than reporting the distribution of current resources. Ideally one should understand and measure the distribution of lifetime resources. In order to understand how lifetime resources translate into observable indicators, and what these indicators are, it is crucial to have a thorough understanding of how and to what extent households can transfer resources through time and across states of the world using financial markets. Our own previous work has highlighted the importance of using consumption as an indicator, but recent exciting work is being done by leading researchers in the economics community stressing the role of inequality and dispersion in other variables, too, such as labor effort or wealth, and assessing their impact on incentives, the allocation of resources, and the distribution of welfare.
References and Footnotes
Krueger Dirk and Fabrizio Perri, “Does Income Inequality lead to Consumption Inequality?,” Review of Economic Studies, March 2006.
 Gary Burtless correctly mentions that when one measures total consumption in the CES and compares it to total consumption as measured in the National Income and Product Accounts (NIPA) the fraction of CES to NIPA consumption declines substantially from 1985 to 2000. While this raises some concern about the quality of the CES data (NIPA consumption data may not be perfect either, though), it is very hard to assess if and how it biases estimates of inequality measures and their trend over time. In order to partially address this problem we include in our measure of consumption several categories of durables, for which the problem mentioned above is much less severe. In addition, in the most recent waves of the CES (2000-2005) the discrepancy between growth in NIPA consumption and aggregate CES consumption has shrunken.
 To reply to Gary Burtless’ suggestion that many people with conservative inclinations [are] enamored of consumption data in the BLS’s Consumer Expenditure Survey (CES), we want to point out that a) We used the CES because 30 years of economic theory teach us that looking at consumption is a much more compelling way to understand the effects of inequality and the CES is the only dataset that allows us to do so in the US for a long enough period of time; so if we were enamored of the CES, it is only because it is the only girl in town b) We like to think of ourselves as social scientists, and as such we keep our political inclinations, whatever they are, very separate from our work.