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Macroeconomic Misery by Levels of Income in America

At the time of writing (mid-2021), there is a public debate in the U.S. stemming from fears that the macro policies in the wake of the 2020-21 pandemic are stimulating inflation. Concerns have been raised about the impacts of macro policy choices on poverty and inequality.

The relative importance of inflation versus growth and employment as macroeconomic indicators has long been debated. Arthur Okun’s famous “Misery Index” (OMI hereafter)—developed when Okun was an advisor to the Johnson Administration in the U.S. during the 1960s—added up the inflation rate with the unemployment rate. Since then, others have argued that the growth rate should be included (weighted negatively).

Economic theory has offered some insights, but what does the evidence suggest on how these macro variables impact levels of real income in America, ranging from the poorest to the richest?

Micro evidence can tell us (for example) whether poorer families have higher rates of unemployment. However, macro evidence can also reveal indirect effects on real incomes; for example, a higher economy-wide unemployment rate may reduce the wage-bargaining power of workers in poor families or reduce (public or private) transfer payments to those families. There is also likely to be heterogeneity within any given income group, such as due to differences in dependence on the labor market, wage setting, discrimination by race or gender, and wealth portfolios. It is thus of interest to see if systematic differences in the mean impacts of these macro variables are evident at different levels of income.

In a new paper I ask how the relative importance of three prominent macro indicators—the rate of unemployment, the inflation rate and the growth rate of GDP per capita—depends on whether one is talking about the real incomes of the poor, middle-income groups or the rich.

The new paper explores these issues using real income distributions assembled from almost 30 years of survey data since the 1980s, spanning a wide range of macro-outcomes, including the Great Recession (GR) of 2009-10.  The literature does not suggest that any single summary measure of “inequality” or “poverty” could adequately capture the nature of the distributional changes induced by these macro variables. So I look at data on incomes from the poorest to the richest Americans. The regression specifications aim to isolate the short-term effects of the macro variables at each income level.

The paper’s results indicate a systematic pattern in how the key macroeconomic indicators influence real incomes in America. The unemployment rate should have higher weight than inflation in a Misery Index calibrated to real incomes across the whole distribution, at least in this time period.

A higher unemployment rate unambiguously increases poverty measures (for all measures and lines). It also reduces the skewness of the distribution—an effect that is not evident in its (ambiguous) implications for inequality. This more complex distributional pattern found in the study is not evident if one only looks at a summary statistic of overall inequality, such as the popular Gini index.

Inflation matters more in the middle of the distribution than in the tails. GDP growth rates matter at all levels of income, and especially for the poorest; however, this effect is largely attributable to the impact of growth on the unemployment rate.

The restrictions implied by the OMI—namely equal weighs on unemployment and inflation and excluding the GDP growth rate—are rejected across the bulk of the distribution, and strongly so for the poorer strata; indeed, the OMI appears to only be defensible for the top income groups.