What to watch for in the Census income and poverty data
Next Tuesday, the Census Bureau will release its data on income, poverty, and health insurance coverage for 2015, which will give us a better picture of how working families are—and are not—recovering from the Great Recession. Even in the full business cycle of 2000-2007, earnings and incomes never fully recovered to the pre-recession peaks reached in 2000, so when the Great Recession hit, the economic impacts were especially devastating for many. To the extent the data allow, next week’s release will let us see how much the recovery has improved the economic lot for typical Americans, paying particular attention to differences in the recovery across racial and ethnic groups.
First, EPI researchers will examine the data on median earnings, by gender, race and ethnicity. Hourly wage data for 2015 suggest decent growth between 2014 and 2015 across the board, driven mostly by unexpectedly low inflation, driven mostly by falling oil prices. Median hourly wages grew 1.7 percent between 2014 and 2015. Hand-in-hand with stable average weekly hours, this suggests an uptick in median annual earnings.
We’ll look at changes over the last year, as well as changes since before the Great Recession, and since 2000—the last business cycle peak that can be confidently associated with genuine full employment. Women have already exceeded their 2000 real earnings level; the hourly wage data indicate a return to 2007 prerecession levels of earnings for men in 2015. We’ll also analyze these changes by race and ethnicity to understand how the economy has treated demographic groups. Again, the hourly wage data is the best predictor of what we can expect for these sub-groups. (For a taste of these comparisons, check out EPI’s new State of Working America Data Library.) I expect the 2015 annual earnings data to show a slight decline in the gender wage gap, and the Hispanic-white wage gap, but a slight increase in the black-white wage gap.
Second on our agenda will be an examination of trends in median household incomes. Again, we will be looking at these data across a range of households: all households, non-elderly households, and by race, ethnicity, and nativity (native born vs. foreign born). As labor income is the primary form of income for non-elderly households in the middle of the income distribution, we should see a slight rise in these measures between 2014 and 2015—though likely not strong enough to return to 2000 or even 2007 levels. (Also, just a side-note on the income data, because of the redesign in 2013, we will be making an imputation to the historical series, 2000 to 2012 to make them directly comparable to the latest income data. This entails creating a ratio of the original and redesigned 2013 income data within each demographic subgroup, and imputing that backwards to create a consistent series.)
In addition to looking at how median household income growth differed by race and ethnicity, we will also examine changes in incomes across the income distribution. Specifically, we will be presenting the growth in income by income fifth and the top 5 percent to make an assessment of growing or shrinking inequality over the last few years. Unfortunately, again, the hourly wage data through 2015 indicate a growth in wage inequality and therefore likely a growth in income inequality.
Third, we will provide an analysis of recent trends in poverty. Similar to the previous discussion, we will analyze poverty in 2015 and then make comparisons to 2007 and 2000. We’ll also look at poverty by race and ethnicity, and separately for children—who tend to have particularly elevated levels of poverty.
Finally, on Tuesday the Census Bureau will also release its annual report on the Supplemental Poverty Measure (SPM), an alternative to the long-running official poverty measure that attempts to correct some of the weaknesses of the official poverty measure (e.g., the fact that it counts only cash income, and often sets possibly too-low thresholds for poverty, due in part to its lack of geographic variability.) We will take a deeper look at these SPM data to make an assessment of how poverty, as measured by the SPM, has changed in the recovery. Also, because the SPM includes non-cash measures of family income, such as income from social security and tax credits, we will provide a brief assessment of how well our public assistance programs are lifting people out of poverty.