Labor Market Concentration, Earnings Inequality, and Earnings Mobility

Kevin Rinz, "Labor Market Concentration, Earnings Inequality, and Earnings Mobility," U.S. Census Bureau, 2018, https://www.census.gov/library/working-papers/2018/adrm/carra-wp-2018-10.html

Figure 7 focuses on markets containing at least one top-five firm and reports the number of top five firms competing in these markets. In 1976, just over 60 percent of markets with at least one top-five firm contained exactly one top-five firm. By 2015, that share had fallen to just over 50 percent. Notably, the bulk of the approximately ten additional percent of markets with multiple top-five firms in 2015 had three or more top-five firms, as the share of markets with two such firm was fairly stable over this period. Also, as indicated by the previous figure, those ten percent represent substantially more markets in 2015 than in 1976. Together, Figures 6 and 7 show that the largest national firm have expanded their geographic reach over the past 40 years while also increasingly entering the same local markets. The expansion of the geographic reach of these top firm accelerated around the same time that national HHIs began to increase. These patterns provide suggestive evidence that this channel merits further investigation. I now turn my attention to changes in the distribution of local industrial concentration. Figure 8 plots trends in key percentiles of the employment-weighted local HHI distribution. The box and whisker plots present the interquartile range (box) and internecine range (whiskers), with the mean (circle) and median (horizontal line) also plotted. The figure makes a few important features of the distribution immediately clear. First, the distribution has a long right tail; in every year, the value of the 75th percentile is more than twice that of the median, and the value of the 90th percentile is more than twice the value of the 75th percentile. As a result, the mean HHI is consistently well above the median. Second, the distribution has tightened over time, and this appears to have been driven by changes in the top of the distribution. The value of the 90th percentile has fallen by about a third between 1976 and 2015. The values of the 75th percentile and median have also fallen, but more modestly, while the 10th and 25th percentiles have seen little change in absolute terms over this period. Figure 9 extends this distributional analysis beyond the key percentiles presented in Figure 8, showing changes in the values of each percentile between 1976 and 2015. This figure confirms that changes in the values of high percentiles of the local HHI distribution over this period were much larger in absolute terms than were changes in the values of middle percentiles. Low percentiles saw little change in absolute terms, but relative to their initial levels, the changes at the bottom of the distribution were comparable in magnitude to those at the top, as illustrated by the log difference version of the figure….”

Kevin Rinz finds that local industrial concentration (using Herfndahl-Hirschman) has declined over recent decades. Think of large nations chains moving into new markets increasing local competition, “…Though trends in national measures of other forms of concentration may have contributed to recent interest in monopsony, trends in local industrial employment concentration have differed substantially from trends in national industrial employment concentration over the last four decades. While mean national industrial concentration declined sharply in the early 1980s, it began increasing rapidly again around 1990 and continued to do so until the onset of the Great Recession, nearly returning to its initial level. Local industrial concentration, on the other hand, has been declining fairly consistently since 1976, with limited interruptions. By 2015, average local concentration had declined to about three quarters of its 1976 value….”

Relationship btw concentration and wage, …"Consistent with other recent research,I find that increased concentration reduces earnings.My estimates imply that moving from the median to the 75th percentile of the employment-weighted local industrial concentration distribution would reduce earnings by about ten percent. Moving from the median to the 25th percentile would increase earnings by a similar amount. Estimates produced without weighting by employment are larger in magnitude than the baseline estimates, which indicates that earnings reductions associated with increased concentration are larger in smaller markets.... the effects of concentration vary across groups of workers. First, looking across the earnings distribution, I find that increased concentration leads to greater inequality as measured by the ratio of the 90th percentile of the earnings distribution to the 10th percentile (the 90/10 earnings ratio). By comparing changes in the 50/10 earnings ratio and the 90/50 earnings ratio, I estimate that about 60 percent of the increase in the 90/10 earnings ratio arises from changes between the median and the 10th percentile. Moreover, I estimate elasticities of particular percentiles with respect to concentration and find that lower percentiles are more negatively responsive to changes in concentration than are percentiles in the middle of the distribution. Percentiles higher in the distribution change little in response to changes in concentration…”

Distributional impact, "...All demographic groups experience increases in inequality when concentration increases. Men, older workers, and workers with high school diplomas or less see the largest increases in the 90/10 earnings ratio. As in the overall distribution, these increases are generally driven by the bottom of the distribution.Women and Black workers are again exceptions, with virtually all of the inequality increases in these groups coming from the top half of the distribution. This could be due in part to the fact that these groups generally have lower earnings throughout the distribution. As a result, changes experienced at any given point in the overall earnings distribution are experienced further up the distribution of earnings withing these groups..."

Bottom line, "...While these estimates indicate that increased concentration does indeed reduce earnings and increase inequality, combining them with the changes in concentration that have actually been observed since 1976 suggests that local labor market concentration has not been a major contributing factor to broader changes in inequality and earnings growth. According to back-of-the-envelope calculations, average annual real earnings were about 1.2 percent higher and the 90/10 earnings ratio about 6.3 percent lower in 2015 than they would have been if local concentration were at its 1976 level...."

The evidence, "...Some business data are available publicly, but they do not provide frm-level information with fne geographic detail, limiting their usefulness for measuring local employment concentration. As for outcomes, few local labor markets are suÿciently well represented in surveys to construct reliable distributional statistics. Fortunately, I can address both of these issues using administrative records available through the U.S. Census Bureau. The Bureau’s data linkage infrastructure also allows me to construct earnings measures that incorporate demographic information available from the Census Numident file, the 2000 and 2010 decennial censuses, and all available years of the American Community Survey...Before turning to local concentration,Figure 1 presents the average HHI across national four digit NAICS industries from 1976 through 2015, with industries weighted according to total employment.Average concentration falls sharply in the early years of this period, declining by roughly 40 percent between 1976 and 1983. It then sees little change until about 1990, at which point it begins increasing, nearly reaching its 1976 level by the onset of the Great Recession. This pattern is not sensitive to measuring concentration using the HHI. Appendix Figure B1 shows very similar patterns emerge when concentration is measured using the top-four or top-twenty firm employment concentration ratios.