By Jared Bernstein and Larry Mishel President Trump’s Council of Economic Advisers has a new piece out claiming to show that real wages are growing faster than has been widely reported. Their conclusion stems from numerous adjustments to Bureau of Labor Statistics wage data that otherwise show flat real earnings for most workers. However, most of CEA’s adjustments, applied accurately, do not change the inconvenient fact that even amidst strong macroeconomic results and a tight labor market, real wage growth for middle-wage workers has been weak over the past two years. That may change, if falling unemployment triggers faster wage growth, but at this point, measurement tweaks make little difference to the conventional wisdom, at least over the short period covered by the CEA report. As
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By Jared Bernstein and Larry Mishel
President Trump’s Council of Economic Advisers has a new piece out claiming to show that real wages are growing faster than has been widely reported. Their conclusion stems from numerous adjustments to Bureau of Labor Statistics wage data that otherwise show flat real earnings for most workers.
However, most of CEA’s adjustments, applied accurately, do not change the inconvenient fact that even amidst strong macroeconomic results and a tight labor market, real wage growth for middle-wage workers has been weak over the past two years. That may change, if falling unemployment triggers faster wage growth, but at this point, measurement tweaks make little difference to the conventional wisdom, at least over the short period covered by the CEA report. As former CEA chair Jason Furman tweeted yesterday, the report “does almost nothing to change our understanding of wage growth”
The CEA argues that by adjusting for the following factors, real wages grew at least 1.4 percent higher over the past year, as opposed to zero:
–adding fringe benefits;
–adjusting for the demographics of the job market;
–adjusting/reducing hours worked;
–using a slower growing price deflator.
We find that only the last point is valid, but that even with that adjustment, real compensation is still flat, largely because benefits, properly measured, have not been rising any faster than wages, contrary to CEA’s claims.
Fringe benefits: Even in the data used by CEA, the growth of benefits is hardly outpacing that of wages, so adding fringes doesn’t change the underlying trends. Their own Figure 2 (see their report) shows how benefits as a share of compensation have been flat at around 30 percent over the recent period of flat real wage growth.
The most commonly cited wage and compensation data come from the Employment Cost Index (ECI), and these data show, for example, that over the past two years, nominal wages (private sector workers) are up 5.4 percent while fringe benefits are up 5.1 percent. Thus, in these data, adding in benefits doesn’t change the wage growth story.
The CEA uses a related data series (ECEC data, which unlike the ECI does not keep the industry and occupation mix constant and provides detailed benefits data) that we analyzed to track two different ways of measuring the benefit share (see table below). The first column uses a “W-2 wages” concept, that includes earnings, paid leave, and supplemental pay in the wage category (the second column includes leave and supplemental pay as benefits, as in CEAs figure above). The W-2 measure corresponds more closely to the measures of wages most analysts and journalists track using household and establishment data. But either way, the share is clearly stable. As we show below, a stable benefit share cannot lead compensation to grow faster than wages.
In comparing compensation to wage trends, it is also germane to note that not all workers get key fringe benefits, yet CEA implicitly assigns them to everyone (and we follow this practice too, for comparability). Recent BLS data show that only 23 percent of workers in the bottom quartile participate in health plans and 25 percent participate in retirement plans. For those in the second quartile (25-50th percentile range), about half participate.
Demographic adjustments: Here again, the short time frame works against CEAs conclusions, as, barring a large shock, like a recession, the composition of the labor force doesn’t change that much year-to-year. Though they claim the entry of young workers taking low-wage jobs is dragging down the average, analysis by Heidi Shierholz and Elise Gould show that “since 2013, as the recovery has strengthened, the opposite has been true—low-wage jobs are actually declining on net while middle and high wage jobs are being added, which has the effect of raising average wages. In other words, the composition effect is currently putting upward pressure on wages.”
What about the other end of the age scale? CEA also claims the retirement of high-earning older persons is putting downward pressure on wages, though here again, for this to affect the trend, such retirements would have to be accelerating. As this interesting analysis by economist Adam Ozimek reveals, the opposite appears to be the case. He finds that “…the senior share of the workforce is growing, not shrinking; 2) seniors are not the highest-paid age group; and 3) to the extent the workforce age composition has affected wages over the last decade or even the last year, it’s not about seniors.”
A simple way to dispel the composition explanation is to look at Atlanta Fed’s wage growth tracker, which controls for demographic changes in the workforce by following the same workers over time. The nominal wage growth in the series accelerated steadily from around 2010 to 2016, it has been largely flat since then, hovering around an average annual growth rate of 3.2 percent (this series runs faster than others in part due to its inclusion of a one-year “experience premium,” the extra pay accruing to workers as the gain experience on the job). This suggests that composition is not a factor in the flattening of real wage growth, which has been a function of faster inflation and slow growth in nominal pay.
All this evidence suggests little to no role for a demographic or composition explanation of the flat real wage trends that have persisted over the past two years. CEA makes a bigger adjustment by applying the a “demographic composition correction…based on the average for the expansion from 2013 through 2018.” This very likely overestimates any near-term compositional shifts, and it is unclear to us why they use an average versus annual values. Moreover, CEA’s demographic adjustments still do not make the early Trump quarters look better than the period that preceded them.
Similarly, their rationale for their hours adjustment—they reduce hours in some series which raises hourly pay—based on the difference between hours worked and hours paid was unclear to us as the paid leave share of wages or compensation has been stable since at least 2014.
Price adjustments: This is the one place where the CEA has a point, though once again, given the short time frame in their final analysis, 2017q2-2018q2, this too doesn’t amount to much. The CEA argues for the use of chain-weighted deflators, which more accurately measure consumer price changes, as they better account for consumer behavior (specifically, chain-weighted deflators better account for changes in the contents of the consumer market basket driven by changes in relative prices). The CPI, which is used by the BLS in their monthly earnings reports, is not chain-weighted.
Therefore, the CEA adjusts wages using the PCE deflator. However, the problem with this choice, as Bivens and Mishel describe here, is that the PCE is considerably less representative of prices faced by consumers. A better choice would be the chained-CPI, which the BLS has produced since 2000. Though the two chain-weighted deflators track each other fairly closely, over the past year, the PCE deflator was up 2.3 percent compared to 2.7 percent for the chained CPI (and 2.9 percent for the standard CPI). In other word, moving to a chained CPI only raises real wage growth over the past year by 0.2 percent.
As a technical note, we find it curious how economists seemingly attentive to measurement details about inflation typically fail to account for the faster than average growth in health insurance prices (relative to the CPI, whatever version) when incorporating benefits data into a compensation measure. Recognizing this faster inflation in health insurance would yield a slower growth in compensation than the measures both here and in CEAs report.
Putting it all together, the table below shows the impact on real hourly compensation for middle-wage workers, using our benefit adjustment, which excludes wage benefits, such as overtime and shift premiums, from health and retirement benefits, along with the chained CPI (see data note for more details). Between 2017q2 and 2018q2, real hourly compensation adjusted by the CPI was essentially flat, down 0.2 percent. After the relevant adjustments, it’s still flat, essentially unchanged over the last quarter.
Sources: see data note below.
The chart below takes a slightly longer-term perspective, showing real hourly compensation for 2014-2018, second quarters. Compensation was growing, in real terms, in earlier years, driven largely by unusually low inflation and some nominal wage acceleration as the jobless rate fell in those years. But the last two years have been dry spells for the real hourly pay of middle-wage workers, a finding that holds when we include their benefits and shift to a slower-growing deflator.
Sources: See data note below.
In other words, there is no evidence of the CEA-suggested acceleration of compensation since Trump took office. To the contrary, the growth of real hourly pay of middle-wage workers has slowed to a crawl since then.
As we said, faster real wages and benefits may occur if the jobless rate continues to fall, giving less advantaged workers more of the bargaining clout they lack. But for now, hourly wage and benefit growth, inflation-adjusted, is close to flat in real terms and considerably less than the 1.3 percent productivity growth over the last four quarters. We’d thus urge CEA to spend less time with their thumb on the measurement scale and more time on policies to help working people benefit from the ongoing expansion.
Data note: Table 2 starts with the hourly wage of blue-collar factory workers and non-managers in services (this is the BLS production, non-supervisory wage, which covers 82 percent of the workforce). We then scale that up to include benefits using the ECEC benefits data as described in the text (W-2 measure). Finally, we adjust nominal compensation by both the regular and chain-weighted CPI. Note that since ECEC data are not yet out for 2018q2, we use the 2018q1 benefit share (as, apparently, does CEA).