macroblog

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The Atlanta Fed's macroblog provides commentary on economic topics including monetary policy, macroeconomic developments, financial issues and Southeast regional trends.

Authors for macroblog are Dave Altig and other Atlanta Fed economists.


August 21, 2015


No Wage Change?

Even when prevailing market wages are lower, businesses can find it difficult to reduce wages for their current employees. This phenomenon, often referred to as "downward nominal wage rigidity," can result in rising average wages for incumbent workers despite high unemployment levels. Some economic models predict that a period of subdued wage growth can follow, even as the labor market recovers—a kind of delayed wage-adjustment effect.

In her 2014 Jackson Hole speech, Fed Chair Janet Yellen suggested this effect may explain sluggish growth in average wages in recent years, despite significant declines in the rate of unemployment.

This macroblog post looks at evidence of wage rigidity, particularly a spike in the frequency of zero wage changes relative to wage declines. A comparison is made between hourly and weekly wages and between incumbent workers (job stayers) and those who have changed employers (job switchers).

Chart 1 shows the fractions of job stayers reporting the same or a lower hourly or weekly wage than 12 months earlier. These measures are constructed from the Current Population Survey microdata in the Atlanta Fed's Wage Growth Tracker. They include workers who are paid hourly (accounting for about 60 percent of all wage and salary earners). The measures exclude those who usually receive overtime and other supplemental pay and those with imputed or top-coded (redacted) wages. Weekly wage is defined as the hourly wage times the usual number of hours per week worked at that rate. The data are aggregated to an annual frequency (except for 2015, where the first six months of the year are covered).

Job stayers cannot be exactly identified in the data and are approximated by those who are in the same occupation and industry as they were 12 months earlier and the same job as they were in the prior month. Consistent with other studies (see, for example, the work of our colleagues at the San Francisco Fed), we find that the incidence of unchanged hourly wages among job stayers is substantial (although some of this is probably the result of rounding errors in self-reported wages). The measured share of unchanged hourly wages rose disproportionately between 2008 and 2010, and it has remained elevated since. Zero hourly wage changes (the green line in chart 1) have become almost as common as declines in hourly wages (the blue line in chart 1).

150821a

Chart 1 also suggests that weekly wages for job stayers show a pattern over time broadly similar to hourly wages. But the fraction of unchanged weekly wages (the purple line in chart 1) is lower. Each year, about 60 percent of those with no change in their hourly wage had no change in their weekly wage (or hours) either. Also, there are relatively more declines in weekly wages (the orange line in chart 1) than in hourly wages—mostly the result of reduced hours worked. On average, a reduction in weekly wages is associated with a four-hour decline in hours worked per week. About 90 percent of those with lower hourly wages also had lower weekly wages, and 20 percent of those with no change in their hourly wage had a lower weekly wage (working fewer hours).

If job stayers show a relatively high incidence of no wage change, we might expect a different story for job switchers, since they are establishing a new wage contract with a new employer. Chart 2 shows the fraction of job switchers reporting the same or a lower hourly or weekly wage than 12 months earlier. Job switchers are approximated by workers who are in a different industry than a year earlier.

150821b

Not surprisingly, a smaller share of workers experience no change in their hourly or weekly wage when switching jobs. But the pattern of zero wage change for job switchers over time is generally similar to that of job stayers. It is also true that a decline in hourly and weekly wages is more likely for job switchers than for job stayers, with a significant temporary spike in the relative frequency of wage declines for job switchers during the last recession.

Taken at face value, this analysis suggests the presence of some amount of wage rigidity. Also, rigidity increases during recessions and has remained quite elevated since the end of the last recession—especially for job stayers. The question then becomes whether this phenomenon has important macroeconomic consequences. A prediction of most models in which wage stickiness has allocative effects is that it causes firms to increase layoffs when faced with a decline in aggregate demand. Interestingly, during the last recession—when wage stickiness appears to have increased substantially—the rate of layoffs was not unusually high relative to earlier recessions. What was atypical was the size of the decline in the rate of job creation, and this decline contributed to unusually long unemployment spells. As noted by Elsby, Shin, and Solon (2014), it is not clear that an increase in wage rigidity would constrain the hiring of new workers more than it constrains the retention of existing workers.

On the other hand, persistently high wage rigidity in the wake of the Great Recession is consistent with the relatively sluggish pace of wage increases seen in most measures of aggregate wage growth via the "bending" of the short-run Phillips curve (as described by Daly and Hobijn (2014)). Interestingly, the Atlanta Fed's Wage Growth Tracker is an exception. It has indicated somewhat stronger wage growth during the last year than other measures. It will be interesting to see if that trend continues in coming months.

Photo of John Robertson
By John Robertson, a senior policy adviser in the Atlanta Fed's research department

August 21, 2015 in Employment, Labor Markets, Wage Growth | Permalink | Comments (0)

July 17, 2015


Getting to the Core of Goods and Services Prices

In yesterday's macroblog post, I highlighted an aspect of a recent Wall Street Journal article that concerns how households perceive inflation. Today, I'm going back to the same well to comment on another aspect of that story, which correctly notes that service-sector prices are rising at a faster clip than the price of goods.

Of course, this isn't just a recent event. Core services prices have outpaced core goods prices over the past 50 years, save a few short-lived deviations. What's unusual about the current recovery, as the chart below shows, is how low services inflation has been.

Core Goods and Services Prices

In the nearly six years since the end of the 2007–09 recession, core services prices have risen at an annualized pace of 2.1 percent, a full percentage point below their average during the last expansion. Conversely, the annualized growth rate in core goods prices during the recovery has been 0.5 percent, compared to a decline of 0.6 percent during the last expansion (see the chart below).

Core Goods and Services Prices

To see how broad-based the slowdown across core services prices has been relative to that of core goods prices, let's take a deeper dive into the components. The chart below compares the difference between a particular component's annualized growth rate during the current expansion and its growth rate during the previous expansion. A negative number here means that a component's price is growing more slowly now than it did prior to the recession.


It's evident that the slowdown in core services prices is fairly broad-based (17 of 22 components are exhibiting disinflation relative to their growth rate over the previous expansion). For core goods components, that number is just five of 15 components. So, if we accept the premise of the WSJ article—that trends in services prices more closely reflect "unused domestic capacity"—then it's possible we could be farther away than we think.


July 17, 2015 in Inflation | Permalink | Comments (0)

July 16, 2015


Different Strokes for Different Folks

A recent Wall Street Journal article offered an interesting conjecture. The author stated,"[b]ecause consumers pay service bills more often than they buy most goods other than food and gasoline, perceptions of inflation skew on the high side."

Research supports the idea that inflation perceptions are unusually influenced by particular prices. For example, some authors have noted that inflation expectations appear to be unusually influenced by movements in gasoline prices.

This research by Georganas, Healy, and Li shows that inflation perceptions are affected by how frequently people buy a particular good—so that nondurable goods prices like gasoline affect inflation perceptions more than durable goods.

And recent work by Johannsen at the Federal Reserve Board shows that demographic groups who have a more disperse set of inflation experiences also tend to hold more disperse inflation expectations. One thing I think we can say is that different demographic groups appear to have different inflation experiences, as this research by Hobjin, Mayer, Stennis, and Topa indicates.

For example, let's take a look at the difference between the inflation experiences of two households. The first is a single older female (over 55 years of age) who rents her home and has a relatively low income (less than $30,000 a year). The second is a young couple (younger than 35 years old) who own their home and have a high income (over $70,000 annually). Both households have high school educations. Recently, the difference between the inflation experiences of these two demographic groups has opened up to a sizable 2.0 percentage points (see the chart). Why?

Different Inflation Experiences

Well, the spending habits of these two groups contain a few striking differences. For example, the older female spends a lot more of her household income on food at home, rent, and medical care than the young couple does (see the table). Also, the young couple appears to spend a larger fraction of their income on transportation (a large portion of which is gasoline).

Comparison of myCPI Weights

Average of the previous five years (through December 2014)

 

A young couple, homeowner, high income, high school education

Older female, renter, low income, high school education

Food at home

7.2

14.4

Food away from home

5.4

2.8

Shelter

23.2

39.8

Utilities

6.4

8.5

Household operations

1.0

1.2

Household furnishings and equipment

2.8

1.3

Apparel

2.2

1.7

Transportation

23.5

7.5

Medical care

4.1

11.3

Recreation

5.1

3.6

Education

0.7

0.2

Other

18.2

7.7

Note: "Other" includes personal care, alcohol, tobacco, reading, and miscellaneous goods and services
Source: Author's calculations based on the BLS's Consumer Expenditure Survey

What's the inflation experience for someone in your particular demographic group? Let's find out. We've developed a tool called myCPI. It allows users to track a measure of the cost of living that captures some of the variation that occurs between demographic groups. In less than a minute, you can answer a few questions about your demographic category, and we'll show you the cost-of-living trends for "your" group. And if you want, we'll send you updates of your demographic group's inflation with every consumer price index (CPI) report.

Why not get your myCPI report? And when tomorrow's CPI report is released, we'll send you a note telling your how your group's cost-of-living adjustment compares to the average urban consumer in the headline CPI.


July 16, 2015 in Inflation | Permalink | Comments (0)

July 15, 2015


Have Changing Job and Worker Characteristics Restrained Wage Growth?

In the wake of the Great Recession, nominal wage growth has been subdued. But it is unclear how much of this relatively low wage growth reflects protracted weakness in the labor market versus other factors, such as changes in the composition of the workforce and jobs over time. Wage growth tends to vary across personal and job characteristics, so it stands to reason that changes in the composition of the workforce, alongside demographic and work characteristics, could be an important explanation of overall movements in wage growth.

In this post, we explore the impact of the changing mixture of worker characteristics (by age and education) and types of jobs (by industry and occupation) on the Atlanta's Fed Wage Growth Tracker. We find that composition effects do not account for the low median wage growth experienced in recent years. Holding worker and job characteristics fixed at their 1997 shares raises the median wage growth in 2014 by only about 0.2 percentage point. Our results are consistent with the analysis in a previous macroblog post, which found that changing industry-employment shares could not explain much of the sluggish growth in the average hourly earnings data from the payroll survey.

Median wage growth, composition change by worker characteristics
In terms of demographics, we consider two features: a worker's age and education. As shown in this earlier macroblog post, younger workers tend to experience higher median wage growth than do older workers. Although older workers tend to be paid more based on experience, they are also more likely to be near the top of the wage distribution for their job, so the median older worker experiences less wage growth. The difference is quite large. In 2014, the median wage growth of workers over age 54 was around 1.2 percentage points lower than the overall median.

A person's education can also affect his or her wage growth. Workers with a high school diploma or less tend to have lower median wage growth. In 2014, the median wage growth of less-educated workers was about 0.1 percentage point lower than the overall median, reflecting that these workers are more likely to be earning minimum wage, which does not change very frequently.

In addition, the employment shares by age and education have changed over time. The proportion of workers in the Atlanta Fed's Wage Growth Tracker data who are over age 54 has more than doubled from 12 percent in 1997 to 25 percent in 2014. During the same period, the share of workers without a college degree has declined from 63 percent to 49 percent (see the charts).

Education and Age Distribution Over Time

Wage growth, composition change by job characteristics
In terms of job characteristics, we consider two features: the worker's industry (where they work) and their occupation (what they do). Before 2011, workers in service-producing industries experienced slightly higher (about 0.1 percentage point) median wage growth than all workers. But since then, the trends have flipped. In recent years, median wage growth of individuals working in service-producing industries has been slightly below the median wage growth of all workers.

Nonetheless, workers in professional occupations such as managerial, legal, scientific, and engineering jobs tend to experience relatively higher median wage growth. In 2014, the median wage growth of workers in these professional jobs was 0.2 percentage point higher than the median wage growth for all workers.

The share of workers in service-producing industries and in professional jobs has increased moderately over time. In 1997, 77 percent of workers in the data were employed in service-producing industries. In 2014, the share had increased to 82 percent. During the same period, the share of workers in professional occupations rose from 36 percent to 41 percent.

Composition effects on median wage growth
Individually, an aging workforce is putting downward pressure on wage growth, whereas rising education levels are adding upward pressure. The rising share of workers in professional occupations is also pushing wages up somewhat, although the impact of the rising share of workers in service-producing industries is ambiguous. But how large are these effects when combined?

To get an idea, we conducted two counterfactual experiments. First, we held fixed the age and education distributions at their 1997 levels (the first year in our Wage Growth Tracker data). Second, we held fixed the age, education, industry, and occupation characteristics at their 1997 levels. We used three age groups (16–24, 25–54, and 55-plus years of age), two education groups (college degree and no college degree), two industry groups (service- or goods-producing industries), and two occupation groups (professional and other occupations).

The blue line in the next chart is the median wage growth over time with no adjustments for changes in composition. For example, for 2014, the chart shows median wage growth of workers in the data set with earnings in January 2014 and January 2013, February 2014 and February 2013, etc. This depiction is the Atlanta Fed Wage Growth Tracker, but at an annual frequency. The other two lines show the results of the experiment: demographically adjusted (green) and both demographically and job adjusted (orange).

Conclusion
These experiments suggest that—for our data set, at least—the impact on the median of the wage growth distribution from shifts in the composition of the workforce and jobs over time has increased in recent years, but the impact is not especially large. For example, the unadjusted median wage growth for 2014 is 2.5 percent. Holding fixed all four characteristics at their 1997 levels would have raised this by only 0.2 percentage point. Shifting worker and job characteristics are not a primary explanation of low median wage growth since 2009.

 

July 15, 2015 in Employment, Labor Markets, Wage Growth | Permalink | Comments (0)

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