Why Did Our Unemployment Rate Change?

You may have noticed that your recent historical unemployment rate numbers look different—very different—compared to how you remember them looking just a few months ago. If you’ve noticed this, you’re not alone.

With the publication of 2015 unemployment rate data, the Bureau of Labor Statistics implemented its “2015 LAUS Redesign,” a set of methodological changes in their Local Area Unemployment Statistics program (LAUS). In conjunction with this, local unemployment rate estimates for the period 2010 to 2014 were revised and rereleased.

At the county level, the impact on the numbers ranged from slight to eye-popping. And while smaller regions tended to have more dramatic adjustments, even some large areas saw fairly significant revisions.

For example, the monthly unemployment rate estimates for 2010 to 2014 in Marion County, Indiana (Indianapolis) were revised upward an average of 0.6 percentage points. Miami-Dade County, Florida, on the other hand, saw an average 1.1 percentage point decrease for its unemployment rates over the same period.

Other examples of increased estimates included Sumter County, Florida (+3.1 percentage points on average) and Clarke County, Alabama (+3.6 percentage points). At the county level, the largest average increase in monthly unemployment rates happened in Lake and Peninsula Borough, Alaska, with a whopping 7.0 average percentage point revision.

Places with downward revisions from 2010 to 2014 included York County, South Carolina (-1.8 percentage points) and Santa Cruz County, Arizona (-2.0 percentage points). The largest overall drop happened in Chattahoochee County, Georgia, where the monthly unemployment rates were revised downward an average of 5.6 percentage points for the period.

You can use the tools and charts above to select your region, see how your unemployment rate estimates were changed, and compare the scale of these changes with revisions in other regions.

The data used in the above charts—as well as in all the comparisons made in the above text—are based upon the LAUS release of April 29, 2015 compared with data from February 4, 2015, the date of the last release before the revisions were implemented.

Economic Impact: Worker Productivity Growth Might Influence Fed’s Interest Rate Policy

Taking a look at worker productivity growth could shed some light on what the Federal Reserve might do with interest rates.

The faster the rate of productivity growth, the faster the Fed can let the economy grow without inflation picking up.

But productivity is slow right now compared to historical benchmarks.

By definition, growth in productivity means the same amount of output can be produced with fewer hours, which sometimes translates into fewer workers. Over the long run, this often means the workers who remain in the industry are paid more.

Productivity growth leads to rising living standards.

Yet, it also is a double-edged sword as workers who lose their jobs due to productivity improvements need to find employment elsewhere.

Productivity growth also is an important contributor to how fast the overall economy can grow. It is an important driver of what the Federal Reserve has referred to as the maximum sustainable growth rate or potential growth rate of real gross domestic product.

Productivity in manufacturing grew 2.4 percent in the fourth quarter of 2014 compared with the same quarter in the previous year while mining industries productivity grew 3.9 percent in 2014, according to the U.S. Bureau of Labor Statistics.

About 75 percent of manufacturing and mining industries posted gains in 2014 compared with about 60 percent in 2013.

Productivity grew the fastest in 2014 in oil and gas extraction category followed by textile and fabric finishing and coating mills.

The potential growth rate varies over time and is dependent on productivity and labor force expansion.

A simple way to estimate the potential growth rate is to add the annual productivity growth rate, which was 0.9 percent from 2008 through 2014, with the labor force growth rate of 0.5 percent during that same period.

As a result, the potential growth rate of real gross domestic product was 1.4 percent during that period.

That is much slower than the 3.3 percent average potential GDP growth rate from 1950 through 2014.

During that time, productivity averaged a faster 1.8 percent a year and the labor force grew an average annual 1.5 percent.

Looking ahead, the Congressional Budget Office is estimating productivity to grow 1.6 percent and the labor force to advance 0.5 percent a year from 2015 through 2025.

That would equate to a potential growth rate of 2.1 percent a year.

In other words, growth in living standards could be much slower over the next decade than it was over the last half century.

In addition to predicting changes in living standards, the difference between the potential growth rate and projected GDP growth is considered by the Federal Reserve when it decides whether to try to speed up or slow down economic growth to meet its long-term goals.

The Federal Reserve tends to increase the overnight interest rate that banks charge each other, known as the Federal Funds Rate target, when the economy is consistently growing faster than it potentially should and to lower this rate when the economy is growing too slow.

Despite an anemic 0.2% real GDP growth in the first quarter of 2015, many economists are looking for about 3 percent GDP growth in the second half of 2015 and in 2016, which provides another reason why the Federal Reserve will likely be increasing the federal funds rate target later this year.

Shift in Mix of Industries Contributed to the Slow Wage Growth in 2014

After adjusting for inflation, annual average wages for workers in the United States grew a meager 0.3% between 2013 and 2014. In contrast, annual average wages grew at an annualized pace of 3.5% between 2001 and 2007 (also inflation adjusted).

Is recent slow wage growth a result of firms being stingy with raises, or is it due to other factors? Chmura’s analysis shows that a shift in industry mix towards lower-paying sectors was a major driver of the relatively slow wage growth.

To examine the recent slow wage growth, we will split that growth into two contributing components:

  1. Changes in pay within individual industries, and
  2. Shifts in employment share represented by the percentage of workers in that industry. For example, if employment in an industry expands, but grows more slowly than other industries, its share of regional employment may decline.

Looking at 2014 annual wages in a state as if the 2013 industry mix was constant and comparing that to actual 2014 wages illustrates how much of the actual change in wages was due to the shifting mix of employment by industry. Virginia and North Dakota provide contrasting examples of the changes in industry mix and their effect on wage trends.

In Virginia, major sectors paying below-average wages per worker—such as accommodation and food services, health care and social assistance, and retail trade—gained a greater share of employment. Meanwhile, employment in many sectors that tend to pay above-average wages—especially professional, scientific, and technical services as well as public administration—declined relative to their share of employment in 2013. Overall, the change in industry mix reduced wages by an average $202 per worker in Virginia.  

In North Dakota, however, industries like construction; mining, quarrying, and oil and gas extraction; and transportation and warehousing—which pay an above-average wage in the state—gained employment relatively faster than lower-paying industries such as health care and social assistance and accommodation and food services. As a result, the change in industry mix boosted wages by an average $446 per worker in the state.

The map and chart below detail how the shifting industry mix has contributed to the change in average annual wage growth in each state. A negative value (shown in red on the map) indicates that below-average wage industries have gained a larger share of employment in the state in 2014, while a positive value (in green) indicates that higher-wage industries gained relatively more employment.

Data on industry sectors are also included in the chart to illustrate which industries gained or lost employment share in the nation or state of interest over the past year, and which of these pay above-average or below-average wages.

Economic Impact: Wage Gains Remain Elusive

Slow wage growth is one of the side effects of a weak labor market.

Even though the U.S. unemployment rate has fallen to 5.5 percent in February, the rate that includes people working part time who would rather work full time and the marginally attached is 11.0 percent.

With plenty of jobseekers to choose from, firms have been stingy with wage increases.

From 2009 (the year the recession ended) through 2014, annual average wages in the Richmond metro area rose 1.7 percent.

That’s slightly better than the 1.6 percent in Virginia but not as good as the 2.2 percent growth in the nation.

Over that same period, inflation rose an average 2.0 percent a year.

From that perspective, the purchasing power of consumers in Virginia fell over that period and barely rose in the nation. That may partially explain why retail sales have not been as strong as many observers expected with the declines in gasoline prices.

Wage gains in some industries have kept pace with inflation.

Annual average wages in the finance and insurance industry rose a respectable 5.4 percent over the last five years in the metro area followed by an average 4.6 percent for mining and quarrying and 3.3 percent for real estate.

In contrast, wages in the arts and entertainment industries grew an annual average 0.7 percent in the region and the state to make it one of the slowest growing industries over the period.

Wage growth was much stronger in the five years before the recession.

From 2002 through 2007, annual average wages rose 4 percent in the Richmond region and 4.3 percent in the state. The wage increase is better than the average 2.9 percent rise in inflation during the same period.

Labor markets were tight just before the recession started. The unemployment rate in the nation hit a low of 4.4 percent in 2007. The metro area and state saw an even lower 2.9 percent during that same year.

Slack in the labor market is not the only factor that impacts wage growth in a region. The changing mix of industries also is important.

During the five years before the beginning of the last recession, professional business services firms added more than 76,000 jobs to the state. That was nearly 30 percent of all new jobs.

That sector, which is dependent on federal contracting, paid an average annual wage of $82,790 in 2007 — 180 percent higher than the average of all jobs in the state.

In contrast, professional business services added a little less than 9,000 jobs since the recession ended or 8 percent of all jobs created in the state.

In both the Richmond metro area and the state, the health care and social services sector added the most jobs over the last five years.

Although those jobs made up 35 percent of total employment gained in the metro area and state during that period, the average wage in the sector is 7 percent below the metro average and 12 percent below the average in the state.

The next three largest employment gains provided a little more than half of the jobs in the metro area and state. Each of these three sectors — retail, arts and entertainment, and accommodation and food services — paid less than half the annual salary of all jobs in 2014.

As the labor market continues to improve, annual average wage gains will start to accelerate.

That trend has begun to emerge in the Richmond metro area. State wage growth remains slow, partially because of the slow employment growth in the federally-dependent professional business services sector.

Much of the Nation Still Waiting to Grow Beyond Recovery

As of April 2014, employment in the U.S. economy exceeded the 138.35 million jobs that existed when the recession began in December 2007. Employment in more than a third of the U.S. metropolitan areas, however, has yet to reach the same levels of employment they experienced in December 2007.

While national employment describes the recovery in aggregate, not all metropolitan statistical areas (MSAs) are recovering at the same pace. In Texas, for example, many MSAs dipped briefly below pre-recession levels before recovering and expanding, likely buoyed by oil production. The Washington, D.C. area also recovered fairly quickly, supported by federal stimulus money going to a relatively higher concentration of federal contractors in the region.

In contrast, no MSAs in Arizona have recovered to December 2007 employment levels, and conditions vary considerably in the state. The Phoenix area has added an average of 4,475 jobs each month (about 0.2% of total employment) over the last twelve months of available data; at that rate, the region could recover to December 2007 levels of employment in about seven months. The Tucson area has added an average of 317 jobs (about 0.9% of employment) monthly over the past year—but at that rate, it would take the region another four years or more to fully recover recession job losses.

While most of the largest metro areas have reached pre-recession levels of employment and continue to expand, the map shown below indicates that many MSAs are still waiting to get back to the employment levels that existed over seven years ago.