The FRED® Blog

Where are the teenage employees?

When I was in high school, I had a job. As you can see from the graph above, up until 2001, over 50% of teenagers had jobs. Since then, the percent of teenagers employed—including part-time jobs—has declined and continues to decline. The most recent labor force participation rate for 16- to 19-year-olds is at just under 35%. Likely, most parents and teenagers see school as the first priority, as the rewards from finishing school have grown. Many years ago, teenagers participated in the labor force at a higher rate than adults over 55 years of age. But the percent of workers aged 55 and over has risen by almost 10% since then, at least in part because they are in better health during those later years and many retirees seek what they did as teenagers: part-time jobs.

How this graph was created: Search for “Civilian Labor Force Participation Rate” and then filter for the tag “sa,” which is “seasonally adjusted.” (NOTE: The seasonality of teenage employment is pretty extreme due to summer jobs.) And choose the ages 16-19 and over 55.

Suggested by Katrina Stierholz

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Manufacturing is growing, even when manufacturing jobs are not

The role of manufacturing in the U.S. economy is often discussed. As shown in the FRED graph above, as a year-over-year percent change, the level of manufacturing has generally grown. (One striking exception is during the recent recession.) The number of employees working in manufacturing is a different story, however. It has sometimes grown, but it has nearly always grown less than the growth in manufacturing. This suggests that growth in manufacturing does not equal growth in manufacturing jobs. What’s the explanation? A prime candidate is productivity growth. Another is that the sectoral mix has shifted toward industries with higher value added, such as computers and electronics. (See this previous FRED Blog post for more on this subject.)

How this graph was created: Search for “Industrial Production: Manufacturing” and “Manufacturing Employees” and add the series to the graph. Then convert both series to “Percent change from a year ago.” Finally, restrict the sample to a time period when both series are available.

Suggested by Katrina Stierholz

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More-severe unemployment in Southern Europe

“There is always someone who has it worse” is sometimes a consolation when bad things happen to you. Here, we contrast the U.S. unemployment rate with the rates in Greece and Spain. There were certainly reasons to complain about the high unemployment rates in the U.S. during the past recession, but they pale in comparison with the experiences in Greece and Spain—even outside recessions. This disparity doesn’t come from differences in definitions of unemployment, either; this graph uses the harmonized unemployment rates from the OECD, which are designed specifically to make the rates comparable.

How this graph was created: Search for “harmonized unemployment rate,” then modify the tags in the side bar to restrict the choices. Select the countries you want and add the series to the graph (using the button at the top or bottom of the list). Finally, restrict the sample period to when data are available for Greece or Spain.

Suggested by Christian Zimmermann

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Japan’s lost decades (and lost population)

After decades of high growth, Japan’s economy slowed down in the early 1990s and has never really returned to old growth rates. Many people have proposed explanations for this, and one of them is shown in the graph above: an unusual drop in the employed population, which has to do with Japan’s substantial demographic changes. The working-age population has actually been declining since 1997, with no sign of reverting soon. For economic growth to occur in this environment, productivity improvements must increase faster than the workforce decreases. These data come from the Penn World Tables, which provides main economic aggregates for almost every economy of the world, while attempting to make them comparable in definition and in measurement units.

How this graph was createdSearch the Penn World table for the “Japan” tag. Select the series and add to a graph. Select the right axis for one of the series.

Suggested by Christian Zimmermann.

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Keep the car running: retail gas sales and prices

Fuel has the reputation of being very price-inelastic: Consumption changes little even when the price changes. One way to illustrate this relationship is to compare the gasoline sales with prices. This is done in the graph above, and it is very clear these two measures move in sync. It is even more apparent if you look at their growth rates, shown below. Except for the recent recession, the growth rates are almost always very close to each other: The price swings only a little more widely, indicating that quantities respond very little to price changes.

How this graph was created: Search for one series, graph it, then add the other series. For the top graph, select the right axis for one series, as the scales are very different. To create the bottom graph, place both axes on the left and select “Percent Change From Year Ago” for both series.

Suggested by Christian Zimmermann.

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What if we priced food in gold?

Imagine paying for food not in dollars, but in gold. How different would the world be? The graph above is an attempt to depict the difference it would make to food prices. Taking the subcategory “food and beverages” in the consumer price index, we compare the price in dollars (in blue) with the price in gold (in red). The graph shows month-to-month percentage price changes. The price in gold is calculated by dividing the price index by the price of gold in dollars.

The graph makes very apparent that, if we priced food in gold, there would be wild fluctuations in those food prices. Consider the units on the vertical axis: Prices change several percent in either direction from one month to the next. But would price fluctuations really be that wild? Probably not, as it’s costly for sellers to change prices (“menu costs”) and they would make those changes less frequently than the graph shows. Yet, the essential premise remains: The Fed has a mandate to keep prices (in dollars) stable, which it can do by managing the money supply. Such stability is not possible with the gold supply. It is thus unavoidable that gold-based prices would fluctuate more.

How this graph was created: Find “consumption price index, food and beverages” and graph it. Add the same series to the graph, then add “gold price,” making sure to check “modify existing series 2.” For series 1, select units “percent change.” For series 2, apply formula “a/b” and transformation “percent change.”

Suggested by Christian Zimmermann

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Unemployment by occupation

The new FRED release tables make it much easier to find related series. One example is Table A-13 in the BLS’s household data release, which describes the employment situation by occupation. The graph here shows the unemployment rate in some occupations: Clearly, any occupation linked to producing stuff or moving it has 1) a higher unemployment rate and 2) substantial seasonal fluctuations. Also, even in the best times (booms in the summer) these occupations maintain a higher unemployment rate than others. Why is that? A similar graphical ladder exists for unemployment rates by educational attainment (discussed in a previous post on this blog), and similar factors may be at work behind this graph.

How this graph was created: Go to release Table A-13, select the relevant series, and click on the “add to graph” button.

Suggested by Christian Zimmermann

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Graphing GDP components with our new release view

FRED makes it easy to create a stacked area graph of GDP components using our new release view feature:

How this graph was created: Navigate to the gross domestic product release page using the “Releases” link on the FRED homepage. Choose “Gross Domestic Product” (page 2) and then click on the “Section 1 – Domestic Product and Income” release link. Select Table 1.1.5 and then select the “Quarterly” series (they’re all quarterly). Now you have reached the components of GDP, and the page will look like this:

Screenshot from 2014-11-20 15:13:17

From here, you can easily see the components of GDP as a hierarchy with the latest value, the previous period’s value, and the value from a year ago. Check the boxes next to personal consumption expenditures, gross private domestic investment, net exports of goods and services, and government consumption expenditures and gross investment. Then click the “Add to Graph” button.

You’ll see a line graph of the four series. Under the graph tab, expand the “Graph Settings” menu. Change the graph type to “Area” and the stacking to “Normal.” Finally, so that net exports are easier to see, expand the menu for that series and click the “move down” button.

Suggested by Keith Taylor

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Measuring labor costs

Some economic analysts are looking for signs of faster wage growth (labor costs). In their view, faster wage growth is a sign of building inflation pressures. In October’s employment report (released Nov. 7), average hourly earnings of production and nonsupervisory employees on private nonfarm payrolls rose by only 2.2 percent over the past 12 months. A rather modest increase. Although closely followed, this series excludes most employee benefits, such as employer-paid health insurance and retirement benefits.

Broader measures that better account for these benefits include the employment cost index (ECI) and compensation per hour (CPH) in the business sector, both published by the Bureau of Labor Statistics. In the third quarter of 2014, the ECI increased by 2.3 percent over the past four quarters, while the CPH increased by 3.1 percent. But these two series are also incomplete: The reason is that businesses tend to care more about unit costs: that is, costs of labor and non-labor inputs adjusted for productivity changes. For example, if compensation is increasing solely because of faster gains in worker productivity, then unit labor costs will be unchanged and a firm’s profit margins will be largely unaffected. This can be seen in the graph. After the past recession, compensation per hour was increasing, but because labor productivity was increasing by a larger amount, unit labor costs were falling.

In the productivity and costs report released earlier this month, the Bureau of Labor Statistics reported that unit labor costs in the business sector had increased by 2.4 percent in the third quarter from a year earlier. The modest acceleration in unit labor costs over the past three quarters reflects, on net, slower growth in labor productivity and slightly faster growth in compensation per hour.

How this graph was created: Search for “Nonfarm Business Sector: Unit Labor Cost.” In the “Edit Data Series” function, change the units to “Percent Change from a Year Ago.” Repeat the process by adding these series: “Nonfarm Business Sector: Compensation Per Hour” and “Business Sector: Real Output Per Hour of All Persons” (labor productivity).

Suggested by Kevin Kliesen

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Federal, state, and local expenditures

The graph above uses U.S. national income and product account data to show three shares of government expenditures—state and local, federal defense, and federal nondefense—among total government expenditures. Note that this covers only government consumption and investment, not redistribution. These NIPA data start only in 1999, but we can still see some changes, in particular that the share of state and local government expenditures has become smaller.

The graph below shows exactly the same data but in a different way. It displays the absolute numbers instead of shares. State and local government expenditures have increased slightly, while federal expenditures have increased much more.

How these graphs were created: Search for “Real Government Consumption Expenditures & Gross Investment,” select the relevant series, and add them to the graph. In the graph settings, set type to “Area” and stacking to “Percent.” For the second graph, set type to “Bar” and stacking to “None.”

Suggested by Christian Zimmermann

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