The FRED® Blog

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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Transportation indexes

FRED recently added a set of transportation services indexes from the U.S. Department of Transportation. The freight index covers all domestic transport of commercial freight, including pipeline movements for oil and gas. It does not cover in-house trucking, courier, or postal services. The passenger index covers local public transportation (except taxi) and intercity rail and air transportation. (The FRED Blog previously discussed miles traveled, which covered personal transportation by automobile.) The graph shows freight transportation declining more than passenger transportation during the past recession; in the previous recession, passenger transportation suffered more.

How this graph was created: Look up the Transportation Services Index (TSI) and select the three indexes.

Suggested by Christian Zimmermann

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Renting and owning homes

It should not surprise anyone that the homeownership rate has declined nationwide in the most recent years after a large number of foreclosures. Many former homeowners must have moved into rental units, pushing down the rental vacancy rate, as seen in the graph. What is surprising is that the homeowner vacancy rate is actually declining as well. How could this happen? Was the housing stock significantly reduced? Did homeowners become renters of the same home? Has there been significantly more household creation? Anything else?

How this graph was created: Search for one of these series, then add the other. For the homeownership rate, check “right” for the Y-axis position.

Suggested by Christian Zimmermann

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The importance of migrant remittances

Many migrant workers systematically send some money back to their home countries to family members who could not follow them or others they know. How important is this source of income for these home countries? Hard to say. But the graph offers three examples, which offer three quick takeaways: 1) remittances can make up a significant share of local GDP, 2) they appear to be growing, and 3) they can be quite variable. We can speculate that this last point may involve adverse consequences, but also that Moldova (for one) is better off with remittances than without.

How this graph was created: Search for “remittances,” pick your countries, and add them to a graph.

Suggested by Christian Zimmermann

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On financial stress

The past recession highlighted the financial sector’s role in the economy, specifically that its health can affect economic fluctuations. It is not as easy to see how well this sector is doing now, as there are many, many indicators. (The FRED database is testimony to that.) So it is useful to look for a summary indicator, and three Federal Reserve Banks provide one: The Cleveland, Kansas City, and St. Louis Feds each offer their own financial index to measure the stress or uncertainty within the financial sector. Each draws on different data, uses different methodologies, and emphases different factors. Of course, the indexes can incorporate only tangible information to measure something more or less intangible, so they are going to be imperfect. Still, as the graph shows, they correlate remarkably well.

How this graph was created: Search for “financial stress index” and select the three series. Click “add to graph.”

Suggested by Christian Zimmermann

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Oil prices and business fixed investment in structures

Most economists believe lower oil prices are positive for the economy: They lead to lower gasoline and diesel prices, which tend to reduce headline inflation, which increases consumer purchasing power. Lower oil prices also tend to reduce operating expenses for transportation firms, such as airlines, trucking, and delivery services. The sharp drop in crude oil prices since mid-June 2014 is generally expected to produce positive (if temporary) economic effects. Lower oil prices generally don’t benefit energy producers, but the vast majority of households, firms, and organizations are net consumers, not net producers; so, lower prices still tend to bring net benefits.

One way the effects of lower oil prices reveal themselves is through mining activity. (More precisely, “real private nonresidential fixed investment in mining exploration, shafts, and wells.”) In 2013, fixed private investment in mining activity was about 5 percent of total fixed private investment and only 0.8 percent of real GDP. Still, since the third quarter of 2009, mining activity has increased at a 17.1 percent annual rate—much faster than the 5.5 percent rate of gain in total fixed private investment.

As the graph shows, mining activity (which includes drilling) is positively correlated with crude oil prices. When oil prices rise, this activity increases and so does investment in it. When oil prices fall, this activity slows and investment in it falls.

How this graph was created: Search for mining investment to find the first series, then add “Crude oil prices WTI” for the second. Limit the sample to start in 1999.

Suggested by Kevin Kliesen

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Of sticky and flexible prices

The consumer price index (CPI) is composed of many prices with wildly different characteristics. One dimension in which they can differ is how frequently they change. Everybody is aware that gasoline prices can change daily. Other prices may not even change every year, such as administrative fees. To highlight the difference between these extremes, the Federal Reserve Bank of Atlanta produces separate indices for goods that have flexible prices on the one hand and sticky prices on the other hand. The graph above clearly shows that flexible prices have a much wilder ride. The sticky price index is informative even if doesn’t move much, though. Indeed, it can reflect longer trends in inflation, and these are the ones everyone cares more about.

How this graph was created: Go to the Sticky price CPI source, select the sticky and flexible consumer price indices (percent change from year ago), and add them to the graph.

Suggested by Christian Zimmermann.

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How fast has the unemployment rate declined?

One way to compare recessions is to compare their unemployment rates, and the graph above includes the civilian unemployment rate for the four most recent business cycles. In this case, index values are used to show how the rate for each cycle changed in comparison with the highest rate that occurred in that cycle. (The graph shows each cycle’s unemployment rate relative to the highest rate in that cycle, which has an index value of 100.) None of the four rates seem to stand out; they all follow a similar path downward. But we know that the last cycle’s unemployment rate went higher than any of the others. So, that must mean the most recent unemployment rate declined faster in absolute terms (the actual percentage unemployment rate) because it hit a higher point than any of the other rates but still had a relative decline similar to the other rates.

How this graph was created: Find the “Civilian Unemployment Rate,” then select “Index (Scale value to 100 for chose period)” under Units. Then choose the data to match the highest unemployment rate in the previous cycle. Finally, check “Display integer periods” with values 0 and +60. Add the civilian unemployment rate three more times to the graph (it is preselected) while including the different dates that correspond to the highest value in each of these three earlier cycles.

Suggested by Christian Zimmermann

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Bank failures

The previous recession was clearly associated with substantial problems in the financial sectors. As the graph shows, there has been a significant number of bank failures, as recorded by the Federal Deposit Insurance Corporation (FDIC), which is responsible for managing the closure process and insuring depositors. The number of failures, however, is nowhere near the peak around 1989, the time of the savings and loan crisis. The recession around that time involved different financial problems and thankfully was much less deep than the previous recession.

How this graph was created: Search for “bank failures” and then change the graph type to “Area” under graph settings in the graph tab.

Suggested by Christian Zimmermann

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