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Is Inflation Running Hot or Cold?

One popular measure of the price level is the consumer price index (CPI), which measures the average change over time in the prices paid by urban consumers for a market basket of goods and services. This index can be broken down into smaller component indexes, each representing a different subset of goods and services. So changes in the aggregate price level can be traced back to changes in the price levels of the underlying components. As described in a recent Economic Synopses essay, we have developed a “heat map” that visually represents CPI data in FRED: specifically, the relative inflation levels of various CPI components over the past 10 years. The heat map shown here lists the components in order according to their weight in the overall index as of July 17, 2015.

2015 July 20 FRED Blog post heat map x800

How this heat map was created: We used the FRED Add-In for Microsoft Excel (view instructions for installing the Add-In here) to download the FRED data: year-over-year percent change in each CPI component index over the past 10 years. We normalized each value by subtracting the series mean and dividing by its standard deviation calculated over the past 10 years to take into account differences in long-term trends and volatility across series. Each colored box in the heat map corresponds to the normalized inflation value for a given CPI component for a particular month. Blue represents an inflation value below the long-term trend of the index, and red represents an inflation value above the long-term trend. The darker the color, the greater the difference between that particular inflation value and the long-run average for the component index in terms of standard deviations.

Because we’re comparing series against their long-run averages, it’s possible for a “blue” series to have a higher inflation rate than a “red” series. For example, for June 2015, owners’ equivalent rent is red, with an inflation value of 2.95 percent; water, sewer, and trash is blue, and yet has a higher inflation value of 4.65 percent. The reason is that the June 2015 owners’ equivalent rent inflation is above its 10-year average of 2.16 percent; and the June 2015 water, sewer, and trash inflation is below its 10-year average of 5.11 percent.

An Excel file containing a version of this heat map can be found here, and anyone who downloads the FRED Excel Add-In has the ability to easily update the heat map when new data are released. Simply select the tab containing the raw data and press the “Update Data” button from the FRED Excel Add-in. (More instructions and details are provided in the Excel file.)

Suggested by Joseph T. McGillicuddy and Lowell R. Ricketts.

View on FRED, series used in this post: CPIAPPNS, CPIAUCNS, CPIEDUNS, CPIENGNS, CPILFENS, CPIRECNS, CPIUFDNS, CUUR0000SAF116, CUUR0000SAG1, CUUR0000SAH3, CUUR0000SAM1, CUUR0000SAM2, CUUR0000SAS4, CUUR0000SEGA, CUUR0000SEHA, CUUR0000SEHB, CUUR0000SEHC, CUUR0000SEHG, CUUR0000SETA01, CUUR0000SETA02

Wage stickiness

Unemployment has been a fixture in the news since 2008, but relatively little has been said about wages. So how have wages changed as the U.S. has weathered the Great Recession and the spike in unemployment? Most people would expect that wages have decreased, but data in FRED offer a different perspective. The graph above shows two time series from the Bureau of Labor Statistics: unemployment (red line) and private industry wages and salaries (green line) from the employment cost index. Note that even when unemployment rapidly doubled, the green wages line continued to rise (albeit at a reduced rate). In other words, as the economy contracted and employers sought to cut costs, they almost exclusively opted to lay off workers rather than negotiate for lower wages. This phenomenon is known as downward nominal wage rigidity: During macroeconomic shocks such as recessions, wages remain “sticky.” Of course, it’s possible that inflation is cutting real wages even if nominal wages aren’t changing. However, when we adjust the wages data for inflation in the graph below (blue line), the pattern remains similar. Although real wages posted a slight decline several years after the recession hit, it pales in comparison to six years of elevated unemployment.

How these graphs were created: For the first graph, search for and add the unemployment series (left y-axis) and the total wages series (right y-axis). For the second graph, add the wages series (a) and the consumer price index (b) as parts of a single data series. Do this using the “Modify Existing Series” option within “Add Data Series.” Set the units for both (a) and (b) to “Index” with the observation date equal to 2007-11-01. Then, in the “Create your own data transformation” option, enter “(a/b)*100” in the formula box and apply the transformation. For the trend line, choose “Trend Line” under “Add Data Series” and set the start date to 2007-10-01. Set both the start and end values to 100.

Suggested by Ian Tarr.

View on FRED, series used in this post: CPALTT01USM661S, ECIWAG, UNRATE

Public pensions

Some cities and states, such as Detroit and Illinois, are struggling to fund their public-sector employee pensions. These crises may have seemed abrupt, but we can observe some structural causes using FRED. In the graph above, the blue line shows pension benefits paid to public-sector employees; the red and green lines show contributions from employers and employees. Adding the two revenue streams (red and green lines) creates the purple line. Note how the purple revenue line dipped below the blue payouts line in the mid-1990s and never fully rebounded. When the Great Recession hit in 2008, revenues dropped dramatically and payouts continued to rise. The graph below shows the resulting gap between pension payouts and contributions has increased markedly since the past recession.

Elected officials hoped for higher future dividend and interest income to close this gap; but cities and states typically invest pension contributions in very safe assets, which have underperformed. The graph below shows that rates on 10-year Treasuries (the epitome of safe pension fund investments) have reached all-time lows since the past recession. So pension funds are being squeezed from both directions: Payouts rose faster than contributions, and returns on investments fell. Cities and states usually cannot revise or renege on benefits promised to their pensioners because pensions are often rigidly guaranteed in city charters and state constitutions. Elected officials will try to find new ways to shore up pension funds, but Baby Boomer retirements won’t make that task any easier.

How these graphs were created: First graph: Add the first series (benefits) to the graph, then add the second (employer contributions) and third (employee contributions) series to the graph with the “Add Data Series” feature. To create the fourth series, start by re-adding the second series to the graph and then adding the third series by using the “Modify Data Series” option. Then, with the “Create your own transformation” option, add employer (a) and employee (b) contributions by using “a + b” in the formula box. Second graph: Start by adding benefits (a) to the graph, then use the “Modify Data Series” option to add employer (b) and employee (c) contributions as components of one data series. With the “Create your own transformation” option, use “(b + c) – a” in the formula box and change the graph type to “Area.” Third graph: Simply search for and add the “10-Year Treasury Constant Maturity Rate” series to the graph.

Suggested by Ian Tarr.

View on FRED, series used in this post: GS10, S121000A144NBEA, S251100A144NBEA, S251200A144NBEA


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