Federal Reserve Economic Data

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Posts tagged with: "CPIAUCSL"

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Wages with benefits

Nominal wages generally increase, but the picture is mixed for real wages. The green line in the top graph shows real wage growth, which is negative a fair amount of the time. Bursts in inflation can counteract the usually small increases in nominal wages. In fact, the strong growth of real wages at the end of the past recession is mostly due to a short episode of deflation.

But wages aren’t the whole story. A job usually also involves other types of compensation, such as the employer’s contribution to retirement pensions, health and life insurance, paid vacation and other leave, and any taxes the employer pays on these benefits. These benefits are now a substantial part of the cost of an employee, and they appear to be growing. The top graph shows that labor compensation growth is frequently higher than real wage growth. We can make this point more clearly by using index values: In the bottom graph, we set both series at 100 in 1970 and let them run. Real compensation growth is significantly higher: the 60% increase looks much better than the 3% increase for real wages.

How these graphs were created: Search for “real compensation” and click on the series shown. In the “Edit Graph” panel, add a new line by searching for “hourly earnings.” Then, within the same panel, add a series by searching for “CPI.” Apply formula a/b to the second line to make earnings real. For the first graph, set units for both lines to “Percent Change from Year Ago”; for the second line, you do this at the bottom of the panel. For the second graph, the selected units are “Index (scale value to 100 for chosen period)”; set the date as 1970-01-01.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: AHETPI, CPIAUCSL, RCPHBS

Testing theory: marginal product and wages

Economic theory tells us that, in a perfectly competitive labor market, labor should be paid according to its “marginal product.” Now, without the jargon: The last workers to be hired by a business should receive pay that is equal to their contribution to the output of that business. So, let’s compare the data with the theory…

Unfortunately, we have no data on the marginal product. But fortunately, we have data on average product. Although it’s not a certainty, these two products should be correlated. So, the graph above shows real growth rates for average product and the average wage. But again, there’s a limitation to the data: We must use the wage of production workers only if we want a series that’s long enough to compare with average product.

Ultimately, it doesn’t look like these series are closely related. The two data limitations we have here could be undermining the relationship. Or the labor market could be less than perfectly competitive. Or the theory could be wrong. It’s difficult to say. But such is the life of an economist… For some more-rigorous research on this topic, take a look at this recent Economic Synopses essay.

How this graph was created: Search for “real output per hour” and select the series shown here. In the “Edit Graph” panel, add the next series by searching for “average hourly earnings” and taking the series with the longer duration. Then modify this series by adding the CPI data series and applying the formula a/b. Select “Percent Change from Year Ago” as the units.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: AHETPI, CPIAUCSL, PRS84006091

The Great Recession and trade collapse: Comparing Missouri and the nation

The Great Recession (Dec. 2007 to June 2009) not only shrunk U.S. GDP and employment levels, but also dramatically diminished international trade. This trade collapse was both national and global. But it also had regional effects. So we highlight the trade collapse’s effect on the state of Missouri and compare that with the decline for the U.S. as a whole.

The graph above maps the number of exporting firms, which is a measure of the extensive margin for exports. The graph below maps average export revenues, which is an approximation of the intensive margin, which refers to an individual firm’s exports. The total real value of U.S. exports dropped 17.9 percent between 2008 and 2009. The number of U.S. exporting firms and the real value of average exports dropped by 4.5 percent and 14.1 percent, respectively, during the same period. Missouri saw much sharper declines over the same period: 25.4 percent (total exports), 6.6 percent (number of exporting firms), and 20.2 percent (average exports).

What is intriguing is that changes to the number of exporting firms in Missouri roughly align with the national situation, but Missouri’s average export revenues exhibit some interesting differences. The nation’s average export revenues peaked in 2007, fell slightly in 2008, fell sharply in 2009, and smartly recovered after that. Missouri’s average export revenues, on the other hand, peaked in 2006 and then fell quite sharply until 2009; then they had a rather anemic recovery after that. This stark difference in Missouri’s intensive margin (relative to the nation) is worthy of further attention.

How these graphs were created: For the top graph, search for and select “number of exporters to all countries from the United States” and use the “Add Data Series” option to search for “number of exporters to all countries from Missouri” and add that series to the graph. Place the Missouri series on the right y-axis. For the bottom graph, search and select “CPI all consumers”: Under the “Frequency” menu, select “Annual.” Under the “Units” menu, select “Index (Scale value to 100 for chosen period)” and set the “observation date” to 2009-01-01. This preliminary step is necessary to report the value of exports in 2009 dollars. Now modify the existing series by adding two series, “value of exports to all countries from the United States” and “number of exporters to all countries from the United States,” through the “Add Data Series / “Modify Existing Series” options. Finally, use the “Create your own data transformation” option and insert the formula (b/a)*100/c. Repeat the same steps with the corresponding Missouri series and place this new series on the right y-axis.

Suggested by Subhayu Bandyopadhyay and Rodrigo Guerrero

View on FRED, series used in this post: CPIAUCSL, MOWLDA052SCEN, MOWLDA475SCEN, USWLDA052SCEN, USWLDA475SCEN


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