The FRED® Blog

Is the PPI going crazy?

Posted on November 12, 2015

The graph above shows the producer price index since 1913. It measures the cost of items used in the production process and is thus different from the consumer price index, which measures the cost of final goods to consumers. Two aspects of the graph are striking: Prices have increased quite a bit since 1913, and prices in recent years seem to be subject to wild fluctuations. There’s no doubt the ups and downs of commodity prices such as oil and metals have an effect here, but are the recent years really as wild as they look?

In part, the second observation is a consequence of the first. Prices now are roughly 18 times greater than those in 1913. So a 1% increase will look 18 times larger now than before. This “optical illusion” can be fixed in two ways. 1. Look at percent changes. The first graph below shows these changes from the same month a year before, which takes care of any potential seasonal effects. Recent fluctuations are indeed somewhat larger than in preceding decades, but they’re nowhere close to the large fluctuations in the first years of the series. 2. Look at natural logarithms. The second graph below includes a transformation so that any change in the series looks the same in relative terms: that is, a 1% increase looks the same in 1913 and 2015. Again, we see that the fluctuations were much larger in the early years.

How these graphs were created: Search for and select the PPI for the first graph. Change the units to “Percent Change from Year Ago” and you have the second graph. For the third graph, start with the first graph, choose “Create your own data transformation,” and select “Natural Log” among the transformations.

Suggested by Christian Zimmermann

View on FRED, series used in this post: PPIACO

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

Posted on November 9, 2015

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

Contrasting the U.S. and German unemployment rates

Posted on November 5, 2015

FRED’s rich set of international indicators allows us to compare the behavior of different countries over time. Here we contrast the behavior of unemployment in the U.S. and Germany. We use the OECD’s harmonized data series for both countries so that the population definitions are the same: Working age population = Active population + Inactive population. Active population = Employed population + Unemployed population. The harmonized unemployment rate is defined as the ratio of unemployed population to active population, and the resulting series are plotted in the graph. (The shaded recession bars for the U.S. are from the NBER and for Germany are from the OECD.) The data go back to 1991, but this graph starts in 2003, the period after the so-called HARTZ labor market reforms in Germany.

The graph highlights huge differences in the behavior of the two unemployment rates. In 2003 and 2004, Germany, but not the U.S., was in a recession. Its unemployment rate was much higher than—and for a while, double—the U.S. unemployment rate. But since the implementation of HARTZ IV, the German unemployment rate has been falling. HARTZ IV significantly reorganized and reduced the unemployment insurance program and narrowed the eligibility criteria. More interestingly, although both the U.S. and Germany entered recession around the same time in late 2007/early 2008, the two unemployment rates behaved quite differently: The U.S. rate skyrocketed and remained persistently high; the German rate kept declining for a while, had a relatively modest increase, then had a similar decline as before. By the end of the sample, the two countries had switched places: The U.S. looked like Germany and Germany looked like the U.S. in the early 2000s.

How this graph was created: As noted above, we want comparable unemployment series. We use the OECD harmonized series for the U.S.: USAURHARMMDSMEI. Add this series to a graph. Next, add the comparable German series by using the “Add Data Series” menu below the graph to search for and select DEUURHARMMDSMEI. Finally, add the indicator for Germany’s recessions: DEUREC. To make the graph more readable, use the right axis for this third series. Also, don’t forget to start the graph in 2003.

Suggested by Alexander Monge-Naranjo and Faisal Sohail

View on FRED, series used in this post: DEUREC, DEUURHARMMDSMEI, USAURHARMMDSMEI


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