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Comparing the U.S. dollar with other currencies

One way to assess the performance of the U.S. dollar is to compute an index of other countries’ currencies, with each one weighted according to how much the U.S. trades with that country. The graph shows two versions of such an index: The “real” index factors in the evolution of prices in each country, essentially accounting for deviations from the long-run equilibrium. The nominal index makes no such adjustment and reflects the typical market listings of foreign exchange rates. The graph makes clear that the U.S. dollar has appreciated in the long run against the currencies of its major trading partners. For example, the dollar appreciated recently when euro area countries had their debt troubles and the dollar became a refuge for investors and consumers. The graph also shows how the two indexes have been basically parallel since the mid-1990s, reflecting the convergence of inflation rates across major economies after the creation of the euro.

How this graph was created: Search for “trade weighted index broad” and select the two monthly indexes.

Suggested by Christian Zimmermann

View on FRED, series used in this post: TWEXBMTH, TWEXBPA

FOMC projections

Four times per year, the FOMC releases economic projections for overall personal consumption expenditures inflation, core personal consumption expenditures inflation, real gross domestic product growth, and the unemployment rate. These projections are commonly known as the Summary of Economic Projections (SEP) and are offered in a variety of ways: as the range of predictions and as the central tendency of predictions, in the short run (one, two, or three years out) and in the longer run. One of the more interesting ways to use the SEP release is to compare forecasts over time.

With ALFRED (our archival FRED database), these comparisons are easy to make. This graph shows how the real GDP growth rate forecasts for 2008, 2009, and 2010 have been revised across three consecutive SEP releases (or “vintages”): November 2007 in blue, February 2008 in red, and May 2008 in green. The FOMC twice lowered the projected real GDP growth rate for 2008 and once lowered the projected growth rate for 2009. The projected growth rates for 2010 were raised across all three releases.

How this graph was created: Place the series “GDPC1CTM” into an ALFRED graph three times: Within each data series setting, select the appropriate vintage. Limit the time range using the scroll bar below the plot area.

Suggested by Katrina Stierholz and Keith Taylor.

View on FRED, series used in this post: GDPC1CTM

How big is the federal government?

One way to determine the size of the U.S. federal government is to look at its expenditures. Of course, population and the economy have grown, so it’s a good idea to use a ratio to measure expenditures. For example, you can divide expenditures by GDP, and this is exactly what is shown here. (One detail to pay attention to: This graph uses nominal values—at current prices—for both series.) The graph shows the huge government buildup during WWII, almost doubling in 1942, and its equally impressive contraction thereafter. Since then, the size of the government has fluctuated between 17 percent and 23 percent of GDP, with another recent buildup that looks ready to melt away if the trend continues.

How this graph was created: Select the series “Federal Government Current Expenditures,” then add the series “Gross Domestic Product” to series 1. Apply data transformation “a/b” and then select graph type “bar” in the graph settings.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: AFEXPND, GDPA

The comovement of investment and GDP

There’s much more to the business cycle than fluctuations in GDP. There are all sorts of other variables that comove (that is, that fluctuate in more or less systematic ways) with GDP. It’s easy to understand that, when GDP is going up, the unemployment rate often is going down. Other series that comove may not be so easy to see.

Here we use a scatter plot (instead of a line graph) to show comovement between GDP and private investment. The cloud of points is clearly following a lower-left to upper-right path, which shows positive comovement. (Economists like to say that private investment is procyclical.) Note also that the range of the growth rate for private investment on the y axis is much wider than that for GDP on the x axis, reflecting that investment is much more volatile than GDP.

How this graph was created: Search for and select “Real Gross Private Domestic Investment,” then add the series “Real Gross Domestic Product.” Apply “Percent Change” to both series and select “Scatter” in the graph settings. If you wish, reduce the width of the lines in the settings of the first series.

Suggested by Christian Zimmermann

View on FRED, series used in this post: GDPC1, GPDIC1

The rise of education and health services

There’s little doubt that the prices of education and health care have risen considerably over the past decades. One reason for this is that more and more people work in these fields. The graph displays the share of workers in the education and health services sector among all employees: The share was about 4 percent in the 1940s and is now above 15 percent. Note also that this sector appears to be quite recession-proof: The share has gone up in all recent recessions, mostly because general employment declined while this sector’s employment did not. Interestingly, the employment share systematically stays up when the recession is over.

How this graph was created: Search for and select “All Employees: Education and Health Services,” and then modify the existing series by adding the “All Employees: Total nonfarm” series and applying the data transformation “a/b.” Choose graph type “Area” in the graph settings.

Suggested by Christian Zimmermann

View on FRED, series used in this post: PAYEMS, USEHS

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