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The Beveridge curve

What’s new in FRED? Beyond the pie charts we saw on the blog a week ago, FRED also features scatter plots, like the one shown here. The classic scatter plot used in economic analysis is the Beveridge curve, which describes the dynamics of the labor market through the business cycles, with the unemployment rate on the horizontal axis and the job openings rate on the vertical axis. Thus, every point corresponds to the values of those two rates on a particular date, with the dates connected by a line.

As one would expect, when the unemployment rate is high, the job openings rate is low (and vice versa). If markets were perfectly fluid with perfectly adjustable wages, both rates would be zero. But there are all sorts of frictions, from rigidities in wages to spatial, sectoral, and competency mismatches between demand and supply of labor. These frictions typically generate a scatter plot that looks like a banana, as the markets react sluggishly to changing conditions. Because the current business cycle has been so long and continues even now, the line around the banana is not yet complete.

How this graph was created: Select the two series, the maximum time range, then choose “scatter” for the graph type. To connect the dots, choose a non-zero line width in the settings of the first series. That’s where you can also adjust the size of the dots.

Suggested by Christian Zimmermann

View on FRED, series used in this post: JTSJOR, UNRATE

Dating the financial crisis using fixed income market yield spreads

How would you answer the question, “When did the Great Financial Crisis begin?” Some date the beginning of the crisis according to the events surrounding the failure of Lehman Brothers in mid-September 2008. But at that point, financial markets had already been in turmoil for more than a year, as certain time series from the summer of 2007 show. So how do you date the crisis?

One way to date the recent financial crisis is to identify significant breaks in the dynamics of yield spreads from U.S. fixed income markets (thought to be at the core of the crisis) using appropriate statistical techniques, like I do in a forthcoming article (working paper version) along with coauthors Massimo Guidolin and Pierangelo De Pace. With a particular definition of financial crisis in mind, this procedure allows us to identify the weeks of August 3, 2007, and June 26, 2009, as the beginning and the end of the crisis, at least from the perspective of fixed income yield spreads.

While some of the spreads we use are based on proprietary data, several can be constructed from FRED data. In the graph, we plot the spread between Moody’s seasoned Aaa corporate bond yield and Moody’s seasoned Baa corporate bond yield, as well as the spread between the 30-year fixed-rate mortgage average in the United States and the 30-year Treasury constant maturity rate.

Even just eyeballing the graph gives a sense of the degree of comovement of these spreads at least for the period beginning in 2007. Moreover, the spreads show an upward shift in their level approximately in the second half of 2007 as well as a downward shift approximately in mid-2009.

How this graph was created: In FRED, enter “Moody’s” in the search box. This will return a few Moody’s series: I first selected the Baa corporate bond yield and then added the Aaa corporate bond yield. The spread is then the difference between the two: a-b. A similar transformation was applied to the 30-year Treasury constant maturity rate and the 30-year fixed-rate mortgage average in the United States.

Suggested by Silvio Contessi

View on FRED, series used in this post: AAA, BAA, DGS30, MORTGAGE30US

Who holds federal debt?

Yes. You’re seeing it right: FRED now features pie charts! This chart shows who holds federal debt, which excludes federal debt held within the federal government itself but includes debt held by local and state governments and public entities. Close to half is held by foreign investors, about a fifth by the Federal Reserve, and the rest by domestic investors. Unfortunately, the Treasury doesn’t specifically provide the amount of debt held by private domestic investors alone, so that has to be calculated, as shown here.

How this graph was created: Choose the series “Federal Debt Held by Federal Reserve Banks” and “Federal Debt Held by Foreign & International Investors.” Now, to create the series that shows only private domestic holders of federal debt, select “Federal Debt Held by Private Investors” and then use “Add data series, modify existing series” to include “Federal Debt Held by Foreign & International Investors.” Apply the data transformation a-b and then select graph type “pie,” which will default to the last observation.

Also: To see how the debt holdings have evolved, click on “customize” below the graph and change the graph settings to graph type “line,” “area” or “bar,” and then expand the date range. Set stacking to “percent” to see how the relative shares have evolved.

Suggested by Christian Zimmermann

View on FRED, series used in this post: FDHBFIN, FDHBFRBN, FDHBPIN

Labor market conditions: good or not so good?

The April U.S. employment report showed that nonfarm payrolls rose by 288,000 from March to April. This gain was the largest since January 2012. However, other measures suggest that labor market conditions may not be as strong as the headlines suggest. One key measure that economists regularly track is the employment-to-population (EP) ratio. The numerator in the EP ratio is civilian employment. The denominator is the civilian population. Both series come from the household survey. The ratio thus captures key variables of labor market conditions, such as population growth and the percentage of the population that is working and thus participating in the labor force.

Why do economists look at the EP ratio? The key reason, in short, is that the EP ratio is a key input in a standard growth accounting framework. In this framework, real GDP is the product of (1) real GDP per worker, (2) the percentage of the population that is employed, and (3) the civilian population. The first term approximates labor productivity and the second term is the EP ratio. Mathematically, we can transform each of the three components into growth rates and then add them together to produce real GDP growth. Since population growth tends to change very little in the short-to-medium term, the growth accounting framework is useful because it shows why real GDP growth accelerates or slows. Thus, has real GDP growth changed because of changes to the growth of labor productivity, EP ratio, or some combination of the two? One reason why average real GDP growth during this expansion (2.24 percent) has been so slow is that labor productivity growth has been relatively slow: 1.48 percent per quarter (annualized) through the first quarter of 2014. As shown in the graph, the other reason is that the EP ratio is still below the level that prevailed at the trough of the past recession (second quarter of 2009). Since then, the EP ratio has declined by an average of 0.26 percent per quarter (annualized). Until the growth of the EP ratio strengthens, the pace of the economy’s growth will remain quite modest. That is, assuming population growth remains constant, if labor productivity growth doesn’t accelerate, neither will economic growth.

Suggested by Kevin Kliesen

How this graph was created: In FRED, enter “Civilian employment to population ratio” in the search box. The data are in levels (no transformation).

View on FRED, series used in this post: EMRATIO

The Fed’s “tapering”: a nonevent?

In the weeks leading up to the June 18-19, 2013, FOMC meeting, financial markets were fixated on the possibility that the FOMC would soon begin to slow the pace of its large-scale asset purchase program—which at that point was $85 billion per month. In his press conference following this meeting, Chairman Bernanke said that “the Committee currently anticipates that it would be appropriate to moderate the monthly pace of purchases later this year.” By the time the FOMC finally voted to slow the pace of its asset purchases at the conclusion of its December 17-18 meeting, the 10-year Treasury yield had risen from 1.66 percent on May 2 to 2.85 percent on December 18. The period of rising interest rates before the FOMC began to officially slow the pace of its asset purchases is sometimes referred to as the “taper tantrum.” This development led some analysts to conclude that financial markets would not react well when the real tapering got underway. Well, it hasn’t quite worked out that way.

This graph plots the St. Louis Fed’s Financial Stress Index (STLFSI) since Oct. 1, 2009. In the STLFSI, values above zero are defined as periods of above-average levels of financial market stress and values below zero are defined as periods of below-average levels of stress. Zero is considered average. The STLFSI rose sharply (became less negative) from the week ending May 17 to the week ending July 5. However, since early July it has steadily drifted lower. Moreover, since the December 2013 meeting, when the FOMC first voted to reduce the pace of its asset purchases by $10 billion per month, the STLFSI has fallen even further. Indeed, for the week ending April 25, 2014, the STLFSI was at its lowest level since mid-March 2013. All of this suggests that the Fed’s decision to steadily slow the pace of its asset purchases—currently $45 billion per month after the conclusion of the April 29-30 FOMC meeting—is having little adverse effect on financial markets.

An alternative, though perhaps complimentary view, is that the markets see what the Fed sees: A steadily improving economy and a continued low and stable inflation outlook.

How this graph was created: In FRED, enter “St. Louis Fed Financial Stress Index” in the search box. The data are in levels (no transformation). The beginning period was adjusted to show data since Oct. 1, 2009.

Suggested by Kevin Kliesen.

View on FRED, series used in this post: STLFSI

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