The FRED® Blog

Output volatility in small and large countries

The best investment advice is to diversify your asset portfolio because it reduces the volatility and risk of the portfolio. The same applies to the economic performance of countries. The better diversified they are in terms of sectors, the less they suffer from large economic fluctuations. (This concept applies when all other factors are equal, of course; we have recently seen that emerging economies suffer from large fluctuations.) So, how to illustrate the benefit of diversification? One way is to contrast a large country such as the U.S., which covers virtually every imaginable sector, with smaller countries whose size limits the number of industries they can have. The graph shows per-capital real GDP growth for the U.S. (thick black line) and for three countries whose combined population amounts to about 3.5% of the U.S. population. It is quite easy to see that U.S. GDP growth fluctuates less.

How this graph was created: Search for “Constant GDP per capita” for the various countries and add those series to the graph. Transform each series to “Percentage change” and emphasize the line for the U.S. so it stands out (in this case, it is thicker and black).

Suggested by Christian Zimmermann

Spurious correlation

Relationships between macroeconomic time series are not usually straightforward enough to establish with a simple graph. The problem is that almost all time series tend to grow in the long term as an economy grows. So, any measure in nominal terms will grow even more, since inflation rates are almost always positive. Because time series can exhibit a common trend, it becomes difficult to interpret whether there is a relationship between them beyond that common trend. We call this spurious correlation. There are various ways one can isolate the common trend, and we show some here using M2 and total federal debt. Above, with just the raw series, all we can see is that they both tend to increase in the long run at roughly the same rates.

In the second graph, we simply take growth rates of both series. Now the trend is gone, and it is much more difficult to argue that there is some correlation here, positive or negative. (Remember also that correlation does not mean causation: Even if we saw some relationship, we wouldn’t be able to tell whether one series is affected by the other. That requires more substantial statistical analysis.)

In the third graph, we remove the trend in another way: by dividing each series by another series that also has this trend. In this case, we take nominal GDP: GDP because it measures the size of the economy, and nominal because both M2 and the federal debt are measured in nominal terms. The picture of the two ratios now looks different, but it is still difficult to claim that there is a systematic relationship between them. Looking only at the first graph, one would not have concluded that.

How these graphs were created: Search for “M2″ and “federal debt” to find the series: Be sure one of the series has its y-axis on the right. For the second graph, select “Percent change from year ago” for both series. For the third graph, change units to levels and add “Gross Domestic Product” to “M2″ and apply the transformation “a/b”; then replace federal debt with the debt/GDP ratio available in the database (or create that ratio yourself).

Suggested by Christian Zimmermann

Regulatory capital

The United States and several other countries are members of the Basel Committee, a global initiative to help regulate banks and address regulators’ concerns about the way banks hold capital. In fact, the committee has published specific standards for capital requirements for member countries to implement.

Traditionally, banks have reduced the capital they’re required to hold by taking advantage of the lack of risk restrictions assigned to government bonds. But countries such as Greece have shown that government bonds do have some risk attached to them, so regulators hope to change this practice.

We can track relevant changes by looking at data in FRED: specifically, the IMF’s calculation of the ratios of regulatory capital to risk-weighted assets for several countries, which are part of their set of financial soundness indicators.

The data show similar trends in the United States and euro area: The recent recession, which underscored the risk associated with billions of dollars of bank assets, caused a large spike in the amount of capital that banks were holding. However, this amount has declined sharply in the recovery period. Interestingly, the ratios of regulatory capital actually seemed to decrease during the 2001 recession—which points to differences in the nature of the two recessions.

How this graph was created: Search for “Regulatory Capital to Risk-Weighted Assets for United States” and change the units to “Percent, Change, Percent.” Click on “add data series” and add “Regulatory Capital to Risk-Weighted Assets for Euro Area.”

Suggested by Abhinav Chhabra

Economic policy uncertainty

How clear is the public’s understanding of economic policy and its likely outcomes? FRED includes a data series that seeks to answer this question: In a recent paper, Scott Baker, Nicholas Bloom, and Steven Davis developed an index that estimates the level of uncertainty about economic policy by accounting for newspaper references to uncertainty, tax codes, and disagreement among forecasters.

The authors refer to spikes in the index that occurred during important events such as “tight presidential elections, Gulf Wars I and II, the 9/11 attack, and other major shocks.” More-recent events include the Lehman Brothers bankruptcy, the euro crisis, and the debt-ceiling deadlock.

The Federal Reserve has been making an effort to reduce uncertainty by increasing clarity and transparency with respect to its policies. As noted in a previous blog post, FRED also allows you to track the projections made by FOMC members. (Read full-text FOMC statements back to 2009 on the Board’s website.)

How this graph was created: Search for “Economic Policy Uncertainty Index” and change the frequency to “Weekly, Ending Friday.”

Suggested by Abhinav Chhabra

Economic volatility in emerging economies

By definition, “emerging” economies are in transition from “developing” status to “developed” status, which is generally a bumpy road that may involve more-frequent crises and stronger economic fluctuations. One way to visualize this transition in FRED is to graph per capita GDP growth rates for the BRIC countries (Brazil, Russia, India, China) and compare them with the rate for the U.S. (thick black line). While it is usually better to show fewer series on one graph, the idea here is simply to illustrate that these economies bounce around much more than the U.S. economy does. The U.S. rate is never the highest. On the rare occasions when it is the lowest, it is only barely so—with 2007 being the exception.

How this graph was created: Search for “Constant GDP per capita” for the various countries and add the series to the graph. Transform each series to “Percentage change” and emphasize the line for the U.S. so it stands out (in this case, it is thicker and black).

Suggested by Christian Zimmermann

Hours worked and unemployment: United States vs. Germany

Many economists argue that German labor market reforms implemented in the 2000s clearly paid off during the global recession, particularly the combination of less-generous unemployment benefits, wage moderation, and incentives to hoard labor. A long-established work program called Kurzarbeit (literally “short work”) is credited with helping to smooth Germany’s labor market adjustment much better than in previous recessions by allowing firms to reduce employee hours.

The graphs provide some evidence of the effect of this program at the aggregate level. Average annual hours per worker between 2008 and 2009 dropped by 1.87 percent in the United States, but fell more markedly—by 2.74 percent—in Germany. Massive layoffs occurred in the United States, but employment losses were barely noticeable in Germany. In addition, between the recession’s peak and trough, the U.S. employment-to-population ratio decreased by 2.6 percentage points (from 48.4 to 45.8 percent) while it increased by 0.6 percentage points in Germany (from 48.7 to 49.3 percent).

If this labor market feature works well in Germany, could it be adopted in other countries as well? One version of a short-time work program—called work sharing—already exists in the United States, with the goal of limiting job losses during difficult economic times. At the start of this year, twenty-six states and the District of Columbia were able to offer the program (now under the umbrella of the Layoff Prevention Act of 2011), though the levels of implementation vary.

How this graph was created: The graph of unemployment rates is a simple plot of the unemployment rates for the two countries since 2008. The graph of hours worked is plotted using the option “Index (scale value to 100 for the chosen period).” The data samples were shortened to highlight the previous recession cycle.

Suggested by Silvio Contessi and Li Li.

Debt- and deficit-to-GDP dynamics

Several historical examples show that financial crises generate large increases in private and public debt that take many years and sometimes drastic measures to resolve. The recent global financial crisis, which began in 2007, was no exception: The public debt of the affected countries increased to levels not seen for decades.

During a recession, tax revenue falls because of the contraction of GDP and governments also increase spending. The combination of these two forces increases deficits, and debt-to-GDP ratios can rise quickly as a result.

This mechanism can be seen very clearly in these scatter diagrams: Debt-to-GDP ratios (vertical axis) and deficit-to-GDP ratios (horizontal axis) are shown for the United States (red dots), Japan (blue dots), and the euro area (green dots) for several years after 2001. The changes in the two ratios are more marked for the recent financial crisis than what would be seen for plain vanilla recessions (such as the U.S. recession in 2001) that are not associated with such crises. As the recession ended, the deficit ratios started to decline because tax revenue grew and primary deficits (excluding interest) contracted. But the debt ratios kept rising, in part because primary balances are still negative and in part because the burden of interest is now larger.

How this graph was created: Search for and select the appropriate series for central government debt for each country and then add the appropriate series for the deficit-to-GDP ratio. Select “scatter” for the graph type in “settings.” The width of the lines connecting the dots can be adjusted in the settings of the first series.

Suggested by Silvio Contessi

Quitters, public and private

St. Louis Fed economist David Wiczer recently assessed the labor landscape by comparing rates of workers quitting their jobs with rates of workers being let go. This graph takes a simpler view and shows the rates of workers quitting in the public and private sectors. The private-sector rate is obviously higher; in July 2005, for example, the private-sector rate was 460 percent of the public-sector rate.

Not surprisingly, though, the rates track each other pretty closely: Any worker would be more inclined to quit a job when economic prospects are good and less inclined when they’re not so good. But the data behind this graph show that the gap between the rates has narrowed a bit since the recent recession. From December 2000 to June 2009, the private-sector rate was on average about 350 percent of the public-sector rate; since then, the gap has fallen to about 320 percent. The graph does show a recent rise in the private-sector quit rate, however, so the gap may be increasing.

How this graph was created: Select the first series, “Quits: Total Private,” and then add the second series, “Quits: Government.” Both series shown here are seasonally adjusted monthly rates. You can also search for specific industries (e.g., construction or manufacturing) and other measures (e.g., layoffs and discharges).

Suggested by George Fortier.

Mapping international data

GeoFRED_Gross_Domestic_Product-4

GeoFRED, part of the FRED family, allows you to map many data series that exist in FRED. GeoFRED just underwent a major overhaul and now features a modern layout and plenty of new functionality. It also includes plenty of data series that cover a wide range of geographical territory. It used to cover only regional U.S. data, such as states, counties, and MSAs; but now it also encompasses international data, such as the per capita GDP data shown above. Enjoy exploring this renewed site!

How this graph was created: No need to search for the series, as this is the default graph on GeoFRED. But you can also find it by selecting this series in the tool bar. Country labels were removed by unchecking “display labels.” Finally, the graph was saved using the “download & print” tab of the tool bar.

Suggested by Christian Zimmermann

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


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