Federal Reserve Economic Data

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Posts tagged with: "GDP"

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The velocity of money

The velocity of money played an important role in monetarist thought. For example, monetarists argued that there exists a stable demand for money (as a function of aggregate income and interest rates). In some formulations, that translates into a stable relationship between the velocity of money and a nominal interest rate—for example, the short-term Treasury bill rate.

The velocity of money is defined by

V = (PY)/M,

where V is velocity, P is the price level, Y is real output, and M is a measure of the money stock.

The graph shows the velocity of M1, with nominal gross domestic product as the chosen measure of PY. There are at least two interesting features in the graph: First, before the early 1980s, there was a more-or-less predictable trend increase in velocity. But after 1980, velocity exhibits wide swings. Basically, this reflects a fairly stable money demand relationship before 1980 and an unstable one afterward. Second, there’s a dramatic decrease in velocity starting at the beginning of the Great Recession, shown as the shaded area in 2008-09 in the graph. This is perhaps surprising, as short-term nominal interest rates have been essentially zero since late 2008. If the demand for M1 had been stable, velocity would be roughly constant; but since the beginning of the Great Recession, M1 has grown at a much faster rate than nominal GDP. This can be explained partly by a flight to the safety of insured bank deposits during the financial crisis.

How the graph was created: There are measures of the velocity of money available in FRED, but we can learn some useful things about FRED by constructing M1 velocity ourselves. First, go to the Categories menu, look under the category “Money Banking and Finance,” and select the subcategory “Monetary Data”: There you’ll find “M1 and Components.” Select “M1 Money Stock, Monthly, Seasonally Adjusted” and the graph will appear. Because we use quarterly GDP as our nominal income measure, we need M1 to be quarterly as well. So in the Frequency box, select “Quarterly.” This will convert the raw monthly M1 data to a quarterly frequency. Next, select ADD DATA SERIES and check the “Modify existing series” box. In the search box, type “gross domestic product” and add it to the graph. (Make sure you select “gross domestic product” and not “real gross domestic product.”) Now click “EDIT DATA SERIES 1” and select “Create your own data transformation.” M1 is series “a” and PY is series “b,” so enter the formula “b/a.” (See the V = (PY)/M equation above.) Next, under “Create your own data transformation,” scale the result by selecting “Index (Scale value to 100 for chosen period)” and then add the initial date of the series, 1959-01-01, in the Observation Date box.

Suggested by Stephen Williamson.

View on FRED, series used in this post: GDP, M1SL

How much money is the Fed printing?

We hear frequently that the Fed is printing money like crazy these days. This is not quite true. There are various definitions of money: For money that is being printed, one needs to look at currency in circulation, which actually counts all printed banknotes less those that have not left the Fed’s vaults. So, has the money in circulation increased like crazy since the start of the latest recession?

The currency in circulation (technically called the currency component of M1) is indeed increasing, but there is no indication that it is accelerating. To see this, we have taken the natural logarithm of the series. This means that if the slope is the same for two years, the growth rate is the same. Not taking the natural logarithm would show an illusion of acceleration, as a 1% increase in 2014 would look much bigger than a 1% increase in 1960 because the stock of currency has increased over time.

And why did it increase? One major reason is simply that the economy has grown and needs more currency to function. In the graph above, we divide the currency in circulation by nominal gross domestic product (GDP). While this ratio has indeed increased recently, it is nowhere near historical highs as some commentators seem to imply. In fact, it also seems to follow a neat U-shaped long-term trend. Thus, again, nothing special in recent years.

How these graphs were created: For the first graph, search for “currency” to find the right series. In the graph tab, expand “Create your own data transformation” and select the “Natural Log” transformation. For the second graph, undo the natural log transformation by selecting the empty transformation. Then search for GDP (not the Real one; we want a ratio of nominal series) and add it to series 1. Finally, use the data transformation “a/b” to obtain the ratio.

Suggested by Christian Zimmermann

View on FRED, series used in this post: CURRSL, GDP

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

View on FRED, series used in this post: GDP, GFDEBTN, GFDEGDQ188S, M2NS


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