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How the exchange rate regime drives inflation

This graph shows inflation rates for some of the countries that founded the euro zone. The sample period encompasses three exchange rate regimes: 1. The first is a fixed exchange rate under the Bretton Woods agreement, which allowed some adjustments but ones that were difficult to achieve. The countries’ inflation rates were similar in this period, with occasional exceptions. 2. This system collapsed in 1971 and gave way to a series of exchange rate arrangements with varying membership and success in limiting exchange rate fluctuations. The graph clearly shows that inflation rates varied considerably from one country to the next, which made it difficult to obtain relatively stable exchange rates. 3. Then came the creation of the euro in 1999. A major requirement of membership to this currency union was a low inflation rate maintained within a small range across candidate countries. The graph nicely shows the convergence in inflation rates, which has been maintained to this date.

How this graph was created: Search for “Inflation” and then limit the selection in the sidebar by choosing tags: “Nation” (under geography types) and “World Bank” (under sources).

Suggested by Christian Zimmermann

View on FRED, series used in this post: FPCPITOTLZGESP, FPCPITOTLZGFRA, FPCPITOTLZGGRC, FPCPITOTLZGITA, FPCPITOTLZGNLD

Not all books are created equal

The evolution of consumer prices is not uniform across categories, and there can be stark differences between relatively similar products. In the example above, we look at two types of books: those used for recreation and those used for education. The paths of their price indices are very different, even in the long term. While this example is rather extreme, there are plenty of others in the disaggregated CPI data. This shows that one should not use personal experience with the price of a very specific product to draw conclusions about the general price level.

How this graph was created: Search for “CPI book.” To weed out the price indices from other countries, click on USA in the left sidebar tags. Select the two series, not seasonally adjusted (as one is not available seasonally adjusted). Finally, select a right axis for one series, as they have different index years.

Suggested by Christian Zimmermann

View on FRED, series used in this post: CUUR0000SEEA, CUUR0000SERG02

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


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