The FRED® Blog

Not all prices increase

It is natural to complain that some prices increase. But don’t forget that prices can also decrease. While there are obvious seasonal fluctuations for some goods (say, agricultural products), other goods have been declining year over year, contributing to a general price inflation that is lower than one may think. The prime example shown here is anything related to information technology. It is no secret that IT devices with a given set of characteristics have continuously fallen in price. Or, to put it differently, a device of the same price year after year will provide much better performance; its price by “unit of performance” must therefore be declining. This graph shows some CPI categories where advances in IT have lead to price decreases. Or at least no price increases. This is not restricted to the IT category, of course. A future blog post will explore more examples on this topic.

How this graph was created: Search for CPI, then add the other series. Because their base years are different, the axis labels get crowded. So, these were removed by unchecking “Axis titles” in the graph settings.

Suggested by Christian Zimmermann.

A clearer picture of housing equity before the crisis

This graph shows housing equity in the United States. The way it’s shown here, housing equity appears to have undergone an extremely unhealthy evolution: rapidly accelerating run-up, sudden and brutal crash, and another rapid run-up. There’s no doubt the housing crash has been significant; after all, housing equity was cut by half. But the alarming run-up shown in this graph is to some degree an optical illusion. Indeed, an increase in the 1950s isn’t equivalent to a same-sized increase in the 2000s because the level of the series was dramatically different. For a clearer picture, we’ll use the natural logarithm of the series.

Now, the run-up around 2000 looks like a normal part of a trend that’s continued for more than half a century. The illusion shown in the top graph can occur whenever a series grows over time. Think of the principal on a savings account that accumulates interest. Soon enough, the effect of compounding interest kicks in and the principal appears to explode, even though it’s still growing at the same interest rate.

How this graph was created: For the first graph, search for the series name. For the second, expand the “Create your own data transformation” option in the graph tab and choose the “Natural Log” transformation.

Suggested by Christian Zimmermann

This recession was different

Most recessions share common characteristics, but not the most recent one. To illustrate this, we use a little known and used feature of FRED: setting a common index value and examining a period before and after that point. In the graph, you see four versions of the same series, civilian unemployment. Each series is centered on a different recession peak date, with a value of 100 for these start dates. The graph also shows data for 60 months before and 80 months after those dates.

The period before the start dates reveals nothing remarkable, but the most recent recession deviates from the other recessions after the start date: The unemployment rate shoots up much higher, and despite a steeper downslope the unemployment rate has yet to reach a value that would be expected from a normal recovery. (By the time 80 months had elapsed from the other recessions’ start dates, the unemployment rates had essentially returned to where they started.)

How this graph was created: Find the “Civilian Unemployment Rate” and modify the units to “Index (Scale value to 100 for chosen period).” For this graph, we use “U.S. Recession Peak” (vs. the “Trough” or another “Observation Date”). The default will be the peak of the most recent recession. Then choose the “Display integer periods instead of dates” option. Choose an interior period range of -60 to 80. Add this unemployment rate series three more times, performing the same manipulations but selecting different recession peaks.

Suggested by Christian Zimmermann

The seasonality of e-commerce

We know that retail sales move with the seasons, but what about e-commerce retail sales? FRED has the data, so we can take a look. The graph shows this series is also very predictable. The general trend is a straight line, with a pattern of increasingly large spikes in the fourth quarter. But e-commerce seasonal patterns are particularly striking: Retail sales in general always rise in the fourth quarter, but e-commerce sales do so even more intensely.

How this graph was created: Search for “E-Commerce” and select the “Sales Share” series without seasonal adjustment.

Suggested by Christian Zimmermann

The demographics of the activity rate decline

Many are lamenting the record lows in the labor force participation rate (or activity rate). The debate is whether this decline is cyclical or structural. The structural view has much to do with demographic shifts as the population gets older on average, so let’s look at the rates for different age groups.

We see a strong drop in participation by young men, likely reflecting a larger share who are staying in school longer. Older men’s participation hasn’t changed much. The bulk of the overall decline comes from middle-aged men. They are the largest group and have the largest impact. But their participation has been declining throughout the sample period, so it is not a new phenomenon for them.

For women, the story is very different because of their large increase in labor force participation up until the end of the past century. Older women are still increasing their participation, but recent declines for younger women seem to mirror the declines for men. So, the recently accelerating decline in the overall participation rate may have to do with women’s participation just not increasing like it used to.

How the graphs were created: Search for “Activity Rate,” then use the tags to limit the series to “Nation,” “USA,” and then “Males” or “Females.” Select the series and then add them to the graphs. Depending on the order of the series in the search results, you may have to adjust line colors to make them consistent in the two graphs.

Suggested by Christian Zimmermann

Inflation in the dollar zone

In a recent FRED Blog post, we showed how the exchange rate regime has had an impact on inflation rates in Europe. This time, we look at the dollar zone. Indeed, several countries have adopted the U.S. dollar as legal tender, and it is startling how their inflation rates have rapidly converged toward the U.S. rate. Just look at the graph. This convergence was likely the intention of those countries: Ecuador in 2000 and El Salvador in 2001 switched to the U.S. dollar to fight against very high inflation rates. Panama had already adopted the U.S. dollar in 1904 and has had no such problems with inflation.

How this graph was created: Search for “Inflation” and the respective countries. In the case of the U.S., change the units to “Percent Change from Year Ago” to match the units of the other series. The line width for the U.S. was increased and the color changed to black.

Suggested by Christian Zimmermann

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

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

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

Quits and layoffs

Consider times when employment has declined. What are the causes? An employment decline can come from fewer hires, more layoffs, and people quitting their jobs. But these factors can interact in complex ways. Indeed, the Job Openings and Labor Turnover release from the Bureau of Labor Statistics shows that hires went down and layoffs went up during the past two recessions. But quits went down, not up; in fact, the decrease in quits partially counteracted the impact the other two factors had on employment, even to the point of entirely canceling the increase in layoffs. This makes perfect sense: The incentive to quit a job is lower when there are fewer opportunities.

The graph also highlights that layoffs came back down quickly after the most recent recession to the lowest levels in this sample. So, the sluggishness of hiring is to blame for the slow recovery in the labor market.

How this graph was created: Go to the Job Openings and Labor Turnover release, select the three series (Rate, Seasonally Adjusted), and click on “add to graph.”

Suggested by Christian Zimmermann

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