Federal Reserve Economic Data

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Canada votes. What’s up?

Canadians are heading to the polls on Sunday, October 18, 2015, to elect a new parliament and government. Voters often consider the current state of the economy during election season, and FRED can help you track the economic situation for the U.S.’s neighbor to the north. Although data from Statistics Canada aren’t included in FRED, plenty of Canadian data from other sources are available, although sometimes with a delay. At the time of this writing, the tag for Canada has 2226 series listed in FRED.

The graph above shows some of the economic aggregates that are likely to matter the most for Canadians: the unemployment rate, GDP, inflation, and the exchange rate with the U.S. dollar. Canada did relatively well during the previous recession, at least compared with the U.S. Unemployment has remained relatively high, though, and the economy is currently suffering from the massive decrease in several commodity prices, which is readily visible with the weakening of the Canadian dollar. If you are reading this blog post some time after it was published, the graph will have updated automatically with the latest data. And, reader from the future, you will be able to see how the Canadian economy has fared and know whether the conservative government was reelected.

How this graph was created: Search by using the Canada tag, select the four series shown in the graph, and click “Add to Graph.” Three of these series need a little attention: CPI and GDP need to be expressed as growth rates, which is done by opening their respective panels and selecting “Percent Growth Rate from Previous Year” under “Units.” Finally, the axis for the exchange rate needs to be moved to the right because the unit range is so different from the others.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CANCPIALLQINMEI, EXCAUS, LRUNTTTTCAQ156S, NAEXKP01CAQ189S

Inflation decline opens regional inflation differentials

The annual inflation rate of the U.S. declined to (roughly) zero at the beginning of 2015, and it has remained close by ever since. But is inflation equally low in all regions? To find out, we look at data series in FRED that track overall inflation for the U.S. and inflation for each of the four Census regions: the Northeast, Midwest, South, and West. As the graph shows, all U.S. price growth over the past eight months has come from the West; since January, inflation in the West has been at least a full percentage point above that of the other three regions. If the West were excluded from the picture, then August’s national inflation rate of 0.20% would instead have been –0.19%.

In a recent On the Economy blog post, we showed that the lion’s share of this difference between inflation in the West and inflation in the other three regions is explained by differences in prices for energy and shelter. Energy inflation explains between 42% and 70% of the gap, depending on the region, and shelter inflation explains between 37% and 51% of the gap.

Does it matter that shelter inflation is a key driver of these regional differences? If shelter inflation in the West is driven by low interest rates, then one implication for monetary policy is that normalization (or “liftoff”) could push inflation in the West down to the levels observed in the other three regions.

How this graph was created: Search for “CPI” and select the series “Consumer Price Index for All Urban Consumers: All Items” (monthly, not seasonally adjusted). Change the units from “Index 1982-1984=100” to “Percent Change from Year Ago.” Then add the four regional CPI series to the graph by searching for the following series IDs: CUUR0100SA0, CUUR0200SA0, CUUR0300SA0, and CUUR0400SA0. Also change the units for each of these to “Percent Change from Year Ago.” Finally, restrict the sample to start in January 2014 by using the settings above the graph on the right.

Suggested by Alejandro Badel and Joseph McGillicuddy

View on FRED, series used in this post: CPIAUCNS, CUUR0100SA0, CUUR0200SA0, CUUR0300SA0, CUUR0400SA0

Higher order moments of unemployment duration

The unemployment rate has steadily improved since its peak at the end of the Great Recession. The unemployment rate is a good summary of the state of the labor market, but unemployment duration also contains information about how easy it is for people to find jobs. The BLS measures duration by taking a cross-section of unemployed and asking them how long they’ve been unemployed. A persistent characteristic of the data is that some people find jobs much more quickly than others—and the longer someone is unemployed, the lower their chance of finding a job.

This dynamic leads to a distribution of unemployment duration that is “right skewed”: That is, the distribution has a long “tail” of workers who’ve been unemployed for a long time and a large number of job finders with very short spells of unemployment. We can use many measures to evaluate this skewness, but a simple one is the ratio of the mean duration to the median duration. When the mean is much larger than the median (a ratio greater than 1), then these very long durations of unemployment have increased the mean duration and the large number of short durations have decreased the median duration.

In recessions, the skewness of unemployment duration (green line) always falls because the inflow of newly unemployed with zero duration reduces the mean duration. In the aftermath of the Great Recession, unemployment duration has become increasingly skewed outward: The mean and median are still high relative to other expansions, but strikingly the skewness has continually risen. The force behind this skewness is the number of long-term unemployed, who are now a particularly prominent portion of the distribution.

How this graph was created: Search for “mean unemployment duration” and add this series to the graph: UEMPMEAN. Then use the “Add Data Series” feature to search for “median of unemployment duration” and select UEMPMED as a new line. For the third series, combine these two series to create a new series: First add UEMPMED again, then add UEMPMEAN through the “Modify existing series” option. Use the “Create your own data transformation” option and insert the formula b/a . Place this new series on the right y-axis by itself.

Suggested by David Wiczer.

View on FRED, series used in this post: UEMPMEAN, UEMPMED


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