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The FRED® Blog

The sound and fury of gasoline prices

Gasoline prices have really gone up and down lately. With such wide-ranging short-term fluctuations, it’s hard to tell whether gasoline has become more expensive over the long run. So we turn to FRED. The CPI includes a component that tracks gasoline used for private transportation. We can compare this gasoline component with the CPI to see how gasoline prices have risen in relation to prices in general. The graph clearly shows all the stormy fluctuations for gasoline. But it also clearly shows something we may not have expected: The price of gasoline is now at the same level it would have reached had it simply followed the smooth evolution of the overall price index. We can’t depend on these price levels to coincide, of course, given the typical fluctuations of gasoline. And if the past decade is any indication of the future, gasoline prices will return to their higher levels.

How this graph was created: Search for “CPI gasoline” and select the monthly seasonally adjusted series. Then add the series “CPI.” (You can also work from the relevant release table to select the series you want.) Finally, to start the series at the same level instead of the 1982-84 index year, edit both series as follows: Choose “Index (Scale value to 100 for chosen period)” under Units and “1967-01-01” under Observation Date.

Suggested by Christian Zimmermann

View on FRED, series used in this post: CPIAUCSL, CUSR0000SETB01

The evolution of income inequality

Do you know that FRED includes data on income inequality? The data come from the income, poverty, and health insurance coverage release from the U.S. Census Bureau as part of its yearly Current Population Survey. The data cover both households and families, with geographic and racial subcategories. Do you also know the distinction between “households” and “families”? A household includes all people living in a housing unit; a family includes only those related by marriage, blood, or adoption.

The Gini ratios shown in this graph measure income inequality. Higher values indicate more inequality, and the graph clearly shows an upward trend for both households and families.

How this graph was created: Go to the release noted above, choose “gini” in the tags, choose the series you want to graph, and click “Add to graph.”

Suggested by Christian Zimmermann

View on FRED, series used in this post: GINIALLRF, GINIALLRH

Oil and the Norwegian stock market

Norway is a small country with an oversized oil sector. So how do fluctuations in crude oil prices affect its economy? It is too early to look at Norway’s GDP for any effects from the recent drop in oil prices. But we can look at its stock market. The graph above shows the price of North Sea oil (deflated to remove the general increase in prices) and the index of the Oslo Stock Exchange (converted to U.S. dollars and deflated as well). It is pretty obvious that there’s a strong relationship between the two. The relationship is even more obvious when you look at the scatter plot below, where each point corresponds to a date and each axis corresponds to one of the time series.

How these graphs were created: Search for “Share price Norway” and add the monthly index series to the graph. Note: We’ll use only monthly series here. Then add the series “Norway exchange rate” and “CPI United States” to series 1. Apply transformation a/b/c. Now select “Brent oil price” as series 2 and add “CPI United States” to it. Apply transformation a/b. Use the right y-axis for this series. (You may remove the axis labels, under the graph settings tab, if you think things have become too crowded with all these transformations.) Repeat these steps to create the second graph, but switch graph type to “Scatter” under the graph settings tab.

Suggested by Christian Zimmermann

View on FRED, series used in this post: CPIAUCSL, EXNOUS, MCOILBRENTEU, SPASTT01NOM661N

Seasonal interest rates

When we say “seasonal variation,” we’re referring to fluctuations in the data that follow a pattern according to the time of year. For example, retail trade is always higher just before Christmas. The sale of ski lift tickets is always higher during winter—at least in the Northern Hemisphere. Agricultural output is higher in the growing season. Could this variation also apply to interest rates? It turns out it can, under specific circumstances. In some markets, banks look for liquidity at various times. They typically face regulations that affect what they can carry in their books; depending on the country and other factors, they may have to satisfy these regulations every single day, at the end of the month, or on average over the month. The end-of-month option especially can introduce seasonality in overnight interest rates, as banks scramble to satisfy regulations at very specific times during the year. The graph above shows liquidity in euros, which spikes every last day of the month. The graph below, which covers banks in Denmark, shows a spike every Wednesday. (Special circumstances also apply, such as holidays: Note the spike on Monday, Christmas Eve 2007, for example.) In the lower graph, you can slide the sample window to the right to see that this spike does not always occur: Rules can change over time, as can general market conditions. In fact, at the very end of the sample (Sep. 2012 through March 2013), the spikes actually point down, as banks were trying to get rid of their excess liquidity.

How these graphs were created: Search for “daily overnight” and you’ll find various choices. The two presented above are those with seasonal variations.

Suggested by Christian Zimmermann

View on FRED, series used in this post: DKKONTD156N, EURONTD156N


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