Federal Reserve Economic Data

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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: NOTE: Data series used in these graphs have been removed from the FRED database, so the instructions for creating the graphs are no longer valid. The graphs were also changed to static images..

Suggested by Christian Zimmermann

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


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