Federal Reserve Economic Data

The FRED® Blog

Christmas in Connecticut

Christmas in Connecticut is a classic romantic comedy from 1945 that depicts, as the title strongly implies, some holiday hijinks in the Nutmeg State. Although FRED does not offer much romantic intrigue, it can tell us how the retail sector is doing in individual U.S. states. The graph above shows definite seasonal regularity in Connecticut’s retail employment (the blue line) that’s associated with retail sales around Christmas. As in other U.S. markets, retail employment is always significantly higher in December—even more so for general merchandise stores that sell a larger share of gifts. So it’s a very good idea to adjust the data for this seasonal regularity. Indeed, noting that sales are higher in December than in the previous month of November doesn’t tell us much because this happens every year. So the seasonal factor must be excluded, as shown in the red line.

How this graph was created: Search for “Connecticut retail employees general merchandise” and select the two monthly series. Click on “Add to Graph” and you’re done. Consider decreasing the time period with the sliding bar below the graph: A closer look at the data shows the December peaks more clearly.

Suggested by Christian Zimmermann

View on FRED, series used in this post: SMU09000004245200001, SMU09000004245200001SA

Shopping lines: The evolution of retail in the U.S.

When it comes to shopping, Americans have many options: the corner store, the supermarket, the specialty store, the “big box,” online, and more. Above, we committed a graphing sin by displaying 12 different series in a single graph to show how retail trade has evolved across various categories.

Signs can be seen over the past two and a half decades: First, while food and beverage stores (supermarkets, convenience stores) were major destinations in the past, they have been joined by general merchandise stores, typically large suburban big box stores. A very volatile bunch are the gasoline stations, which sell mostly one commodity with a very variable price. Finally, one category seems to be steadily overtaking the others: mail-order and online shops (the line in black).

How this graph was created: Search for the Advance Monthly Sales for Retail and Food Services release and select the series you want to display. The release offers more series than the 12 we chose, but 12 is the maximum that can be shown on one FRED graph. In fact, with so many series, you need to make the graph larger by dragging the red marker in the bottom right corner of the graph. We chose the seasonally adjusted series and made the nonstore retail series black.

Suggested by Christian Zimmermann

View on FRED, series used in this post: RSBMGESD, RSCCAS, RSDBS, RSEAS, RSFHFS, RSFSDP, RSGASS, RSGMS, RSHPCS, RSMSR, RSNSR, RSSGHBMS

The Canadian dollar and the price of oil

Canada’s oil sector amounts to about 10% of its GDP and 25% of its exports, almost all of which go to the U.S. It’s not too surprising, then, that the U.S./Canada exchange rate mirrors the price of oil. Of course, trade between the countries is much more than oil, but many of Canada’s other commodity exports have a price that is well correlated with the price of oil. And the financial linkages between the countries are also disproportionately tied to the mining and extractive industries.

That said, this relationship hasn’t always existed. See the graph: If you expand the time sample to more than the 10 years shown above, the correlation becomes gradually less clear. But the reason is clear: Canada has continuously expanded its oil production, and oil simply did not matter that much a few decades ago when it was not nearly the dominant revenue source it is today.

How this graph was created: Look for the Canadian/U.S. dollar foreign exchange rate and select the monthly series. Then use the Add a Series option to search for and select “WTI” (again, the monthly series). Modify this second series as follows: Switch the y-axis to the right side and create you own data transformation with formula 1/a. Finally, restrict the graph’s sample period to the past 10 years.

Suggested by Christian Zimmermann and inspired by a tweet from Paul Storer, who recently passed away

View on FRED, series used in this post: EXCAUS, MCOILWTICO


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