Federal Reserve Economic Data

The FRED® Blog

Busting a Santa myth

How hard are the elves working?

We’ve all heard that Santa and his elves are wildly busy, especially through December, making toys and other gifts for the Christmas season. Can FRED tell us anything about how busy they are? As it turns out, FRED does have quite a bit of employment data on Santa’s neighborhood: Alaska! (Which includes the town of North Pole!)

Given the quantity of gifts distributed on Christmas eve and the size of Alaska’s economy, we reckon that Santa’s enterprise is a major player and that Alaska’s economy is a good proxy for what’s happening in Santa’s shop.

We’re sorry to say that Alaska’s employment data do not corroborate the story that Santa and his elves keep busy in December. The graph above shows the total number of employees in Alaska’s private businesses. This measure excludes government employees, but it’s reasonable to assume Santa isn’t part of the government.

What’s really striking about this graph is the strong seasonal pattern. Significantly more people work in some months than in others, and the differences aren’t small: There’s a 20% difference between the top and bottom in each year. If you look closely (either by shortening the sample size or by hovering over the graph), you see that January has the least employees, which is expected, since Santa has just finished the deliveries and is likely on vacation with the elves. But the top months are all in the summer. This means the elves aren’t scrambling right before Christmas, but instead have planned their production well ahead of time. The graph below tells a similar story, in that weekly hours worked follows the same pattern as the employment measure: They actually bottom out every December.

In conclusion, the story that elves are overworked making toys right up to Christmas is simply a myth.

How these graphs were created: Search for “Alaska private employment,” and both series will be among the choices. Choose on the monthly, not seasonally adjusted series.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: SMU02000000500000001, SMU02000000500000002

Houses, up and down

An international comparison of house price movement

We recently highlighted state-by-state comparisons of house price appreciation. Today, we’re going international. Thanks to the Bank for International Settlements, we have residential property prices for a selection of countries, in both nominal and real terms. Here we focus on the latter, which show how house prices evolve compared with other prices. We also focus on countries with relatively long sample periods so we can document long-term trends.

The graph above shows data for a set of countries where houses have significantly appreciated over the long haul. It’s not a steady trend (e.g., Hong Kong) and doesn’t last through the whole period (e.g., the U.K.’s “weak” property market over the past 10 years); these patterns highlight the adage that past behavior isn’t necessarily a good predictor of future behavior. The graph below shows a different set of countries where the long-term trend is more mixed, even downward facing. The U.S. is part of this group with its distinct “bubble” that the housing market is still recovering from. Switzerland is surprisingly stagnant despite strong population growth, and Korea is even trending down.

How these graphs were created: Search for “BIS house price,” then click the “real” tag in the side bar. Check the series you want shown, and click “Add to Graph.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: QCAR628BIS, QCHR628BIS, QGBR628BIS, QHKR628BIS, QKRR628BIS, QNZR628BIS, QUSR628BIS, QZAR628BIS

To every thing, there is a season…

Playing with retail data

FRED recently added a lot of new data from the U.S. retail sector—just in time for the holidays. So let’s take this opportunity to play a little game. The release table for monthly retail sales shows plenty of subsectors involved in retail trade. Because these series are not seasonally adjusted, they may show some large seasonal factors at work. The game is to try to predict what the seasonal factors for each sector will look like before displaying the graph for that sector. The graph above reveals the seasonality for three sectors: Sales of office supplies peak in August with the return to school. Sales of gifts and novelties peak in December as people scramble to fill Christmas stockings. And sales of used merchandise bottom out at the start of the year for reasons that escape us. Hint: To identify the months more easily on the graph, reduce the sample period to a few years and hover over the lines to identify the months.

How this graph was created: Go to the release table for monthly retail sales (not seasonally adjusted), check the series you want, and click on “Add to Graph.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: MRTSSM45321USN, MRTSSM45322USN, MRTSSM45330USN


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