Federal Reserve Economic Data

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Trade between the U.S. and China: Steady as she goes?

For years now, we’ve been talking about the tempest of tariffs and trade wars between the U.S. and China. The FRED graph above doesn’t reveal all the effects, but it gives us the big picture by tracking overall imports, exports, and the trade balance for goods. Clearly, U.S.-China trade has grown tremendously over the decades, along with a large trade surplus for China. But things haven’t changed in any substantial way for the past 10 years. The composition of traded goods today may be different from what it used to be, but there’s nothing remarkable happening in the aggregate.

A few more ideas:

  1. The units for imports and exports are in natural logarithms, which we’ve used before to evenly display changes over time.
  2. FRED has data only for traded goods, not services; but we did investigate this topic a while back.
  3. There’s nothing intrinsically bad about the U.S. having a trade deficit.

How this graph was created: Search for and select the “goods imports China” series and click “Add to Graph.” From the “Edit Graph” panel, use the “Add Line” option to search for and add the “good exports China” series. Set the units for both lines to “Natural Log.” For the third line, use “Add Line” again to search for and select the “good imports China” series. Then use the “Customize data” search field to search for and select the “good exports China” series. Apply formula b-a. Finally, use the “Format” tab to choose “Right” for the y-axis position of the last line.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: EXPCH, IMPCH

A house divided against itself cannot stand

Explaining the composition effect in housing prices

Our recent post on women in the workforce included a lyric from Dolly Parton and an explanation of the composition effect. Here’s the formal definition: “The part of the observed between-group difference in the distribution of some economic outcome that can be explained by differences in the distribution of covariates.”

That’s a doozy of a definition, so let’s use a picture that’s worth 1,000 words to explain it… The graph shows the year-to-year growth rate of average home prices in the United States (blue bars) and in its 20 largest metropolitan areas (red bars). The blue bars and red bars generally extend in the same direction, although by different magnitudes. Because these top 20 metropolitan areas are part of the United States, it’s not surprising both sets of average prices move in the same direction.

But look what happened in 2010: Average home prices overall decreased while average home prices in the 20 largest metropolitan areas increased. Why? Because average home prices in smaller metropolitan areas and rural areas decreased more than average home prices in large metropolitan areas increased. That’s the composition effect: Looking at the big picture sometimes masks what’s going on with the individual parts.

Want to learn more about the composition effect in housing prices? Read “A Guide to Aggregate House Price Measures” by Jordan Rappaport of the Kansas City Fed.

How this graph was created: Search for “S&P home prices” and select the “U.S. National” series (FRED series ID CSUSHPISA). From the “Edit Graph” panel, use the “Add Line” feature to search for and select the “S&P 20-City” series (FRED series ID SPCS20RSA). From the “Format” tab, select “Bar” for graph type. From the “Edit Bar 1” tab, select “Percent Change from Year Ago” for units and “Annual” under “Modify frequency.” Do the same from the “Edit Bar 2” tab. Adjust the time period shown with the slider beneath the graph or with the start and end date boxes above the graph.

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: CSUSHPISA, SPCS20RSA

Currency arbitrage in the precious metals market: A gold rush?

FRED’s as good as gold, and the FRED Blog has used London Bullion Market Association data to prove it. In fact, our previous post tracks gold prices and appraises the new gold bar at the St. Louis Fed. Now these gold prices are quoted in three different currencies—U.S. dollars, British pounds, and euros—which is a golden opportunity to discuss arbitrage. Arbitrage is the risk-free purchase and sale of an asset to profit from a difference in price across markets. Because the gold fixing price is quoted in three different currencies at once, it’s possible that one could make a profit by buying and selling gold in different currencies and then selling the currencies. For example: buy gold in U.S. dollars, sell the gold right away in British pounds, and then convert the pounds back to dollars in the foreign exchange market. FRED can help us visualize this shiny concept: In the graph above, we show the ratio of the gold fixing price in U.S. dollars to the gold fixing price in British pounds. Then we graph the exchange rate between the U.S. dollar and the British pound. The two lines seem identical, so there’s no obvious arbitrage opportunity here. But let’s dig deeper by building another FRED graph to show the difference between the U.S. dollar/British pound gold fixing price ratio and the exchange rate between the two currencies. If there really is no arbitrage opportunity, the graph should show a flat horizontal line at the zero mark.
This doesn’t look like a flat line, so did we find treasure?! Sadly, no. The graph shows differences in gold fixing prices between currencies, but they are extremely small and volatile. So small they’d likely be wiped out by transaction costs, such as brokerage fees in the precious metals and/or foreign currency markets. Rather than a gold mine, we seem to have found just some gold dust. 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 Diego Mendez-Carbajo.
View on FRED, series used in this post: DEXUSUK, GOLDPMGBD228NLBM, GOLDPMGBD229NLBM


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