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The far-reaching effects of your Valentine’s Day chocolate

This post falls on February 14, Valentine’s Day, and our thoughts turn sweet. Specifically, to chocolate.

Chocolate is ubiquitous and delicious and sometimes frivolous, especially while strolling through the “impulse purchase” lanes of the supermarket. But chocolate can be of major importance to those who produce it, in particular to those who produce its raw material, cocoa.

The largest exporter of cocoa is Côte d’Ivoire (Ivory Coast) in West Africa. Cocoa beans and cocoa derivatives represent close to 40% of the exports for this country of 26 million residents. Cocoa matters a lot to Côte d’Ivoire.

The FRED graph above shows a couple of things:

  1. The price of cocoa is quite volatile, which happens with primary commodities. But price volatility can have big effects on economies that depend on that production.
  2. For cocoa in Côte d’Ivoire, we see that higher prices help reduce the country’s public debt. Of course, many other factors affect the public debt, such as other economic activity, debt conditions, and financial markets.

As you enjoy your chocolate, take a moment to consider its economic impact. And the sweetness of FRED data.

How this graph was created: Search FRED for “cocoa price.” From the graph, click on “Edit Graph,” open the “Add Line” tab, and search for and select “Cote d’Ivoire debt.” Use the “Format” tab to move the y-axis for the second line to the right side. Restrict the sample period to when data are available for both lines.

Suggested by Christian Zimmermann.

Building home price indexes

Federal, S&P/Case-Shiller, and Zillow housing measures

“Every spirit builds itself a house; and beyond its house, a world”

—Nature, Ralph Waldo Emerson (1803-1882)

Today, the FRED Blog considers a more down-to-earth version of Emerson’s lofty concept: How is a home price index built? The FRED graph above starts us off by showing three headline indicators of U.S. home prices:

  • The all-transactions house price index for the United States (in green), produced by the U.S. Federal Housing Finance Agency, measures quarterly changes in single-family home values. It uses sample data from repeated sales of the same property. It is not adjusted for seasonal changes in home values. First released in 1996, this index extends back to the first quarter of 1975.
  • The S&P/Case-Shiller U.S. national home price index (in red), produced by Standard and Poor’s Dow Jones Indices, measures monthly changes in single-family home values. It also uses sample data from repeated sales of the same property, although it considers only “arm’s length” transactions (i.e., those where the buyer and seller are separate parties). This index, like the previous one, is not seasonally adjusted. First released in 2006, this index extends back to December 1987.
  • The Zillow home value index for all homes including single-family residences, condos, and co-ops in the United States (in blue), produced by Zillow, measures the typical dollar value of a composite of homes. It is produced monthly, using sample data from a proprietary estimate of a home’s market value called a “Zestimate.” This value is “smoothed seasonally adjusted” to account for changes in home values related to the calendar. First released in 2019, this index extends back to January 2000.

So. What does the graph tell us? All three indexes show a marked up-and-down cycle in the late 2000s and faster growth in home prices after 2020. In fact, despite their substantially different methodologies, the last two (monthly) indexes report very similar home price growth, almost 30%, between February 2020 and November 2021.

How this graph was created: Search for and select “Zillow Home Value Index (ZHVI) for All Homes Including Single-Family Residences, Condos, and CO-OPs in the United States of America.” From the “Edit Graph” panel, use the “Add Line” tab to search for and select “S&P/Case-Shiller U.S. National Home Price Index” and “All-Transactions House Price Index for the United States.”

Suggested by Diego Mendez-Carbajo.

Logs of softwood lumber

Using the natural logarithm to clarify volatile prices

Some commodities have seen some wild price fluctuations during the COVID-19 pandemic. One that was much discussed in the news is softwood lumber. While FRED does not have data on its retail price, it does have the price that the producer gets: the Producer Price Index, formerly called the Wholesale Price Index.

Our first FRED graph shows how unusual these price fluctuations have been. While the price stayed within a narrow band for years, it has suddenly spiked and plummeted in unprecedented ways since the middle of 2020. When data points rise or fall by multiples of their preceding values, it’s useful to transform the data to ensure an accurate understanding. In this case, taking logs of lumber prices provides us with that clarity—and a nice pun!

Our second FRED graphs shows exactly the same data, except that we took logs (i.e., the natural logarithm). The advantage of such a graph is that a 10% price increase looks the same whether the price is high or low. And the graph confirms that even when the price was high, the fluctuations were proportionally (or in percentages) very large.

How these graphs were created: Search for “PPI softwood lumber,” open the graph, and restrict the sample period to start in 2014 (due to preceding data interruptions). For the second graph, click on “Edit Graph” and set units to “Natural log” (last field).

Suggested by Christian Zimmermann.

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