Federal Reserve Economic Data

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Does the local economy influence voters?

A look at state median household income growth

Posted on March 2, 2020

The health of our local economy affects our outlook, which in turn can affect our decisionmaking, including how we cast our votes. Some classic research shows the economy is an important factor in national elections; and some newer research specifically links disposable income and military casualties to election results.

FRED has data to help you traverse the economic landscape during elections. This map shows the growth rate of median U.S. household income state by state.

  1. Median is defined as the value at which half the households are above and half below. In a majority election, for example, the median voter would be the determining factor. We look at households here, which obviously could include several voters.
  2. We transformed the raw data on household income to a growth rate, to show how things have changed from the previous year. (By the way, these data are nominal and, thus, include general inflation.)

The darker the color, the more growth—and, in simplified terms, the likelier it is an incumbent politician will be re-elected. Now, at the time of posting, the latest data we have is for 2018. To see how incomes grew for previous years, click on the View in GeoFRED link to get to all the mapping tools: The legend box has arrows that let you move from year to year, all the way back to 1990, which includes seven U.S. presidential elections.

How this map was created: The original post referenced an interactive map from our now discontinued GeoFRED site. The revised post provides a replacement map from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.

Suggested by Christian Zimmermann.

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

Posted on February 27, 2020

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

Posted on February 24, 2020

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


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