Federal Reserve Economic Data

Our FRED graph above looks at what U.S. households own and owe in terms of real estate: The blue line represents households’ total equity in real estate as a share of GDP, and the red line represents households’ total mortgage debt as a share of GDP over the same time period.

Household equity and mortgage debt generally moved in tandem before 2007. However, this comovement breaks down after the 2007-2009 financial crisis. Right before the financial crisis, property values began to fall; and, for a few years, total real estate equity fell below total real estate debt. The fall in housing equity reversed after 2012 and has been continuing on its rising trend even as we write this post. Total mortgage debt, on the other hand, has fallen consistently since the 2007-2009 financial crisis.

The graph above shows the ratio of equity to mortgage debt: From 1993 to 2005, the ratio of equity to mortgage debt was around 1.5 on average. After the housing crisis, this ratio bottomed out at 0.83 in 2012 before surging to 2.34 as of 2022, a level not seen since 1960.

This phenomenon may have arisen from changes in the financial sector’s lending capacity, whether from regulation or risk attitude. It could also indicate a change in the ownership structure of houses: It may be that houses were accessible only—or mostly—to people who took out a mortgage, but now they can be owned by people who have enough equity to bypass external financing.

How this graph was created: Search FRED for “Owners’ equity in real estate” and select “Households; Owners’ Equity in Real Estate, Level.” Go to the “Edit Graph” panel in the upper right corner to open the “Edit Line” box. Scroll down to “Customize data.” In the text box, search for “gdp” and select “Gross Domestic Product.” Click “Add” next to the text box. Below this section, in the “Formula” space, enter a/b and click “Apply.” Next click the gray “ADD LINE” box at the top. In that search box, search for “Household Mortgages” and select “Households and Nonprofit Organizations; Total Mortgages; Liability, Level.“ Scroll down to “Customize data”: Search for “gdp” and select “Gross Domestic Product.” Click “Add” next to the text box. Below this section, in the “Formula” space, enter (a/1000)/b and click “Apply.”

Suggested by Yu-Ting Chiang and Jesse LaBelle.

Let’s start with nominal. Economic variables are often quoted in nominal terms—that is, terms that are not adjusted for changes in prices over time. For example, it’s easy to find nominal oil prices in FRED.

In the FRED graph above, the blue line (left scale) depicts the end-of-month prices for West Texas Intermediate crude, an important oil market. This series is not adjusted for changes in the general price level. So, if one wants to know how much consumption of other goods one has to give up to buy a barrel of oil, then one needs to “deflate” the price of that barrel of oil by a price level that corresponds to a relevant basket of goods.

Now let’s get real. Fortunately, FRED allows us to construct and graph the real price of oil by deflating the nominal price by just such a price level. The red line (right scale) in the graph shows a real oil price series, after dividing the nominal price series by the consumer price index (CPI). The series is also normalized to equal 100 in January 1986, making it easy to calculate percentage changes from that date.

Comparing nominal and real prices. Placing the blue nominal price series next to the red real price series in the same graph provides a new perspective on recent oil price movements. Nominal oil prices rose to near-record levels in the first half of 2022, surpassed only by prices in 2008. This rise was associated with the Russian invasion of Ukraine: The green vertical line denotes March 2022, the first full month of the invasion. But deflating the nominal price by the CPI shows that real oil prices in early 2022 were not as high as the nominal series might suggest. In March and April 2022, real prices were 130% higher than in January 1986 but lower than they were for most of the 2010-2015 period.

Of course, the CPI isn’t the only price level or even necessarily the best price level to use as a deflator. For example, one could deflate by the personal consumption expenditures price index (PCE), which is the Fed’s favored inflation measure. Because PCE inflation tends to be lower than CPI inflation, using PCE inflation would produce a real oil price series that does not deviate quite as far from the nominal series as our graph above shows.

How this graph was created: This graph employs three features of FRED that will help you illustrate features of the data more effectively: formulas, 2-scale graphs, and marking of dates with vertical lines.

1. Open FRED and type “oil prices” in the search window. Select “Crude oil Price: West Texas Intermediate,” which will likely be the second choice in the search results.
2. Select “Edit Graph,” change the frequency from daily to monthly, and select “End of period” as the aggregation method.
3. From the same “Edit Graph” panel, select “Add Line” and search for “oil prices” in the search window and select “Crude oil Price: West Texas Intermediate.” Click “Add data series.” Again, change the frequency from daily to monthly and select “End of period” as the aggregation method.
4. Select “Edit lines” and choose “Edit line 2”: Go down to the “Customize data:” section and type “cpi” in the search box. Select “Consumer Price Index for all urban consumers: All items in the US city average” and click the “Add” button to the right.
5. Within the “Formula” box under “Customize data,” type “a/b” to create a real oil price series (that is, monthly oil prices deflated by the CPI price level). Click “Apply” to the right of the formula box. Select “Index (Scale value to 100 for chosen date”) under the “Units” window.
6. Select the “Format” tab at the top of the editing box and select “Right” under “Y axis position” for “Line 2.”
7. One can also mark chosen dates with vertical lines by selecting “Add line” in the “Edit Graph” panel: Click “Create user-defined line? [+]” and then “Create line.” For example, one can mark the approximate date of the early weeks of the Russian invasion of Ukraine —an important event in oil markets —by defining both the start and ending dates as “2022-03-01” and the “values start/end” as “0” to “140.”
8. Close the editing box. On the main graph page, select “Max” as the date range.

Suggested by Christopher Neely.

Today is October 31. Obviously that means the FRED Blog, like every other news and social media outlet, is celebrating Nevada’s admission to the Union on October 31, 1864. What’s so spooky about Nevada’s economy compared with, say, the economy of its neighbor California? Nevada’s economy is much smaller and much less diversified: Mining, entertainment, gambling, and hospitality services are outsized sectors compared with elsewhere. And, as with any portfolio, a lack of diversification brings big risks that typically manifest in volatility. Some find that scary.

Our first FRED graph, shown above, compares real GDP growth in Nevada and California. It’s easy to see it fluctuates much more in Nevada. In this state, one major sector affected by an adverse shock can send shivers through the whole state. This isn’t the case for a larger, diversified state such as California.

The story is similar for the growth of median household income—that is, the income for a household in the middle of the income distribution of all households. There’s more variability, up and down, in Nevada.

Our last graph shows per capita income. Note that the wild fluctuations even way back to the Great Depression were stronger in Nevada. Lesson: Although Nevadans may enjoy higher levels of risk and a good scare now and then, if you don’t have the stomach for economic volatility, then diversify!

How these graphs were created: Search FRED for each Nevada series, click on “Edit Graph,” and use the “Add Line” tab to search for the same California series. Apply units “Percentage change from year ago” to all lines.

Suggested by Christian Zimmermann.