The FRED® Blog

Is household wealth overvalued?

Fluctuations in household net worth relative to income

When economists look at household wealth, they’re often concerned about the individual assets that make up that wealth—specifically, that they may be overvalued. Thankfully, FRED has an indicator to help us evaluate household wealth: The ratio of household net worth to disposable personal income. This ratio remained nearly constant for 50 years before the dot-com bubble (roughly 1994-2000), when it started increasing. And an increasing ratio may signal that the assets underlying net worth are overvalued. Since 2017, household net worth relative to income (dashed blue line) generally has been above its previous record level from the year before the Great Recession.

We also include the value of financial assets, a component of net worth, relative to income (solid green line). Most variations in net worth relative to income are associated with changes in the value of financial assets, which is indicated by the way the two lines track closely together in the graph. Even when housing values were collapsing and net worth fell (from $6.64 billion to $5.25 billion, or 1.4 times disposable income), the decline in the value of financial assets was 50% of that decline in net worth (from $5.07 billion to $4.37 billion). In terms of the recovery of net worth relative to income, which didn’t start until late 2012, we see again that the majority (65%) is accounted for by the rise in the value of financial assets.

How this graph was created: Search for “Household net worth” and select  “Households and nonprofit organizations; net worth, Level.” From the “Edit Graph” panel, use the “Customize Data” option to search for “Disposable Personal Income” and select the quarterly series in billions of dollars. After adding this series, enter “a/b” in the “Formula” box. This will show the ratio of household net worth to disposable income. To add the second line, use the “Add Line” option to search for and add the series “Households and nonprofit organizations; total financial assets, Level.” Then repeat the same process of dividing by disposable personal income.

Suggested by Ryan Mather and Juan Sánchez.

View on FRED, series used in this post: DPI, TFAABSHNO, TNWBSHNO

Taking the time to measure money

A closer look at broad money in the U.K.

The FRED graph above, which tracks broad money in the U.K. over the past 172 years, makes it look like the Bank of England has let the money supply go completely out of control since 1970. But not so fast! Two important effects are at play here. The first is the power of compounding: Any statistic that increases at a constant rate will look like it is accelerating, especially if the sample period is long. That’s why FRED graphs offer the option of taking the natural logarithm, as shown in the second graph, below.

If broad money had increased at a constant rate, the graph would show a straight line. That’s not the case, though, as broad money reacts to economic conditions, which is the second effect at play here. Consider that the money supply follows the general evolution of prices. Or the reverse: Prices follow increases in the money supply. In any case, we deflate broad money by the consumer price index, as shown in the third graph, below.

This new statistic is still skyrocketing. But that’s because the U.K. economy has actually grown during most of the period. In our fourth graph, show below, we divide broad money by nominal GDP, which takes into account inflation, population growth, and increases in productivity in one fell swoop. Our final statistic is less dramatic, but it still shows some sort of effect that keeps propelling broad money upward. What could it be?

Let’s stop and define what broad money actually is. As you may have guessed, it’s the broadest possible definition of money, which encompasses all forms of assets that could possibly be used for transactions: from currency all the way to savings accounts and large time deposits. (In the U.S., we call it M3.) And, as an economy becomes more financially developed, broad money grows more than what nominal GDP would account for. This is what we see here.

How these graphs were created: Search for and select “broad money United Kingdom” and you have the first graph. Use the “Edit Graph” panel to create the others: For the second, choose units “Natural Logarithm.” For the third, add a series to the line by searching for and selecting the “United Kingdom CPI” (in levels, with a long sample) and apply formula a/b. For the fourth, replace the CPI series with “nominal GDP United Kingdom.”

Suggested by Christian Zimmermann.

View on FRED, series used in this post: CPIUKA, MSBMUKA, NGDPMPUKA

The stock market is not the economy

Taking a "random walk" through the data

Does the stock market tell us anything about the economy? The stock market seems to react continually to various data and economic news, and many of us follow its day-to-day changes, especially if we’re invested in it. But do fluctuations in the stock market actually reflect economic health?

The best measure we have for measuring total economic activity is GDP. But GDP is measured only quarterly and with a considerable lag. With the help of FRED, though, we can look at a decade’s worth of data to see how closely GDP relates to the stock market.

The graph above looks at quarter-to-quarter percent changes in the Dow Jones Industrial Average (DJIA), deflated to remove general price increases, and real GDP, which is by definition also deflated to remove general price increases. Of course, the stock market is very volatile, but it’s too hard to see any relationship in this line graph. A better way to visualize connections (or a lack of connections) is a scatter plot, shown below, with the same data.

If the two measures were related, we would see the points clustered in the lower left, middle, and upper right. But we don’t see that. One reason may be that the DJIA covers only 30 firms. While they’re large firms, they make up only a fraction of the economy. So we built the same graph (below) with data from the S&P500, which encompasses the 500 largest firms on the stock market. But no luck: We still don’t see any relationship.

So why are GDP and the stock market graphically unrelated? First, it’s important to understand what the value of a stock measures: the sum of discounted expected dividends plus a liquidation value of capital. In other words, what the market thinks the future dividends of the firm will be, evaluated at current prices, and what could be obtained from liquidation if the firm goes bankrupt. Note that dividends are only a small part of the firm’s income; dividends don’t account for any income that’s directed toward taxes, servicing loans and bonds, and (maybe most importantly) wages. The labor income share of total income in the economy is about 60%. And, as recently noted on this blog, the labor income share has decreased. Now, if regulation or laws reduce the bargaining power of labor, for example, labor income decreases, capital income and dividends increase, but total income may not have changed or even decreased.

How these graphs were created: Search for “Dow Jones,” select the Industrial Average series, and click on “Add to Graph.” Click on “Edit Graph,” add the “GDP deflator,” apply formula a/b, and set units to “Percent change.” From the “Add Line” tab, search for and select “real GDP,” and set units to “Percent change.” Once you restrict the sample to the last 10 years, you have the first graph. For the second, take the first, use the “Edit Graph” panel to open the “Format” tab and select type “Scatter.” For the third graph, replace the DJIA with SP500. You can then expand the sample.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: DJIA, GDPC1, GDPDEF, RU3000TR, SP500


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