The FRED® Blog

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

Paychecks at the top, at the bottom, and in the middle

A look at the distribution of wage income

Let’s consider the topic of income disparity by looking at some data from our friends at the Bureau of Labor Statistics—or, as we like to call them, the BLS. (Just to clarify: Top incomes are increasing more than others not so much because of regular labor income, but largely because of capital income, various bonuses, and the like. That said, in this post we’ll stick with the distribution of regular wage income.)

The BLS’s Current Population Survey provides weekly wage income data for the U.S. population that can be split into various segments: These segments are ordered by income, from the very top (100%) to the very bottom (1%). The segments we chose, from top to bottom in the graph, are the 90%, 75%, 25%, and 10% levels. (That is, the ninth decile, the third quartile, the first quartile, and the first decile.) The reported income for each of these segments is divided by the median income to show how each segment compares with the wage earner in the middle of the entire distribution.

So, what do we learn from this graph? For one thing, in 2018, the wage earner at the 90% level got 2.4 times what the median wage earner got. The wage earner at the 10% level got half of what the median wage earner got. It appears that the two bottom segments (25% and 10%) are rather stable compared with the median, except for a surprising improvement recently for the 10% level. The 75% level is almost completely flat. The 90% level is showing a gradual increase, about 10% over the 18 years for which we have data. Although wage income disparity isn’t as spectacular as total income disparity, it is increasing.

How this graph was created: From the release table with the wage quantiles, select the series you want and click “Add to Graph.” If necessary, restrict the sample period to include all series. From the “Edit Graph” panel, add to each line the median statistic (series ID LEU0252887700A), applying formula a/b. From the “Format” tab, move the lines so that the order of the legends matches the order of the lines in the graph. Finally, de-select the “Show: Title” option, as the legends take waaaaaay too much space. (The legends are mostly still visible when you hover over the lines, though.)

Suggested by Christian Zimmermann.

View on FRED, series used in this post: LEU0252887700A, LEU0252916000A, LEU0252916100A, LEU0252916200A, LEU0252916300A

The give and take of technology

Changes in U.S. imports and exports of intellectual property

The U.S. creates many technological innovations that the rest of the world wants to use. The FRED graph above tracks how much technology the U.S. exported to the rest of the world from 2002 to 2018 (blue line), as measured by payments the world made for the use of U.S. intellectual property (IP). These payments, in the form of royalties and licensing fees, increased from $67 billion to about $118 billion, showing that the U.S. has substantially increased the knowledge it shares globally.

The U.S. also seeks out technology it doesn’t produce at home. So our graph also displays what the U.S. imported from the rest of the world (red line), as measured by the royalty payments the U.S. made to all other countries for the use of their IP. Take care to connect the exports with the left axis and the imports with the right axis, and you can see that the U.S. transfers much more knowledge than it receives from the rest of the world. But the graph also reveals some finer points.

  1. During the Great Recession of 2008-09, real U.S. exports of IP decreased slightly but real U.S. imports of IP kept increasing. In fact, the U.S. has been on a largely continuous trajectory of technology imports, even during periods when its technology exports have declined.
  2. The U.S. has imported IP from the rest of the world at a faster pace than it has exported it. During 2002-2018, real royalties from U.S. technology exports increased by 75%, but real royalties from U.S. technology imports increased by 113%. The last four years of the sample are largely responsible for this faster pace: Since 2015, royalties from U.S. technology imports have grown by 30%, considerably faster than the -2.5% rate for exports.

So, is foreign technology increasing its contribution to U.S. innovation?

Data from the OECD provide some highlights: The main contributors of technology transfer to the U.S. are the European Union and Japan, accounting for 45% and 21% of payments, respectively, in 2017. Although a much smaller contributor, China has increased its technology transfer to the U.S. In 2002, China’s share of U.S. royalties for foreign IP was 0.1%; by 2017, its share had increased to almost 2%—which could be an indication China will become one of the leaders in global innovation and knowledge sharing.

How this graph was created: Search for and select the annual series “Real exports of services: Royalties and license fees”; from the “Edit Graph” panel, use the “Add Line” option to search for and select the annual series “Real imports of services: Royalties and license fees.” In the “Format” tab, for Line 2, click “Right” under the “Y-Axis position” label to shift its y-axis to the right side of the graph.

Suggested by Makenzie Peake and Ana Maria Santacreu.

View on FRED, series used in this post: B684RX1Q020SBEA, B908RX1Q020SBEA