Month: August 2026

Employment in July Unexpectedly Declined

This morning (August 7), the Bureau of Labor Statistics (BLS) released its “Employment Situation” report (often called the “jobs report”) for July. The report showed a decline in employment. 

The jobs report has two estimates of the change in employment during the month: one estimate from the establishment survey, often referred to as the payroll survey, and one from the household survey. As we discuss in Macroeconomics, Chapter 9, Section 9.1 (Economics, Chapter 19, Section 19.1), many economists and Federal Reserve policymakers believe that employment data from the establishment survey provide a more accurate indicator of the state of the labor market than do the household survey’s employment and unemployment data. (The groups included in the employment estimates from the two surveys are somewhat different, as we discuss in this post.) 

According to the establishment survey, there was a net decrease of 23,000 nonfarm jobs during July.  Economists surveyed by the Wall Street Journal had forecast an increase of 83,000 jobs.  Economists surveyed by FactSet had forecast a higher net increase of 100,000 jobs. The BLS revised downward its previous estimates of employment in May and June by a combined 103,000 jobs. (The BLS notes that: “Monthly revisions result from additional reports received from businesses and government agencies since the last published estimates and from the recalculation of seasonal factors.”)

The following figure from the jobs report shows the net change in nonfarm payroll employment for each month in the last two years. The figure shows that since peaking in March with a net increase of 214,000 jobs, job growth has slowed markedly over the last four months. Over the last three months, we’ve seen only an average of 20,000 net new jobs created.

The slow pace of recent job growth is consistent with the view among some economists that slowing labor force growth has driven the break-even rate of employment growth—the rate required to keep the unemployment rate constant—down to nearly zero

Despite the decrease in employment in July, the unemployment rate, which is calculated from data in the household survey, declined to 4.1 percent from 4.2 percent in June. The decline in the unemployment rate was due to a decline in the estimated size of the labor force. Although the estimated size of the labor force can fluctuate significantly from month to month, July was the fifth month in a row during which the labor force is estimated to have declined. Despite that fact, as the following figure shows, the unemployment rate has been remarkably stable over the past year and a half, staying between 4.0 percent and 4.4 percent in each month since June 2024. The Federal Open Market Committee’s current  estimate of the natural rate of unemployment—the normal rate of unemployment over the long run—is 4.2 percent. So, currently the unemployment rate is slightly below that estimate of the natural rate. (We discuss the natural rate of unemployment in Macroeconomics, Chapter 9 and Economics, Chapter 19.)

As the following figure shows, the monthly net change in jobs from the household survey moves much more erratically than does the net change in jobs from the establishment survey. As measured by the household survey, there was a net decrease of 87,000 jobs in July, roughly similar to the net decrease in employment shown in the establishment survey. Since January, the household survey has sown a net increase in jobs in only one month, with a total net decrease of 1.8 million jobs. In contrast, the establishment survey has shown a net increase of 426,000 jobs over the same period. (Note that because of last year’s shutdown of the federal government, there are no data for October or November.)

The household survey has another important labor market indicator: the employment-population ratio for prime age workers—those workers aged 25 to 54. In July, the ratio increased to 80.4 percent, partially reversing the sharp decline in June. The prime-age population ratio can show volatility from month to month but has remained above 80 percent every month since December 2022.

There have been media reports of firms, including Salesforce, Cloudflare, Coinbase, Cisco Systems, and Meta Platforms, laying off workers in information systems. The following figure shows net employment changes in the BLS employment category of “computing infrastructure providers, data processing, web hosting, and related services.” Employment in this sector has been declining during most months since the beginning of 2023. July was an exception with a net increase of 2,400 jobs.

The establishment survey also includes data on average hourly earnings (AHE). As we noted in earlier posts, many economists and policymakers believe the employment cost index (ECI) is a better measure of wage pressures in the economy than is AHE. AHE does have the important advantage of being available monthly, whereas the ECI is only available quarterly. The following figure shows the percentage change in AHE from the same month in the previous year. AHE increased 3.2 percent in July, down from 3.4 percent in June. The rate of increase in AHE has been below 4.0 percent each month since August 2025, indicating that cost pressure from wage increases has not been a significant source of price inflation during the past year.

With inflation having been above the Federal Reserve’s 2 percent annual target every month since March 2021, there has been increasing speculation that the Fed’s policymaking Federal Open Market Committee (FOMC) would increase its target for the federal funds rate at least once before the end of 2026. At the FOMC’s last meeting in late July, three members of the committee voted to increase the target, an unusual amount of dissent from a committee decision.

Does the slowdown in employment growth in recent months reduce the chance that the FOMC will increase its target range for the federal funds rate at its next meeting on September 15–16? Investors in the federal funds futures market believe that the answer is “yes.” Yesterday, investors assigned only a 45.0 percent probability to the committee keeping its target rate unchanged. This afternoon, that probability had increased to 55.9 percent. The BLS will release its estimate of inflation as measured by the consumer price index next Wednesday. That report will provide further evidence about the current state of inflation.

Solved Problem: Is Using Money Efficient?

Supports: Macroeconomics, Chapter 14, Section 14.1, Economics, Chapter 24, Section 24.1, and Money, Banking, and the Financial System, Chapter 2, Section 2.1.

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A rare book dealer who often posts to YouTube made the following observation in one of his videos:

“… thousands of years ago, they had the barter system where you could literally exchange wheat for barley and barley for wheat directly. And the idea behind that was to … have a quick solution for [a] transaction, but over time they invented a monetary unit—coinage and money—and they thought that that would inject some efficiency into economic transactions. And in some ways it’s done the complete opposite. There’s a lot of inefficiency because now unfortunately I cannot go right into Bloomingdale’s and take a nice black suit off the shelf and exchange it for a Geneva Bible. I actually have to sell the Bible first … then go buy the suit. So that gives me a lot of extra work, so I’d rather go back to bartering ….”

The dealer may not have been entirely serious, but assuming that he was, is he correct that transacting using barter is more efficient than transacting using money? In your answer, be sure to define “efficient” in this context.

Solving the Problem
Step 1: Review the chapter material. This problem is about the efficiency of using money to purchase goods rather than engaging in barter, so you may want to review Macroeconomics, Chapter 15, Section 15.1, “What Is Money and Why Do We Need It?”

Step 2: Answer the problem by explaining why using money is more efficient than engaging in barter. The book dealer is correct that thousands of years ago, most societies used barter rather than money. Societies transitioned from barter to money because of the inefficiencies of barter. A key inefficiency of barter is the need for a double coincidence of wants. For a barter transaction to take place, each person must want what the other person has. It’s not enough for the book dealer to want a black suit from the Bloomingdale’s department store; Bloomingdale’s must be willing to trade the suit for a copy of the Geneva Bible—which is unlikely.

To use a copy of the Geneva Bible to obtain a suit using barter, the book dealer might have to make—possibly many—additional trades until he obtains some good that Bloomingdale’s would accept in exchange for the suit. In practice, it might be difficult to find such a good and doing so would likely involve substantial search costs.

We can conclude that money has replaced barter in most transaction because it is more efficient in the sense that it allows transactions to be completed at a lower cost.

 

Breaking News: Demand Curves Slope Downward!

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The following was the first sentence of an article yesterday on axios.com discussing the market for beef: “Beef sales are plunging, but processors continue to raise prices as a yearslong cattle shortage strains the industry.”

The sentence seems to be describing a paradox: Why would meat processors, such as Tyson, JBS, and Cargill, raise beef prices if their sales are falling? The key to resolving the apparent paradox is the reference to a “cattle shortage.” The number of cattle raised in the United States has been declining for several reasons, including severe drought in cattle-raising states—which has reduced the pasture that cattle forage on—and a reduction in beef imports from Mexico as the United States Department of Agriculture (USDA) tries to limit the spread of screwworm.

In other words, using the model of demand and supply we develop in Chapter 3 of Microeconomics, the supply curve for beef in the United States has shifted to the left. The result is shown in the following figure:

When the supply curve shifts to the left from S1 to S2, the price of beef rises from P1 to P2 and the equilibrium quantity of beef falls from Q1 to Q2. In other words, when a market experiences a decline in supply, we would expect to observe both higher prices and falling sales. So, the situation described in the first sentence of the article is not a paradox, but instead reflects the normal working of demand and supply in a market. You can explain a lot just by knowing that demand curves slope downward!

The article also observes with respect to Tyson Foods that: “In its most recent quarter, ended June 27, beef volumes declined by 15.9% from a year ago, while prices Tyson charged grocery stores, restaurants and other customers rose 12.1%.” The USDA estimates that the retail price elasticity of demand for beef is about –1. If we assume that no other factors affecting the demand for Tyson’s beef changed during this three-month period, then the price elasticity of demand for Tyson’s beef is –15.9%/12.1% = –1.3. (Note that the USDA elasticity estimates are for beef sold in supermarkets and other retail venues. So the estimates may not directly apply to sales to restaurants and “other customers.”)

We would expect that the price elasticity of demand for Tyson’s beef would be larger (in absolute value) than the price elasticity of demand for beef as a good. As we discuss in Chapter 6 of Microeconomics, if the price of one brand of a good increases, consumers can switch to another brand. In this case, if the price of Tyson’s beef increases, some consumers will switch to Cargill’s or some other firm’s beef. But if the price of beef as a good increases, consumers would have to eat a different protein to avoid the price increase.

What Explains the Rise in 30-Year Treasury Yields?

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At the close of trading on Friday, July 31, the yield on the 30-year Treasury bond was 5.28 percent. As the following figure shows, that yield was the highest since July 2007, before the Global Financial Crisis and the Great Recession of 2007–2009.

Note: As we discuss in Money, Banking, and the Financial System, Chapter 3, when economists refer to the interest rate on a bond, they are referring to the bond’s yield to maturity. (A new edition of our textbook is now available.)

The figure shows the nominal yields on the 30-year Treasury bond—the yield not corrected for the effects of inflation.  What factors can cause the nominal yield on Treasury bonds to increase? Because investors are interested in the real yield on Treasury bonds—the yield corrected for the effects of inflation—an increase in the expected inflation rate will cause the nominal yield to rise. The Fisher effect refers to the assertion by Yale economist Irving Fisher that the nominal interest rate on a bond rises point-for-point with increases in the expected inflation rate. Although the pure Fisher effect doesn’t typically hold, there’s no doubt that changes in the expected inflation rate are a key driver of changes in nominal bond yields.

The other main driver of nominal bond yields is changes in the demand for credit. The Congressional Budget Office forecasts that, because of continuing federal government budget deficits, the value of publicly held Treasury securities will rise “from 101 percent of GDP in 2026 to 120 percent in 2036, well above the previous record of 106 percent just after World War II.” Such substantial increases in the supply of Treasury bonds will lower their prices, raising their nominal yields.

The market for Treasury bonds is linked to the market for corporate bonds. Although not all investors who buy Treasury bonds also buy corporate bonds and vice versa, many investors participate in both markets. As a result, a surge in the supply of corporate bonds will raise both their yields and the yields on Treasury bonds. As the following figure shows, the yields on high-quality corporate bonds (those rated A, AA, or AAA), have moved roughly in synch with Treasury yields, with recent increases in corporate yields mirroring the increases in Treasury yields.

The surge in the supply of corporate bonds has been driven by so-called hyperscalers, such as Amazon, Google, Oracle, and Microsoft, who have been raising hundreds of billions of dollars to fund the building of data centers to power AI programs.

In recent days, there has been much discussion as to whether the increased supply of bonds or rising expectations of future inflation have been behind the surge in Treasury yields. Following the latest meeting of the Federal Open Market Committee (FOMC) on Wednesday, July 29, Fed Chair Kevin Warsh’s press conference left many industry analysts believing that Warsh would be willing to tolerate higher rates of inflation. If, on the other hand, Warsh had been interpreted as willing to raise the FOMC’s target for the federal funds rate in the near future, that may have reassured investors that future rates of inflation would be lower, which would have brought down Treasury yields. An article in the Wall Street Journal quoted Mark Cabana, head of U.S. rates strategy at Bank of America as saying: “If you actually want to get long-end rates down, there’s an argument that you need to raise front-end rates [that is, the target for the federal funds rate] right now in order to establish that credibility.”

The following figure from the Wall Street Journal shows that during Warsh’s press conference, the yield on the 30-year Treasury bond rose sharply.

Despite the immediate reaction of bond investors to Warsh’s press conference, there isn’t much indication that in recent weeks a significant rise in investors’ expectations of inflation has been the key driver of increases in the Treasury bond rate.

In January 1997, the U.S. Treasury started issuing indexed bonds to address investors’ concerns about the effects of inflation on real interest rates. With these bonds, called TIPS (Treasury Inflation-Protected Securities), the Treasury increases the principal, or face value, as the price level increases, as measured by the CP. The stated interest rate on a TIPS remains fixed once issued, but because it is applied to a principal amount that increases with inflation, the effective interest rate increases with inflation. For example, suppose that when issued, a 30-year TIPS has a principal of $1,000 and a coupon rate of 3%. (The coupon rate equals the coupon payment divided by the face value, or par value, of a bond.) If the inflation rate during the year is 2%, then the principal increases to $1,020. So, the investor would receive the coupon rate of 3% plus the 2% increase in the principal, or 5%. In the rare case in which the economy experiences deflation, with the price level falling, the principal of a TIPS will decrease.

If we compare the yield on a TIPS of a given maturity to the yield on a non-TIPS Treasury security of the same maturity, we have an estimate of the annual inflation rate investors expect over that time period. For example, if the yield on a non-TIPS 30-Year Treasury bond is 5% and the yield on a 30-year TIPS is 2%, investors expect an annual inflation rate of 3% over the next 30 years. The difference between the yield on the non-TIPS 30-year Treasury bond and the yield on the 30-year TIPS is called the 30-year breakeven inflation rate because at that inflation rate, an investor would expect the same real yield from buying either the TIPS or the non-TIPS bond.

The following figure shows, for the period beginning in January 2022, the daily yield to maturity on the 30-year Treasury bond (the blue line), the yield on the 30-year TIPS (the orange line), and the implied 30-year breakeven inflation rate (the green line). Note that values for the green line are usually close to 2%, which is the Fed’s long-run inflation target. Even during 2022, when inflation as measured by the CPI reached 9%, this measure of expected inflation never rose above 2.7%. When the expected inflation rate changes relatively little during a period when the actual inflation rate is fluctuating, expectations of inflation are said to be well anchored.


A reasonable conclusion is that, to this point, the rise in long-term bond yields appears to be driven more by the increasing supply of Treasury and corporate bonds than by higher expected inflation.

(We should note that some economists question the accuracy of using breakeven inflation as a measure of expected inflation for two reasons: (1) An investor buying a TIPS is protected against the possibility that the inflation rate might turn out to be higher than expected. As a result, investors may be willing to accept a slightly lower interest rate on TIPS, which would lead to an
overestimate of the expected inflation rate. (2) The volume of TIPS traded on any given day is much smaller than volume of non-TIPS Treasury securities traded, which make TIPS slightly less liquid—meaning they are slightly more difficult to sell. Investors typically require a higher interest rate to buy a less liquid asset. So, this outcome might have the opposite effect of the first one—an underestimate of the expected inflation rate.)