Author: hubbardobrieneconomics

Glenn on the Importance of Research

An image generated by GTP-4o illustrating research.

This opinion column by Glenn appeared in the Financial Times on March 10.

The Trump administration has wisely emphasised raising America’s rate of economic growth. But growth doesn’t just happen. It is the byproduct of innovation both radical (think of the emergence of generative artificial intelligence) and gradual (such as improvements in manufacturing processes or transport). Many economic factors influence innovation, but research and development is key. While this can be privately or publicly funded, the latter can support basic research with spillovers to many companies and applications.

Therein lies the rub: the new administration’s growth agenda is joined by a significant effort to reduce government spending, spearheaded by the so-called Department of Government Efficiency. Some spending restraint can enhance growth by reducing interest rates or reallocating funds towards more investment-oriented activities. But cuts to R&D, as the administration is advocating at the National Institutes of Health (NIH), National Science Foundation (NSF), Department of Energy (DoE) and NASA, are counter-productive. They will limit innovation and growth.

The link between R&D and productivity growth has a long pedigree in economics and has generally been acknowledged by US policymakers. In the mid-1950s, economist Robert Solow made the Nobel Prize-winning conclusion that sustained output growth is not possible without technological progress. Decades later, former World Bank chief economist Paul Romer added another Nobel Prize-winning insight: growth reflected the intentional adoption of new ideas, so could be affected by research incentives.

It is well known that research is undervalued by private companies. Private funders of R&D don’t capture all its benefits. The social returns of R&D are two to four times higher than private returns. These high returns are enabled in the US by federal funding. For example, publicly funded research at the NIH has been found to significantly impact private development of new drugs.

In a comprehensive study, Andrew Fieldhouse and Karel Mertens classify major changes in non-defence R&D funding by the DoE, Nasa, NIH and NSF over the postwar period. They estimate implied returns of as much as 200 per cent — raising US economic output by $2 per dollar of funding. This is substantially higher than recent estimates of returns to private R&D. According to the Congressional Budget Office, the high returns to public funding are more than 10 times that on public investment in infrastructure. With the higher tax revenue generated from additional GDP, an increase in R&D funding more than pays for itself.

In aggregate, productivity gains from federal R&D funding are substantial. Indeed, Fieldhouse and Mertens estimate that government-funded R&D amounts to about one-fifth of productivity growth (measured as output growth less all input growth) in the US since the second world war.

Combined with the high social returns of government-funded R&D, it is essential that policymakers in the current administration acknowledge the risks of underfunding R&D. Spending cuts are clearly harmful to productivity and even budget outcomes.

A shift towards government-financed R&D does not imply that policy in these areas should be beyond review. Some economists have questioned whether current R&D projects take sufficiently high scientific risks, particularly on the ideas of younger scholars. And policymakers can certainly investigate whether indirect cost subsidies to universities and laboratories—in addition to the direct costs of research—are set at the appropriate levels. But, if growth is the objective, the presumption must be that additional public spending on R&D is worthwhile.

Federal support for growth-oriented R&D can extend beyond research grants. Publicly supported applied research centres around the country offer a mechanism to collaborate with local universities and business networks to disseminate ideas to practice. This builds upon the agricultural and manufacturing extension services instituted by 19th-century land-grant colleges that enhanced productivity.

The Trump administration is right to promote growth as a public objective. Spending restraint and fiscal discipline can be growth-enhancing. But all spending is equal. Government-funded R&D is vitally important for innovation and productivity growth. The case is clear.

Strong Jobs Report with No Sign of Recession

Image generated by GTP-4o

In a post earlier this week, we noted that according to the usually reliable GDPNow forecast from the Federal Reserve Bank of Atlanta, real GDP in the first quarter will decline by 2.8 percent. (The forecast was updated yesterday on the basis of additional data releases to a slightly less pessimistic –2.4 percent decline.) This morning (March 7), the Bureau of Labor Statistics (BLS) released its “Employment Situation” report (often called the “jobs report”) for February. The data in the report show no sign that the U.S. economy is in a recession. We should add the caveat, however, that at the beginning of a recession the data in the jobs report can be subject to large revisions.

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 either the employment data or the unemployment data from the household survey. (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 increase of 151,000 jobs during February. This increase was below the increase of 160,000 that economists had forecast. The previously reported increase for December was revised upward, while the previously reported increase for January was revised downward. The net change in jobs, taking the revisions for those two months together, was 2,000 lower than originally estimated. (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 payroll employment for each month in the last two years.

The unemployment rate rose slightly to 4.1 percent in February from 4.0 percent in January. As the following figure shows, the unemployment rate has been remarkably stable in recent months, staying between 4.0 percent and 4.2 percent in each month since May 2024. Last December, the members of the Federal Open Market Committee (FOMC) forecast that the unemployment rate for 2025 would average 4.3 percent.

As the following figure shows, the net change in jobs from the household survey moves much more erratically than does the net change in jobs from the establishment survey. The net change in jobs as measured by the household survey for February showed a sharp decrease of 588,000 jobs following a very large increase of 2,234,000 jobs in January. In any particular month, the story told by the two surveys can be inconsistent with employment increasing in one survey while falling in the other. The difference was particularly dramatic this month. (In this blog post, we discuss the differences between the employment estimates in the two surveys.)

Another concerning sign in the household survey is the fall in the employment-population ratio for prime age workers—those aged 25 to 54. The ratio declined from 80.7 percent in January to 80.5 percent in February. Although the employment-population is still high relative to the average level since 2001, it’s now well below the high of 80.9 percent in mid-2024. Continuing declines in this ratio would indicate a significant softening in the labor market.

It’s unclear how many federal workers have been laid off since the Trump Administration took office. The household survey shows a decline in total federal government employment of 10,000 in February. The household survey was conducted in the week that included February 12, so, it’s possible that next month’s jobs report may find a more significant decline.

The establishment survey also includes data on average hourly earnings (AHE). As we noted in this post, many economists and policymakers believe the employment cost index (ECI) is a better measure of wage pressures in the economy than is the AHE. The 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 the AHE from the same month in the previous year. The AHE increased 4.0 percent in February, up slightly from 3.9 percent in January.

The following figure shows wage inflation calculated by compounding the current month’s rate over an entire year. (The figure above shows what is sometimes called 12-month wage inflation, whereas this figure shows 1-month wage inflation.) One-month wage inflation is much more volatile than 12-month wage inflation—note the very large swings in 1-month wage inflation in April and May 2020 during the business closures caused by the Covid pandemic. The February 1-month rate of wage inflation was 3.4 percent, a decline from the surprisingly high 5.2 percent rate in December. Whether measured as a 12-month increase or as a 1-month increase, AHE is still increasing somewhat more rapidly than is consistent with the Fed achieving its 2 percent target rate of price inflation.

Today’s jobs report leaves the situation facing the Federal Reserve’s policy-making Federal Open Market Committee (FOMC) largely unchanged. There are some indications that the economy may be weakening, as shown by some of the data in the jobs report and by some of the data incorporated by the Atlanta Fed in its pessimistic nowcast of first quarter real GDP. But the Fed hasn’t yet brought inflation down to its 2 percent annual target. In addition, it’s unclear how the Trump Administration’s policies—particularly with respect to tariff increases—might affect the economy. Speaking today at an event at the University of Chicago, Fed Chair Jerome Powell observed the following:

“Looking ahead, the new Administration is in the process of implementing significant policy changes in four distinct areas: trade, immigration, fiscal policy, and regulation. It is the net effect of these policy changes that will matter for the economy and for the path of monetary policy. While there have been recent developments in some of these areas, especially trade policy, uncertainty around the changes and their likely effects remains high. As we parse the incoming information, we are focused on separating the signal from the noise as the outlook evolves. We do not need to be in a hurry, and are well positioned to wait for greater clarity.”

The likeliest outcome is that the FOMC will keep its target for the federal funds rate unchanged, perhaps for several meetings, unless additional data are released that clearly show the economy to be weakening.

One indication of expectations of future cuts in the target for the federal funds rate comes from investors who buy and sell federal funds futures contracts. (We discuss the futures market for federal funds in this blog post.) The data from the futures market indicates that investors don’t expect that the FOMC will cut its target for the federal funds rate at either its March 18–19 or May 6–7 meetings. As shown in the following figure, only at the FOMC’s June 17–18 meeting do investors assign a greater than 50 percent probability to the committee cutting its target. As of this afternoon, investors assign a probability of only 19.2 percent to the FOMC keeping its target unchanged at 4.25 percent to 4.50 percent at that meeting. They assign a probability of 80.8 percent to the committee cutting its target rate by at least 0.25 percentage point (25 basis points) at that meeting.

Are We in a Recession? Depends on Which Forecast You Believe

Image generated by GTP-4o of people engaging in economic forecasting

How do we know when we’re in a recession? Most economists and policymakers accept the decisions of the National Bureau of Economic Research (NBER), a private research group located in Cambridge, Massachusetts (see Macroeconomics, Chapter 10, Section 10.3). Typically, the NBER is slow in announcing that a recession has begun because it takes time to gather and analyze economic data. The NBER didn’t announce that a recession had begun in December 2007 until 11 months later in November 2008. When the NBER announced in June 2020 that a recession had begun in February 2020, it was considered to be an unusually fast decision.

On its website, the NBER notes that: “The NBER’s traditional definition of a recession is that it is a significant decline in economic activity that is spread across the economy and that lasts more than a few months.” The NBER lists the data it considers when determining whether a recession has begun (or ended), including: “real personal income less transfers (PILT), nonfarm payroll employment, real personal consumption expenditures, manufacturing and trade sales adjusted for price changes, employment as measured by the household survey, and industrial production.” In practice, it is normally the case that an NBER business cycle peak coincides with the peak in nonfarm payroll employment and an NBER business cycle trough coincides with a trough in the same employment series.

Of course, policymakers at the Fed don’t wait until the NBER announces that a recession has begun when formulating monetary policy. Members of the Fed’s policymaking Federal Open Market Committee (FOMC) monitor a wide range of data series as the series become available. The broadest measure of the state of the economy is real GDP, which is only available quarterly, and the data are released with a lag. For instance, the Bureau of Economic Analysis’s “advance” (first) estimate of real GDP in the first quarter of 2025 won’t be released until April 30.

Given the importance of GDP, there are several groups that attempt to nowcast GDP. A nowcast is a forecast that incorporates all the information available on a certain date about the components of spending that are included in GDP. The Federal Reserve Bank of New York and the Federal Reserve Bank of Atlanta both release nowcasts of GDP. They use different methodologies, so their forecasts are not identical. Today (March 3), the two estimates are surprisingly far apart. First, here is the nowcast from the NY Fed:

This nowcast indicates that real GDP will grow in the first quarter of 2025 at a 2.94 percent annual rate. That would be an increase from growth of 2.3 percent in the fourth quarter of 2024.

The nowcast from the Atlanta Fed—which they call GDPNow—is strikingly different:

The Atlanta Fed nowcast indicates that real GDP in the first quarter of 2025 will decline by 2.8 percent at an annual rate. If accurate, this forecast indicates that—far from the solid expansion in economic activity that the NY Fed is forecasting—the U.S. economy in the first quarter of 2025 will contract at the fastest rate since the first quarter of 2009, near the end of the severe 2007–2009 downturn (leaving aside the highly unusual declines in the first three quarters of 2020 during the Covid pandemic).

What explains such a large difference between these two forecasts? First, note that the Atlanta Fed includes in its graphic the range of forecasts from Blue Chip Indicators. These forecasts are collected from 50 or more economists who work in the private sector at banks, brokerages, manufacturers, and other firms. The graphic shows that the Blue Chip forecasters do not expect that the economy grew as much as the NY Fed’s nowcast indicates, but the forecasters do expect solid growth rate of 2 percent or more. So, the Atlanta Fed’s forecast appears to be an outlier.

Second, the NY Fed updates its nowcast only once per week, whereas the Atlanta Fed updates its forecast after the release of each data series that enters its model. So, the NY Fed nowcast was last updated on February 28, while the Atlanta Fed nowcast was updated today. Since February 28, the Atlanta Fed has incorporated into its nowcast data on the Institute for Supply Management (ISM) manufacturing index and data on construction spending from the Census Bureau. Incorporating these data resulted in the Atlanta Fed’s nowcast of first quarter real GDP growth declining from –1.5 percent on February 28 to –2.8 percent on March 3.

But incorporating more data explains only part of the discrepancy between the two forecasts because even as of February 28 the forecasts were far apart. The remaining discrepancy is due to the different methodologies employed by the economists at the two regional Feds in building their nowcasting models.

Which forecast is more accurate? We’ll get some indication on Friday (March 7) when the Bureau of Labor Statistics (BLS) releases its “Employment Situation” report for February. Economists surveyed are expecting that the payroll survey will estimate that there was a net increase of 160,000 jobs in February, up from a net increase of 143,000 jobs in January. If that expectation is accurate, it would seem unlikely that production declined in the first quarter to the extent that the Atlanta Fed nowcast is indicating. But, as we discuss in this blog post from 2022, macro data can be unreliable at the beginning of a recession. If we are currently in a recession, then even an initial estimate of a solid net increase in jobs in February could later be revised sharply downward.

As Expected, PCE Inflation Slows but Remains above Fed’s Target

Image generated by GTP-4o of people shopping.

Today (February 28), the BEA released monthly data on the personal consumption expenditures (PCE) price index as part of its “Personal Income and Outlays” report.  The Fed relies on annual changes in the PCE price index to evaluate whether it’s meeting its 2 percent annual inflation target.  The following figure shows PCE inflation (blue line) and core PCE inflation (green line)—which excludes energy and food prices—for the period since January 2016 with inflation measured as the percentage change in the PCE from the same month in the previous year. Measured this way, in January PCE inflation was 2.5 percent, down slightly from 2.6 in December. Core PCE inflation in January was 2.6 percent, down from 2.9 percent in December.  Headline and core PCE inflation were both consistent with the forecasts of economists.

The following figure shows PCE inflation and core PCE inflation calculated by compounding the current month’s rate over an entire year. (The figure above shows what is sometimes called 12-month inflation, while this figure shows 1-month inflation.) Measured this way, PCE inflation rose in January to 4.0 percent from 3.6 percent in December. Core PCE inflation rose in January to 3.5 percent from to 2.5 percent in December. So, both 1-month core PCE inflation estimates are running well above the Fed’s 2 percent target. But the usual caution applies that 1-month inflation figures are volatile (as can be seen in the figure), so we shouldn’t attempt to draw wider conclusions from one month’s data.

In recent months, Fed Chair Jerome Powell has noted that inflation in non-market services has been high. Non-market services are services whose prices the BEA imputes rather than measures directly. For instance, the BEA assumes that prices of financial services—such as brokerage fees—vary with the prices of financial assets. So that if stock prices rise, the prices of financial services included in the PCE price index also rise. Powell has argued that these imputed prices “don’t really tell us much about … tightness in the economy. They don’t really reflect that.” The following figure shows 12-month headline inflation (the blue line) and 12-month core inflation (the green line) for market-based PCE. (The BEA explains the market-based PCE measure here.)

Headline market-based PCE inflation was 2.2 percent in January, and core market-based PCE inflation was 2.3 percent. So, both market-based measures show less inflation in January than do the total measures. In the following figure, we look at 1-month inflation using these measures. Again, inflation is running somewhat lower when using these market-based measures of inflation. Note, though, that all four market-based measures are running above the Fed’s 2 percent target.

In summary, today’s data don’t change the general picture with respect to inflation: While inflation has substantially declined from its high in mid-2022, it still is running above the Fed’s target of 2 percent. As a result, it’s likely that the Fed’s policymaking Federal Open Market Committee (FOMC) will leave its target for the federal funds rate unchanged at its next meeting on March 18–19.

Investors who buy and sell federal funds futures contracts expect that the FOMC will leave its federal funds rate target unchanged at its next meeting. (We discuss the futures market for federal funds in this blog post.) As the following figure shows, investors assign a probability of 93.5 percent to the FOMC leaving its target for the federal funds rate unchanged at the current range of 4.25 percent to 4.50. Investors assign a probability of only 6.5 percent to the FOMC cutting its target by 0.25 percentage point (25 basis points).

As shown the following figure shows, investors assign a probability of greater than 50 percent that the FOMC will cut its target range by at least 25 basis points at its meeting nearly four months from now on June 17–18. Investors may be concerned that the economy is showing some signs of weakening. Today’s BEA report indicates that real personal consumption expenditures declined at a very high 5.5 percent compound annual rate in January. (Although measured as the 12-month change, real consumption spending increased by 3.o percent in January.)

We’ll have a better understanding of the FOMC’s evaluation of recent macroeconomic data after Chair Powell’s news conference following the March 18–19 meeting.

Technological Change Smacks Snacks

Photo from cnbc.com

What causes consumer demand for a product to decline?  Why does demand for some products suddenly rise?  As we discuss in Chapter 3, changes in the relative price of a substitute or a complement cause the demand for a good to shift. For instance, the following figure shows the recent rapid increase in the price of eggs, due in part from the spread of bird flu. We would expect that the increase in the price of eggs will shift to the right the demand curve for egg substitutes, such as the product shown below the figure.

Sometimes a shift in the demand for a product represents a change in consumer tastes. For instance, as we discuss in an Apply the Concept in Chapter 3, for decades most people wore a hat while outdoors. The first photo below shows people walking down a street in New York City in the 1920s. Beginning in the 1960s, hats started to fall out of fashion. As the second photo shows, today few people wear hats—unless they’re walking outside during the winter in the Northeast or the Midwest!

Photo from the New York Daily News

Photo from the New York Times

Technological change can also affect the demand for goods. For example, the development of network television, beginning in the late 1940s, reduced the demand for tickets to movie theaters. Similarly, the development of the internet reduced the demand for physical newspapers.

A recent example of technological change having a substantial effect on a number of consumer goods is the introduction of GLP–1 drugs, beginning in 2005. These drugs, such as Ozempic and Mounjaro, were first developed to treat type 2 diabetes. The drugs were found to significantly reduce appetite in most users, leading to users losing weight. Accordingly, doctors began to prescribe the drugs to treat obesity. By 2025, about half of the users of GLP–1 drugs were doing so to lose weight. A recent article in the Washington Post quoted Jan Hatzius, chief economist at Goldman Sachs, as predicting that by 2028, 60 million people in the United States will be taking a GLP–1 drug.

Many consumers who use these drugs decide to change the mix of foods they eat. Typically, users demand fewer ultra-processed foods, such as chips, cookies, and soft drinks. The percentage of people in the United States who are considered obese—having a body mass index (BMI) of 30 or greater—had been increasing for decades before declining slightly in 2023, the most recent year with available data. It seems likely that the increasing use of GLP–1 drugs helps to explain the decline in obesity.

People taking these drugs have also typically increased the share of foods they eat with higher levels of protein and fiber. These changes in diet are likely to lead to improved health, reducing the demand for some medical services. The number of people experiencing significant weight loss has already begun to reduce demand for extra-large clothing sizes and increase the demand for medium clothing sizes.

How much has the use of Ozempic and similar drugs reduced the demand for snacks? A recent study by Sylvia Hristakeva and Jura Liaukonyt of Cornell University and Leo Feler of Numerator, a market research firm, presents numerical estimates of changes in demand for different foods by users of GLP–1 drugs. The authors assembled a representative sample of 150,000 U.S. households and the households’ grocery purchases from July 2022 through September 2024. They estimate that the share of the U.S. population using a GLP–1 drug increased from 5.5% in October 2023 to 8.8% in July 2024.

The study finds that households with at least one person using a GLP–1 drug reduced their total grocery shopping by 5.5 percent or $416. The study gathered data on changes in the categories of food that households were buying six months after at least one person in the household began using one of these drugs. The figure below is compiled from data in the study.

As expected, purchases of snacks declined. The category of “chips and other savor snacks” (bottom row in the figure) declined by more than 11 percent. Purchases of sweet bakery products, cheese, cookies, soft drinks, ice cream, and pasta all declined by more than 5 percent. Purchases of yogurt, fresh produce, meat snacks, and nutrition bars, all increased. An article in the Wall Street Journal noted that “food makers are starting to understand better and cater to, in some cases with products specifically designed for” users of this drug. The image below shows some of the new products that Nestle—a major candy producer—has introduced to appeal to users of GLP–1 drugs. Nestle’s Vital Pursuit line of frozen packaged foods contain high levels of protein and fiber.

It’s too early to gauge the full effects of GLP–1 drugs on consumer demand. But it’s already clear that GLP–1 drugs are a striking example of technological change affecting demand in a major industry

Interesting Example of Price Discrimination at Walt Disney World

The pool at the All-Star Movie resort at Walt Disney World in Orlando, Florida (Photo from touringplans.com)

A recent article in the Wall Street Journal has the headline “Even Disney Is Worried About the High Cost of a Disney Vacation.” According to the article, “Some inside Disney worry that the company has become addicted to price hikes and has reached the limits of what middle-class Americans can afford ….”

As we discuss in Microeconomics, Chapter 15, the Walt Disney Company engages in price discrimination in a number of ways, by, for instance, charging more for ticket prices to its theme parks during the end-of-year holidays than on other days. Disney also offers hotels at different price levels, ranging from deluxe hotels like the Grand Floridian to more basic value hotels like the All-Star Movie Resort. In the case of hotels, some of the price difference is explained by differences in operating cost. Luxury hotels tend to have more amenities, including larger pools and restaurants on site, which raises their costs. Part of the difference in price, though, is the result of Disney estimating that people with higher incomes have a more inelastic demand for hotels than do people with lower incomes.

The Wall Street Journal article relies in part on data provided by Len Testa on his site touringplans.com. He notes that between 2018 and 2025, the percentage increase in the price Disney charged for staying at a value resort was less than the rate of inflation. In other words, the real price—the nominal price corrected for the effects of inflation—of staying at a Disney value resort decreased during that period. On the other hand, the percentage increase in the price Disney charged for staying at a deluxe was more than the rate of the inflation. So, the real price of staying at a Disney deluxe resort increased during this period.

One interpretation of these data is that over this period, Disney increased the extent of the price discrimination it was practicing with respect to hotel prices. It increased the gap between the price the families with more inelastic demand for Disney hotels pay and the price families with more elastic demand for Disney hotels pay. The article quotes Josh D’Amaro, who is the Disney executive in charge of the company’s theme parks, as saying “we intentionally offer a wide variety of ticket, hotel and dining options to welcome as many families as possible, whatever their budget.”

CPI Inflation in January Is Higher than Expected

Image generated by GTP-4o illustrating inflation

On February 12, the Bureau of Labor Statistics (BLS) released its monthly report on the consumer price index (CPI). The following figure compares headline inflation (the blue line) and core inflation (the dotted green line).

  • The headline inflation rate, which is measured by the percentage change in the CPI from the same month in the previous month, was 3.0 percent in January—up from 2.9 percent in December. 
  • The core inflation rate, which excludes the prices of food and energy, was 3.3 percent in January—up from 3.2 percent in December. 

Headline inflation and core inflation were both above what economists surveyed had expected.

In the following figure, we look at the 1-month inflation rate for headline and core inflation—that is the annual inflation rate calculated by compounding the current month’s rate over an entire year. Calculated as the 1-month inflation rate, headline inflation (the blue line) jumped from 4.5 percent in December to 5.7 percent in January—following a large jump in inflation from November to December. Core inflation (the dotted green line) more than doubled from 2.5 percent in December to 5.5 percent in January.

Overall, considering 1-month and 12-month inflation together, today’s data are concerning. One-month headline inflation is the highest it’s been since August 2023. One-month core inflation is the highest it’s been since April 2023. This month’s CPI report reinforces the conclusion from other recent inflation reports that progress on lowering inflation appears to have stalled. So, the probability of a “no landing” outcome, with inflation remaining above the Fed’s target for an indefinite period, seems to have increased. 

Of course, it’s important not to overinterpret the data from a single month. The figure shows that 1-month inflation is particularly volatile. Also note that the Fed uses the personal consumption expenditures (PCE) price index, rather than the CPI, to evaluate whether it is hitting its 2 percent annual inflation target.

As we’ve discussed in previous blog posts, Federal Reserve Chair Jerome Powell and his colleagues on the Fed’s policymaking Federal Open Market Committee (FOMC) have been closely following inflation in the price of shelter. The price of “shelter” in the CPI, as explained here, includes both rent paid for an apartment or a house and “owners’ equivalent rent of residences (OER),” which is an estimate of what a house (or apartment) would rent for if the owner were renting it out. OER is included in the CPI to account for the value of the services an owner receives from living in an apartment or house.

As the following figure shows, inflation in the price of shelter has been a significant contributor to headline inflation. The blue line shows 12-month inflation in shelter, and the green line shows 1-month inflation in shelter. Twelve-month inflation in shelter has been declining since the spring of 2023, but in January it was still relatively high at 4.4 percent. One-month inflation in shelter—which is much more volatile than 12-month inflation in shelter—rose sharply from 3.3 percent in December to 4.6 percent in January. Clearly a worrying sign given that many economists were expecting that shelter inflation would continue to slow.

To better estimate of the underlying trend in inflation, some economists look at median inflation and trimmed mean inflation.

  • Median inflation is calculated by economists at the Federal Reserve Bank of Cleveland and at Ohio State University. If we listed the inflation rate in each individual good or service in the CPI, median inflation is the inflation rate of the good or service that is in the middle of the list—that is, the inflation rate in the price of the good or service that has an equal number of higher and lower inflation rates. 
  • Trimmed-mean inflation drops the 8 percent of goods and services with the highest inflation rates and the 8 percent of goods and services with the lowest inflation rates. 

The following figure shows that 12-month trimmed-mean inflation (the blue line) jumped from 3.1 percent in December to 5.2 percent in January. Median inflation (the green line), which had been stable over the past five months, increased from 3.2 percent in December to 3.9 percent in January.

The following figure shows 1-month median and trimmed-mean inflation. One-month trimmed-mean inflation jumped from 3.1 percent in December to 5.1 percent in January. One-month median inflation rose from 3.2 percent in December to 3.9 percent in January. These data provide confirmation that (1) CPI inflation at this point is running higher than a rate that would be consistent with the Fed achieving its inflation target, and (2) that progress toward the target has slowed.

Looking at the futures market for federal funds, investors who buy and sell federal funds futures contracts are not expecting that the Fed’s policymaking Federal Open Market Committee (FOMC) will cut its target for the federal funds until this fall. (We discuss the futures market for federal funds in this blog post.) Investors assign a higher probability to the FOMC leaving its target range for the federal funds rate unchanged at 4.25 percent to 4.50 percent at its January, March, June, July, and September meetings. It’s not until the FOMC’s meeting on October 28-29 that, as shown below, investors assign a higher probability to a rate cut than to the committee leaving the rate unchanged.

The Strikingly Large Role of Foreign-Born Workers in the Growth of the U.S. Labor Force

As we noted in a recent post on the latest jobs report, the Bureau of Labor Statistics (BLS) has updated the population estimates in its household employment survey to reflect the revised population estimates from the Census Bureau. The census now estimates that the civilian noninstitutional population was about 2.9 million larger in December 2024 than it had previously estimated. The original undercount was significantly driven by an underestimate of the increase in the immigrant population.

The following figure shows the more rapid growth of foreign-born workers in recent years in comparison with the growth in native-born workers. In the figure, we set the number of native-born workers and the number of foreign-born workers both equal to 100 in January 2007. Between January 2007 and January 2025, the number of foreign-born workers increased by 40 percent, while the number of native-born workers increased by only 6 percent.

As the following figure shows, although foreign-born workers are an increasingly larger percentage of the total labor force, native-born workers are still a large majority of the labor force. Foreign-born workers were 15.3 percent of the labor force in January 2007 and 19.5 percent of the labor force in January 2025. Foreign-born workers accounted for about 56 percent of the increase in the total labor force over the period from January 2007 to January 2025.

H/T to Jason Furman for pointing us to the BLS data.

Strong Jobs Report in the Context of Annual Revisions to the Establishment and Household Surveys

Photo courtesy of Lena Buonanno

This morning (February 7), the Bureau of Labor Statistics (BLS) released its “Employment Situation” report (often called the “jobs report”) for January. This report was particularly interesting because it includes data reflecting the annual benchmark revision to the establishment, or payroll, survey and the annual revision of the household survey data to match new population estimates from the Census Bureau.

According to the establishment survey, there was a net increase of 143,000 jobs during January. This increase was below the increase of 169,000 to 175,000 that economists had forecast in surveys by the Wall Street Journal and bloomberg.com. The somewhat weak increase in jobs during January was offset by upward revisions to the initial estimates for November and December. The previously reported increases in employment for those months were revised upward by a total of 100,000 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 BLS also announced the results of its annual revision of the payroll employment data benchmarked to March 2024. The revisions are mainly based on data from the Quarterly Census of Employment and Wages (QCEW). The data in payroll survey are derived from a sample of 300,000 establishments, whereas the QCEW is based on a much more comprehensive count of workers covered by state unemployment insurance programs. The revisions indicated that growth in payroll employment between March 2023 and March 2024 had been overstated by 598,000 jobs. Although large in absolute scale, the revisions equal only 0.4 percent of total employment. In addition, as we discussed in this blog post last August, initially the BLS had estimated that the overstatement in employment gains during this period was an even larger 818,000 jobs. (The BLS provides a comprehensive discuss of its revisions to the establishment employment data here.)

The following table shows the revised estimates for each month of 2024, based on the new benchmarking.

The BLS also revised the household survey data to reflect the latest population estimates from the census bureau. Unlike with the establishment data, the BLS doesn’t adjust the historical household data in light of the population benchmarking. However, the BLS did include two tables in this month’s jobs report illustrating the effect of the new population benchmark. The following table from the report shows the effect of the benchmarking on some labor market data for December 2024. The revision increases the estimate of the civilian noninstitutional population by nearly 3 million, most of which is attributable to an increase in the estimated immigrant population. The increase in the estimate of the number of employed workers was also large at 2 million. (The BLS provides a discussion of the effects of its population benchmarking here.)

The following table shows how the population benchmarking affects changes in estimates of labor market variables between December 2024 and January 2025. The population benchmarking increases the net number of jobs created in January by 234,000 and reduces the increase in the number of persons unemployed by 142,000.

As the following figure shows, the unemployment rate, as reported in the household survey, decreased from 4.1 percent in December to 4.0 percent in January. The figure shows that the unemployment rate has fluctuated in a fairly narrow range over the past year.

The establishment survey also includes data on average hourly earnings (AHE). As we’ve noted in previous posts, many economists and policymakers believe the employment cost index (ECI) is a better measure of wage pressures in the economy than is the AHE. The 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 the AHE from the same month in the previous year. AHE increased 4.1 percent in January, which was unchanged from the December increase. By this measure, wage growth is still somewhat higher than is consistent with annual price inflation running at the Fed’s target of 2 percent.

There isn’t much in today’s jobs report to change the consensus view that the Fed’s policymaking Federal Open Market Committee (FOMC) will leave its target for the federal funds rate unchanged at its next meeting on March 18-19. One indication of expectations of future rate cuts comes from investors who buy and sell federal funds futures contracts. (We discuss the futures market for federal funds in this blog post.) As shown in the following figure, today these investors assign a probability of 91.5 percent to the FOMC keeping its target range for the federal funds rate unchanged at the current range of 4.25 percent to 4.50 percent at the March meeting. Investors assign a probability of only 8.5 percent to the FOMC cutting its target range by 25 basis points at that meeting.