Tag: Federal Reserve

Economics-Watching: Where Could Reshoring Manufacturers Find Workers?

[from the Federal Reserve Bank of Cleveland, 9 October, 2025]

by Stephan D. Whitaker, Senior Policy Economist

The United States has lost millions of manufacturing jobs in recent decades, but a variety of policies have been enacted to incentivize the creation of manufacturing jobs in America. This District Data Brief analyzes where manufacturers might find US workers to fill these roles.

Introduction

The announcement of new tariffs this year has reignited the discussion of whether the United States can expand its manufacturing employment by millions of workers. Reversing decades of manufacturing job losses is one explicit goal of the new higher tariffs. This District Data Brief presents measures of employment and demographics as context around the current and potential employment in US manufacturing. Raising manufacturing employment by 4 to 6 million workers would constitute a large increase relative to current levels. However, an increase of this scale would not be large relative to the global growth of manufacturing employment in recent decades, the current US labor force size, or the number of US adults not engaged in high-paying work.

With different priorities and approaches, policymakers have spent much of the past decade addressing issues related to the loss or absence of manufacturing in the United States. For example, America’s dependence on imported manufactured goods was highlighted at the beginning of the COVID-19 pandemic as supply chain disruptions led to shortages of medical equipment, pharmaceuticals, microchips, and other products. The CHIPS and Science Act and the Inflation Reduction Act featured tax breaks and subsidies to expand US manufacturing capacity for semiconductors, electric vehicles, and renewable energy equipment.

At the same time, economists have been documenting the loss of work opportunities and earning power by workers without college degrees as manufacturing employment has declined. In 2013, David Autor, David Dorn, and Gordon Hanson published a study that estimated the labor market impacts resulting from increased trade competition following China’s entrance into the World Trade Organization, an effect often referred to as the “China shock.” Dozens of studies have since used the regional variation in job and income losses caused by the China shock to measure the adverse impacts of job displacement on family structures, crime, health, and other social indicators. Some supporters of industrial subsidies and higher tariffs have expressed the hope that these dynamics can be put into reverse.

Read the full article [archived PDF].

Economics-Watching: Estimating the Effects of Monetary Policy: An Ongoing Evolution

New monetary policy tools have lengthened the interval over which policy news is transmitted and processed.

[from the Federal Reserve Bank of Kansas City, 2 October 2025]

by Karlye Dilts Stedman, Amaze Lusompa & Phillip An

Disentangling how the economy responds to a monetary policy decision from its response to macroeconomic conditions at the time of the decision is an ongoing challenge. One popular method researchers use to measure the effect of a monetary policy announcement—high-frequency identification—analyzes the reaction of fast-moving financial variables immediately following the policy announcement, using a time window long enough for markets to respond but not so long that the response is contaminated by other information.

Since high-frequency identification was introduced in the early 2000s, policymakers have introduced tools such as forward guidance and large-scale asset purchases. Karlye Dilts Stedman, Amaze Lusompa, and Phillip An examine how the evolution of monetary policy has changed high-frequency identification and assess whether additional changes might be necessary to better capture the effect of modern monetary policy surprises. Although researchers have continually updated the asset mix used in high-frequency identification over time, they have not updated the measurement window. Because the timing of monetary policy communication has changed significantly in recent years, refining the length of this measurement window may be necessary going forward.

Read the full article [archived PDF].

Economics-Watching: Tracking the Economy in Real‑Time Through Regional Business Surveys

[from the Federal Reserve Bank of New York’s The Teller Window, 23 September 2025]

by Richard Deitz and Kartik Athreya

Federal Reserve policymakers need current information about economic conditions to make well-informed monetary policy decisions. But hard data, such as GDP and the unemployment rate, is released with a significant lag, making it difficult to get a precise, real-time read on the economy, especially during times of rapid change.

To help fill the gap, the New York Fed conducts two monthly regional business surveys: the Empire State Manufacturing Survey of manufacturers in New York state and the Business Leaders Survey, which covers service sector firms in New York state, northern New Jersey, and Fairfield County, Conn. These surveys provide timely soft data, available well before hard data is released.

Hard data is based on precise quantitative measurements, such as sales figures or the specific prices firms are charging. By contrast, soft data is qualitative, focusing on trends, expectations, and sentiment around economic activity. And while hard data looks backward, soft data from the regional surveys can look forward—providing important information about expectations for the future and emerging trends.

Gathering soft data quickly can be impactful—for example, the Empire State Manufacturing and Business Leaders surveys signaled a sharp downturn in economic activity in early March 2020 [archived PDF], providing a warning weeks before official statistics captured the full extent of the COVID pandemic’s economic impact.  

How the Surveys Work

The New York Fed launched the Empire State Manufacturing Survey in 2001. It was modeled after the Philadelphia Fed’s Business Outlook Survey, a long-running manufacturing survey that has historically been watched by financial markets and policymakers as an early signal about national manufacturing conditions. The Business Leaders Survey was launched later in 2004 and was among the first regional business surveys to target the service sector.

The surveys are sent to over 300 business executives and managers at firms across industries during the first week of every month. While about two-thirds of participating firms have 100 or fewer employees, some have hundreds or thousands of workers.

Leaders at the firms fill out a short questionnaire asking if business activity has increased, decreased, or stayed the same compared to the prior month. The surveys ask about indicators such as prices–yielding insights into inflationary pressures–as well as employment, orders, and capital spending. Respondents answer questions about how they expect these indicators to change over the next six months, offering a forward-looking perspective on the economy’s trajectory.

From the responses, New York Fed researchers construct diffusion indexes by calculating the difference between the percentage of firms reporting increased activity and those reporting decreased activity. Positive values indicate that more firms say activity increased than decreased, suggesting activity expanded over the month. Higher positive values indicate stronger growth, while lower negative values indicate stronger declines.

The surveys include local businesses, like restaurants and car dealerships, as well as firms with national and global reach, such as software manufacturers and shipping enterprises. As a result, the economic indicators derived from the surveys are often early predictors of national economic patterns, frequently aligning with hard data released later.

Getting Answers on Current Issues

The surveys regularly ask supplemental questions about current economic issues to get real-time answers. Over the last few years, the surveys have asked about firms’ experience with tariffs, inflation expectations, if the use of AI is leading to a reduction in employment, how often employees work from home [archived PDF], and whether supply availability was affecting their businesses.

Going Beyond the Indicators

In addition to providing data to track economic conditions, the regional surveys also provide a channel to hear directly from local business leaders. Every month, survey respondents are asked for their comments, offering the opportunity for businesses to share their thoughts, concerns, and experiences with the New York Fed. This helps researchers and policymakers understand how businesses are being affected by economic conditions.

The surveys act as one of the bridges between the New York Fed and the business community, ensuring the voices of regional businesses are considered in economic assessments and policy discussions as well as enhancing the ability of policymakers to make informed decisions to respond effectively to economic challenges.

Executives, owners, or managers of businesses in New York, northern New Jersey, or Fairfield County, Conn., interested in participating in the New York Fed’s monthly business surveys can find more information here. The next survey results will be released on Oct. 15 and 16.

Economics-Watching: SF FedViews: September 4, 2025

[from the Federal Reserve Bank of San Francisco]

Andrew Foerster, senior research advisor at the Federal Reserve Bank of San Francisco, shared views on the current economy and the outlook from the Economic Research Department as of September 4, 2025.

While economic activity in the United States has remained resilient, recent data show some softening in the labor market. Swings in net exports affected GDP in the first half of 2025, with imports surging in the first quarter followed by imports declining in the second quarter. Inflation remains above the Fed’s 2% goal, and a near-term rise from tariffs appears likely. Job gains in recent months have slowed. Downward revisions for recent job growth estimates have been large, but the magnitudes of these revisions are not out of line with historical values. Job growth estimates remain reliable despite data collection challenges. With the balance of risks surrounding the Fed’s dual mandate now shifting, market participants are projecting an easing of monetary policy in coming months.

Read the full article [archived PDF].

Economics-Watching: Why Businesses Say Tariffs Have a Delayed Effect on Inflation

[from the Federal Reserve Bank of Richmond, 8 August, 2025]

by R. Andrew Bauer, Renee Haltom and Matthew Martin

Regional Matters

Ever since new tariffs were enacted in early 2025, a key policy question has been what is the extent to which businesses will pass tariff costs through to prices, and when? The effects of a tariff are rarely straightforward, given, among other things, competitive dynamics and the challenges of implementation, but the historically large and changing nature of these tariffs have created additional levels of uncertainty over the effects.

In uncertain times, anecdotal evidence from businesses can be especially insightful. We are learning how businesses are reacting to tariffs through the Richmond Fed’s business surveys as well as through hundreds of one-on-one conversations with Fifth District businesses since the start of 2025.

These conversations showcase that navigating tariffs is a complex and sometimes protracted process for firms, particularly when there is uncertainty. Firms describe several reasons they may not have experienced the full impact of proposed tariffs yet (even when goods and countries they deal with are subject to them), as well as reasons that even when they have incurred tariff-related cost increases, there can be a delayed impact on pricing decisions.

Reasons Firms May Not Have Incurred Tariffs Yet

Business contacts describe several strategies or circumstances that can delay or reduce the tariffs on inputs or other imported items. These include the following:

As our monthly business surveys have found, many firms report deploying more than one strategy to delay tariffs. Notably, many of these delays are only temporary.

Reasons Tariffs May Have a Delayed Impact on Prices

Even when firms have incurred tariffs, they give several reasons why tariffs may not be immediately reflected in the prices they charge for their products. These include the following:

  • Waiting for tariff policy to clarify. Higher prices could reduce demand for goods and services and/or lead firms to lose market share, so many firms said they are hesitant to increase prices until they’re sure tariffs will remain in place. For example, a large national retailer said if tariffs are finalized at a sufficiently low level, they’ll absorb what they’ve incurred to date, but if high tariffs stick, they’ll have to raise prices. A steel fabricator for industrial equipment described being reluctant to raise prices on the 10 percent cost increases they’d seen thus far but would have to raise prices should the increases reach 12 to 13 percent. A grocery store chain was reluctant to raise prices and instead might reduce margins, which had recovered in recent years, to maintain their customer base. Some firms explicitly noted a strategy to both raise prices over time and pursue efficiency gains to cut costs and completely restore margins within a year or two.
  • Elasticity testing. Firms reported testing across goods whether consumers will accept price increases. A furniture manufacturer said he’s seen competitors pass along just 5 percentage points of the tariffs at a time so it isn’t such a huge shock to customers, though in that sector, “We all end in the same place which is the customer bearing most of it.” A national retailer said most firms are doing a version of stair-stepping tariffs through, e.g., raising prices a small amount once or twice to see if consumer demand holds, and if so, trying again two months later. This retailer said prices were going up very marginally in early summer, would increase more in July and August, and would be up by 3 to 5 percent by the end of Q4 and into 2026. Another national retailer said they would start testing the extent to which demand falls with price increases, e.g., when the first items that were subject to tariffs—in this case back to school items—hit shelves in late July.
  • Blind margin. Some firms reported attempting to pass through cost in less noticeable ways. While any price increase to consumers will be captured in measures of aggregate inflation, the fact that price increases may occur on non-tariffed goods might make it difficult to directly relate price increases to tariffs. An outdoor goods retailer said, “Unless it’s a branded item where everyone knows the price, if something goes for $18, it can also go for $19.” A national retailer plans to print new shelf labels with updated pricing, which will be less noticeable for consumers compared to multiple new price stickers layered on top. This takes time (akin to a textbook “menu cost” in economics), so it will not be reflected in prices until July and August. A grocery store said their goal was to increase average prices across the store but focus on less visible prices.
  • Selling out of preexisting inventory: Many firms noted they still have production inventory from before tariffs were announced, so they do not need to raise prices as long as they still sell these lower cost goods. A national retailer noted they have at least 25 weeks of inventory on hand for most imported products. A firm that produces grocery items said they will decide how much to raise prices as they get closer to selling tariff-affected products. Similarly, retailers order seasonal items quarters in advance. Many were receiving items for fall and winter when the new tariffs were going into effect in the spring. They paid the tariff then, but we won’t see the price increase until those items hit the shelves in the fall or winter. One retailer speculated that seasonal décor items will look the most like a one-time increase.
  • Pre-established prices. Many firms face infrequent pricing due to factors like annual contracts or pre-sales. For example, a dealer of farm equipment gets half its sales through incentivized pre-sales to lock in demand and smooth around crop cycles. They noted that while it would be difficult to retroactively ask those customers to pay for part of the tariff, they will pass tariffs directly through on spare parts. A steel fabricator for industrial equipment has a contract for steel through Q3, so they haven’t been impacted yet by price increases. However, they will face new costs once that contract expires.

In general, compared to small firms, large firms have more ability to negotiate with vendors, temporarily absorb costs, burn cash, wait for strategic opportunity, and test things out. This matters because large firms often lead pricing behavior among firms, so these strategic choices may influence the response of inflation to tariffs more generally. Even within firm size, one often hears that negotiations on price vary considerably by relationship and item.

Conclusion

A key question surrounding tariffs is whether any effects on inflation will resemble a short-lived price increase—as in the simplest textbook model of tariffs—or a more sustained increase to inflation that may warrant tighter Fed monetary policy. When asked in May what will determine the answer, Fed Chair Jerome Powell cited three factors [archived PDF]: 1) the size of the tariff effects; 2) how long it takes to work their way through to prices; and 3) whether inflation expectations remain anchored. The insights shared above suggest the process from proposed tariffs to the prices set by firms is far from instantaneous or clear-cut, particularly when tariff policy is changing.

Sensing from businesses suggests that the impact of tariffs on their price-setting [archived PDF] has been lagged, but it is starting to play out. Nonetheless, it remains highly uncertain how tariffs will impact consumer inflation. The discussion above makes clear that firms are nimble and innovative in the face of challenge, and they are concerned about losing customers in the current environment, particularly consumer-facing firms. We will continue to learn from our business contacts and share their insights.

Views expressed are those of the author(s) and do not necessarily reflect those of the Federal Reserve Bank of Richmond or the Federal Reserve System.

Economics-Watching: Tracking Business Sentiment in the Western United States

[from the Federal Reserve Bank of San Francisco, Economic Letters, 11 August, 2025]

by Hamza Abdelrahman, Luiz Edgard Oliveira and Aditi Poduri

Information the San Francisco Fed collects from businesses and community sources for the Beige Book provides timely insights into economic activity at both the national and regional levels. Two new indexes based on Beige Book questionnaire responses track business sentiment across the western United States. The indexes track data on economic activity and inflation, serving as early indicators of official data releases and helping improve near-term forecasting accuracy. The latest index readings suggest weakening economic growth and intensifying inflationary pressures over the coming months.

The San Francisco Fed serves the 12th District—the largest in the Federal Reserve System, representing nine western states, two territories, and a commonwealth. To better understand and analyze the regional economy, we collect information from a variety of business and community sources to create the San Francisco Fed’s report for the Beige Book. This is compiled with reports from other Districts and published by the Federal Reserve Board of Governors eight times a year. 

Views about the economy from businesses and communities play an important role in shaping economic outcomes. For example, expectations for future inflation can help spur or slow current consumer spending and business investment. Furthermore, economic forecasters rely on models that incorporate both more traditional “hard” quantitative data and “soft” qualitative information on sentiment. Adding these soft measures has been shown to improve the accuracy of economic forecasts (see Shapiro, Moritz, and Wilson 2022 and their cited literature). Among the many sentiment measures available, two popular approaches rely on survey data, as in the University of Michigan’s Surveys of Consumers, or on textual analysis, as in the SF Fed’s Daily News Sentiment Index.

This Economic Letter examines the economic information collected through the SF Fed’s Beige Book questionnaire over the past 10-plus years. We analyze this information by constructing sentiment indexes from the qualitative data and comparing them with quantitative measures of national and regional economic activity and inflation. We introduce two indexes—the SF Fed Business Sentiment Index and the SF Fed Inflation Gauge Index—which track our contacts’ views and expectations for economic growth and inflation, respectively. We find that these new indexes serve as reliable early indicators of official data releases and help improve near-term forecast accuracy. The SF Fed Business Sentiment Index has generally exhibited patterns similar to other recent business and household sentiment indexes, and the SF Fed Inflation Gauge Index has shown a strong uptick in expected inflation. To regularly monitor changes in these two indexes, the San Francisco Fed has launched a new Twelfth District Business Sentiment data page.

Constructing regional sentiment indexes

The San Francisco Fed sends out a Beige Book questionnaire to business and community contacts across the District eight times a year to gather regional information. In addition to answering questions regarding their organizations, respondents share their views on regional and national topics, including economic activity and inflationary pressures.

In two questions, respondents indicate whether they see national output growth and inflation rates increasing, decreasing, or staying stable over the coming year using a standard five-tiered scale. We use these responses since 2014 to formulate two business sentiment indexes, one on economic activity and another on inflation. We assign standard weights to the five-tiered qualitative scale that are symmetrical around zero. For example, we ask if activity is expected to “decrease significantly” = –2, “decrease” = –1, “remain unchanged” = 0, “increase” = 1, or “increase significantly” = 2. We add up the weighted shares of responses for each tier within each index. We then normalize each resulting series by its own average and standard deviation for ease of comparison with traditional economic indicators.

Tracking business sentiment

Figure 1 shows how the SF Fed Business Sentiment Index (blue line), compiled from responses to the question on national economic activity, compares with data on changes in national GDP (green line). We measure national output as the four-quarter change in inflation-adjusted, or real, GDP, normalized by its average and standard deviation so that it is centered around zero and, hence, more directly comparable to the SF Fed Business Sentiment Index. The vertical axis shows how many standard deviations away each observation is from its respective measure’s average from 2014 to mid-2025.

Figure 1
Economic growth versus business sentiment

Notes: Indicators normalized by their respective averages and standard deviations based on data from 2014 to present. Gray bar indicates NBER recession dates. Correlation coefficient is calculated between quarterly versions of both indicators.
Source: Bureau of Economic Analysis, FRBSF Beige Book questionnaire responses, and authors’ calculations.

The SF Fed Business Sentiment Index generally tracks the movements in national GDP over the past decade; a correlation coefficient of +0.63 on a scale of –1 to 1 indicates a moderately strong positive relationship between the two measures. A relatively recent exception started in 2022, when our index began showing a considerable decline relative to the national GDP measure. Respondents across the District were downbeat about economic growth and reported expectations of a sharp decline in consumer spending and overall household financial health following the depletion of pandemic-era savings (Abdelrahman and Oliveira 2023). A similar decline appeared in other measures of business and household sentiment. Nevertheless, overall economic growth continued at a solid pace. This decoupling between sentiment and hard data that began in 2022 was dubbed a “vibecession” (Daly 2024, Scanlon 2022).

Another possible reason for the divergence between national real GDP and our Business Sentiment Index is the influence of the regional economy. Although respondents are asked about their views of national GDP, their responses may be affected by regional outcomes. Thus, our index may also reflect a regional perspective from our business and community contacts.

Figure 2 supports this rationale, showing the SF Fed Business Sentiment Index alongside a measure of regional output growth (gold line). We find that the measures closely track one another, including for 2022 and 2023, with a correlation coefficient of +0.74. We define District real GDP growth as the year-over-year percent change in the total output of the District’s nine states as reported by the Bureau of Economic Analysis (BEA). We normalize the series as described before.

Figure 2
Regional economic growth and business sentiment

Notes: Indicators normalized by their respective averages and standard deviations based on data from 2014 to present. Gray bar indicates NBER recession dates. Correlation coefficient is calculated between quarterly versions of both indicators.
Source: Bureau of Economic Analysis, FRBSF Beige Book questionnaire responses, and authors’ calculations.

Our findings indicate that the SF Fed Business Sentiment Index can serve as an accurate early indicator for national and regional output growth. Since the regional Beige Book questionnaire is collected twice each quarter, it provides particularly timely insights into economic activity during the current quarter. By contrast, the first GDP data release for any given quarter usually arrives a full month after that quarter has ended, and initial data releases for state-level output growth arrive with even more delay.

Over the first half of this year, the SF Fed Business Sentiment Index turned negative, with contacts citing elevated uncertainty about trade policy and downbeat expectations for the labor market. This notable decline is also seen in other measures of household and business sentiment, including national measures, such as the University of Michigan’s Surveys of Consumers, and regional measures, such as the Cleveland Fed’s Survey of Regional Conditions and Expectations and the Dallas Fed’s Texas Business Outlook Surveys.

Gauging business views on inflationary pressures

Our Beige Book questionnaire responses also provide insights into how business and community contacts in the District see national inflation evolving. Figure 3 compares the SF Fed Inflation Gauge Index (blue line) with monthly changes in the year-over-year headline personal consumption expenditures (PCE) inflation rate published by the BEA (green line). We normalize the inflation series and index as discussed earlier.

Figure 3
SF Fed Inflation Gauge Index versus realized inflation

Notes: Green line is the percentage point change in year-over-year headline PCE inflation shown as a 6-month moving average. Indicators normalized by their respective averages and standard deviations based on data from 2014 to present. Gray bar indicates NBER recession dates. Correlation coefficient is calculated between quarterly versions of both indicators.
Source: Bureau of Economic Analysis, FRBSF Beige Book questionnaire responses, and authors’ calculations.

Similar to our business sentiment index, the inflation gauge index is an early indicator for official inflation data releases. The index generally tracks changes in headline PCE inflation over the past decade, with a correlation coefficient of +0.65.

The most recent index results suggest a strong uptick in expected inflation among SF Fed business contacts, with several responses citing trade policy adjustments and inflation being persistently above the Federal Reserve’s 2% target. The recent peak resembles the one in 2018, which followed heightened trade tensions with China. The surge tracks other business and household-based measures of short-term inflation expectations, such as the Atlanta Fed’s Business Inflation Expectations and the New York Fed’s Survey of Consumer Expectations.

Making better projections

Beyond tracking data on national and regional economic conditions, we consider whether our two indexes can help improve one-year-ahead projections of output growth and overall inflation. We run linear regressions on a 2014–2022 data sample and estimate out-of-sample projections for the period starting in the first quarter of 2023. We run this analysis for the three economic measures—national GDP, regional GDP, and inflation—once with our index included on the right-hand side of the regression equation and once without the index. For this analysis, we use versions of the SF Fed Business Sentiment Index and the SF Fed Inflation Gauge Index that have been aggregated quarterly.

Figure 4 compares the out-of-sample projection accuracy of the two iterations. Across all economic measures, incorporating the SF Fed Business Sentiment Index or the SF Fed Inflation Gauge Index in the regression noticeably reduced the forecast errors for the out-of-sample period. This general result appears to hold when we project output growth and inflation one quarter ahead, in line with other studies that incorporate soft data from the Beige Book in short-term projections (Balke and Petersen 2002). The results are also consistent when using a local projections method from Jordà (2005) for one-year-ahead projections of output growth and shorter-term projections of inflation. This further supports the usefulness of our qualitative measures as early indicators of the future economic landscape over the short term.

Figure 4
Forecast errors with and without SF Fed sentiment indexes

Notes: Root mean-squared errors of out-of-sample projections from 2023:Q1 to 2025:Q2 including and excluding the SF Fed Business Sentiment Index (for GDP) and SF Fed Inflation Gauge Index (for inflation).
Source: Bureau of Economic Analysis, FRBSF Beige Book questionnaire responses, and authors’ calculations.

Conclusion

Information collected from businesses and communities through the San Francisco Fed’s regional Beige Book questionnaire can provide valuable insights into the national and regional economies. Sentiment indexes described in this Letter use responses from Twelfth District Beige Book contacts to generally track economic activity and inflation. Our two indexes serve as reliable early indicators of official data, which could help improve near-term forecast accuracy. The SF Fed Business Sentiment Index remained negative for much of 2022 and 2023, possibly reflecting more subdued growth within the District relative to the United States. Meanwhile, the SF Fed Inflation Gauge Index spiked in recent months following adjustments to trade policy.

References

Abdelrahman, Hamza, and Luiz E. Oliveira. 2023. “The Rise and Fall of Pandemic Excess Savings.” FRBSF Economic Letter 2023-11 (May 8).

Balke, Nathan S., and D’Ann Petersen. 2002. “How Well Does the Beige Book Reflect Economic Activity? Evaluating Qualitative Information Quantitatively.” Journal of Money, Credit and Banking 34 (1), pp. 114–136.

Daly, Mary C. 2024. “Fireside Chat with Mary C. Daly at the San Diego County Economic Roundtable.” January 19.

Jordà, Òscar. 2005. “Estimation and Inference of Impulse Responses by Local Projections.” American Economic Review 95(1), pp. 161–182.

Scanlon, Kyla. 2022. “The Vibecession: The Self-Fulfilling Prophecy.” Kyla Substack (June 30).

Shapiro, Adam Hale, Moritz Sudhof, and Daniel Wilson. 2022. “Measuring News Sentiment.” Journal of Econometrics 228(2), pp. 221–243.

Economics-Watching: Second-Quarter GDP Growth Estimate Unchanged

[from the Federal Reserve Bank of Atlanta]

The growth rate of real gross domestic product (GDP) is a key indicator of economic activity, but the official estimate is released with a delay. The Federal Reserve Bank of Atlanta’s GDPNow forecasting model provides a “nowcast” of the official estimate prior to its release by estimating GDP growth using a methodology similar to the one used by the U.S. Bureau of Economic Analysis.

GDPNow is not an official forecast of the Atlanta Fed. Rather, it is best viewed as a running estimate of real GDP growth based on available economic data for the current measured quarter. There are no subjective adjustments made to GDPNow—the estimate is based solely on the mathematical results of the model.

Recent forecasts for the GDPNow model are available here [archived PDF]. More extensive numerical details—including underlying source data, forecasts, and model parameters—are available as a separate spreadsheet [archived XLSX]. You can also view an archive of recent commentaries from GDPNow estimates.

Please note that the Atlanta Fed no longer supports the GDPNow app. Download the EconomyNow app to get the latest GDP nowcast and more economic data.

Latest estimate: 2.4 percent — July 25, 2025

The GDPNow model estimate for real GDP growth (seasonally adjusted annual rate) in the second quarter of 2025 is 2.4 percent on July 25, unchanged from July 18 after rounding. The forecasts of the major GDP subcomponents were all unchanged or little changed from their July 18 values after this week’s releases from the U.S. Census Bureau and the National Association of Realtors.

The growth rate of real gross domestic product (GDP) measured by the U.S. Bureau of Economic Analysis (BEA) is a key metric of the pace of economic activity. It is one of the four variables included in the economic projections of Federal Reserve Board members and Bank presidents for every other Federal Open Market Committee (FOMC) meeting. As with many economic statistics, GDP estimates are released with a lag whose timing can be important for policymakers. In preparation for FOMC meetings, policymakers have the Fed Board staff projection of this “advance” estimate at their disposal. These projections—available through 2008 at the Philadelphia Fed’s Real Time Data Center—have generally been more accurate than forecasts from simple statistical models. As stated by economists Jon Faust and Jonathan H. Wright in a 2009 paper, “by mirroring key elements of the data construction machinery of the Bureau of Economic Analysis, the Fed staff forms a relatively precise estimate of what BEA will announce for the previous quarter’s GDP even before it is announced.”

The Atlanta Fed GDPNow model also mimics the methods used by the BEA to estimate real GDP growth. The GDPNow forecast is constructed by aggregating statistical model forecasts of 13 subcomponents that comprise GDP. Other private forecasters use similar approaches to “nowcast” GDP growth. However, these forecasts are not updated more than once a month or quarter, are not publicly available, or do not have forecasts of the subcomponents of GDP that add “color” to the top-line number. The Atlanta Fed GDPNow model fills these three voids.

The BEA’s advance estimates of the subcomponents of GDP use publicly released data from the U.S. Census Bureau, U.S. Bureau of Labor Statistics, and other sources. Much of this data is displayed in the BEA’s Key Source Data and Assumptions table that accompanies the “advance” GDP estimate. GDPNow relates these source data to their corresponding GDP subcomponents using a “bridge equation” approach similar to the one described in a Minneapolis Fed [archived PDF] study by Preston J. Miller and Daniel M. Chin. Whenever the monthly source data is not available, the missing values are forecasted using econometric techniques similar to those described in papers by James H. Stock and Mark W. Watson and Domenico Giannone, Lucrezia Reichlin, and David Small. A detailed description of the data sources and methods used in the GDPNow model is provided in an accompanying Atlanta Fed working paper [archived PDF].

As more monthly source data becomes available, the GDPNow forecast for a particular quarter evolves and generally becomes more accurate. That said, the forecasting error can still be substantial just prior to the “advance” GDP estimate release. It is important to emphasize that the Atlanta Fed GDPNow forecast is a model projection not subject to judgmental adjustments. It is not an official forecast of the Federal Reserve Bank of Atlanta, its president, the Federal Reserve System, or the FOMC.

Economics-Watching: Fed Transparency and Policy Expectation Errors: A Text Analysis Approach

[from the Federal Reserve Bank of New York, written by Eric Fischer, Rebecca McCaughrin, Saketh Prazad, and Mark Vandergon]

This paper seeks to estimate the extent to which market-implied policy expectations could be improved with further information disclosure from the FOMC. Using text analysis methods based on large language models, we show that if FOMC meeting materials with five-year lagged release dates—like meeting transcripts and Tealbooks—were accessible to the public in real-time, market policy expectations could substantially improve forecasting accuracy. Most of this improvement occurs during easing cycles. For instance, at the six-month forecasting horizon, the market could have predicted as much as 125 basis points of additional easing during the 2001 and 2008 recessions, equivalent to a 40-50 percent reduction in mean squared error. This potential forecasting improvement appears to be related to incomplete information about the Fed’s reaction function, particularly with respect to financial stability concerns in 2008. In contrast, having enhanced access to meeting materials would not have improved the market’s policy rate forecasting during tightening cycles.

Read the full article [archived PDF].

Economics-Watching: “Doing Nothing” Is Still Doing a Lot

[from the Federal Reserve Bank of Philadelphia, speech by Patrick T. Harker President and Chief Executive Officer at the National Association of Corporate Directors Webinar, Philadelphia, PA (Virtual)]

Good afternoon, everyone.

I appreciate that you’re all giving up part of the end of your workday for us to be together, if only virtually.

My thanks to my good friend, Rick Mroz, for that welcome and introduction.

I do believe we’re going to have a productive session. But just so you all know, as much as I enjoy speaking and providing my outlook, I enjoy a good conversation even more.

So, first, let’s take a few minutes so I can give you my perspective on where we are headed, and then I will be more than happy to take questions and hear what’s on your minds.

But before we get into any of that, I must begin with the standard Fed disclaimer: The views I express today are my own and do not necessarily reflect those of anyone else on the Federal Open Market Committee (FOMC) or in the Federal Reserve System.

Put simply, this is one of those times where the operative words are, “Pat said,” not “the Fed said.”

Now, to begin, I’m going to first address the two topics that I get asked about most often: interest rates and inflation. And I would guess they are the topics front and center in many of your minds as well.

After the FOMC’s last policy rate hike in July, I went on record with my view that, if economic and financial conditions evolved roughly as I expected they would, we could hold rates where they are. And I am pleased that, so far, economic and financial conditions are evolving as I expected, if not perhaps even a tad better.

Let’s look at the current dynamics. There is a steady, if slow, disinflation under way. Labor markets are coming into better balance. And, all the while, economic activity has remained resilient.

Given this, I remain today where I found myself after July’s meeting: Absent a stark turnabout in the data and in what I hear from contacts, I believe that we are at the point where we can hold rates where they are.

In barely more than a year, we increased the policy rate by more than 5 percentage points and to its highest level in more than two decades — 11 rate hikes in a span of 12 meetings prior to September. We not only did a lot, but we did it very fast.

We also turned around our balance sheet policy — and we will continue to tighten financial conditions by shrinking the balance sheet.

The workings of the economy cannot be rushed, and it will take some time for the full impact of the higher rates to be felt. In fact, I have heard a plea from countless contacts, asking to give them some time to absorb the work we have already done.

I agree with them. I am sure policy rates are restrictive, and, as long they remain so, we will steadily press down on inflation and bring markets into a better balance.

Holding rates steady will let monetary policy do its work. By doing nothing, we are still doing something. And I would argue we are doing quite a lot.

Headline PCE inflation remained elevated in August at 3.5 percent year over year, but it is down 3 percentage points from this time last year. About half of that drop is due to the volatile components of energy and food that, while basic necessities, they are typically excluded by economists in the so-called core inflation rate to give a more accurate assessment of the pace of disinflation and its likely path forward.

Well, core PCE inflation has also shown clear signs of progress, and the August monthly reading was its smallest month-over-month increase since 2020.

So, yes, a steady disinflation is under way, and I expect it to continue. My projection is that inflation will drop below 3 percent in 2024 and level out at our 2 percent target thereafter.

However, there can be challenges in assessing the trends in disinflation. For example, September’s CPI report came out modestly on the upside, driven by energy and housing.

Let me be clear about two things. First, we will not tolerate a reacceleration in prices. But second, I do not want to overreact to the normal month-to-month variability of prices. And for all the fancy techniques, the best way to separate a signal from noise remains to average data over several months. Of course, to do so, you need several months of data to start with, which, in turn, demands that, yes, we remain data-dependent but patient and cautious with the data.

Turning to the jobs picture, I do anticipate national unemployment to end the year at about 4 percent — just slightly above where we are now — and to increase slowly over the next year to peak at around 4.5 percent before heading back toward 4 percent in 2025. That is a rate in line with what economists call the natural rate of unemployment, or the theoretical level in which labor market conditions support stable inflation at 2 percent.

Now, that said, as you know, there are many factors that play into the calculation of the unemployment rate. For instance, we’ve seen recent months where, even as the economy added more jobs, the unemployment rate increased because more workers moved off the sidelines and back into the labor force. There are many other dynamics at play, too, such as technological changes or public policy issues, like child care or immigration, which directly impact employment.

And beyond the hard data, I also have to balance the soft data. For example, in my discussions with employers throughout the Third District, I hear that given how hard they’ve worked to find the workers they currently have, they are doing all they can to hold onto them.

So, to sum up the labor picture, let me say, simply, I do not expect mass layoffs.

I do expect GDP gains to continue through the end of 2023, before pulling back slightly in 2024. But even as I foresee the rate of GDP growth moderating, I do not see it contracting. And, again, to put it simply, I do not anticipate a recession.

Look, this economy has been nothing if not unpredictable. It has proven itself unwilling to stick to traditional modeling and seems determined to not only bend some rules in one place, but to make up its own in another. However, as frustratingly unpredictable as it has been, it continues to move along.

And this has led me to the following thought: What has fundamentally changed in the economy from, say, 2018 or 2019? In 2018, inflation averaged 2 percent almost to the decimal point and was actually below target in 2019. Unemployment averaged below 4 percent for both years and was as low as 3.5 percent — both nationwide and in our respective states — while policy rates peaked below 2.5 percent.

Now, I’m not saying we’re going to be able to exactly replicate the prepandemic economy, but it is hard to find fundamental differences. Surely, I cannot and will not minimize the immense impacts of the pandemic on our lives and our families, nor the fact that for so many, the new normal still does not feel normal. From the cold lens of economics, I do not see underlying fundamental changes. I could also be wrong, and, trust me, that would not be the first time this economy has made me rethink some of the classic models. We just won’t know for sure until we have more data to look at over time.

And then, of course, there are the economic uncertainties — both national and global — against which we also must contend. The ongoing auto worker strike, among other labor actions. The restart of student loan payments. The potential of a government shutdown. Fast-changing events in response to the tragic attacks against Israel. Russia’s ongoing war against Ukraine. Each and every one deserves a close watch.

These are the broad economic signals we are picking up at the Philadelphia Fed, but I would note that the regional ones we follow are also pointing us forward.

First, while in the Philadelphia Fed’s most recent business outlook surveys, which survey manufacturing and nonmanufacturing firms in the Third District, month-over-month activity declined, the six-month outlooks for each remain optimistic for growth.

And we also publish a monthly summary metric of economic activity, the State Coincident Indexes. In New Jersey, the index is up slightly year over year through August, which shows generally positive conditions. However, the three-month number from June through August was down, and while both payroll employment and average hours worked in manufacturing increased during that time, so did the unemployment rate — though a good part of that increase can be explained as more residents moved back into the labor force.

And for those of you joining us from the western side of the Delaware River, Pennsylvania’s coincident index is up more than 4 percent year over year through August and 1.7 percent since June. Payroll employment was up, and the unemployment rate was down; however, the number of average hours worked in manufacturing decreased.

There are also promising signs in both states in terms of business formation. The number of applications, specifically, for high-propensity businesses — those expected to turn into firms with payroll — are remaining elevated compared with pre-pandemic levels. Again, a promising sign.

So, it is against this full backdrop that I have concluded that now is the time at which the policy rate can remain steady. But I can hear you ask: “How long will rates need to stay high.” Well, I simply cannot say at this moment. My forecasts are based on what we know as of late 2023. As time goes by, as adjustments are completed, and as we have more data and insights on the underlying trends, I may need to adjust my forecasts, and with them my time frames.

I can tell you three things about my views on future policy. First, I expect rates will need to stay high for a while.

Second, the data and what I hear from contacts and outreach will signal to me when the time comes to adjust policy either way. I really do not expect it, but if inflation were to rebound, I know I would not hesitate to support further rate increases as our objective to return inflation to target is, simply, not negotiable.

Third, I believe that a resolute, but patient, monetary policy stance will allow us to achieve the soft landing that we all wish for our economy.

Before I conclude and turn things over to Rick to kick off our Q&A, I do want to spend a moment on a topic that he and I recently discussed, and it’s something about which I know there is generally great interest: fintech. In fact, I understand there is discussion about NACD hosting a conference on fintech.

Well, last month, we at the Philadelphia Fed hosted our Seventh Annual Fintech Conference, which brought business and thought leaders together at the Bank for two days of real in-depth discussions. And I am extraordinarily proud of the fact that the Philadelphia Fed’s conference has emerged as one of the premier conferences on fintech, anywhere. Not that it’s a competition.

I had the pleasure of opening this year’s conference, which always puts a focus on shifts in the fintech landscape. Much of this year’s conference centered around developments in digital currencies and crypto — and, believe me, some of the discussions were a little, shall we say, “spirited.” However, my overarching point to attendees was the following: Regardless of one’s views, whether in favor of or against such currencies, our reality requires us to move from thinking in terms of “what if” to thinking about “what next.”

In many ways, we’re beyond the stage of thinking about crypto and digital currency and into the stage of having them as reality — just as AI has moved from being the stuff of science fiction to the stuff of everyday life. What is needed now is critical thinking about what is next. And we at the Federal Reserve, both here in Philadelphia and System-wide, are focused on being part of this discussion.

We are also focused on providing not just thought leadership but actionable leadership. For example, the Fed rolled out our new FedNow instant payment service platform in July. With FedNow, we will have a more nimble and responsive banking system.

To be sure, FedNow is not the first instant payment system — other systems, whether operated by individual banks or through third parties, have been operational for some time. But by allowing banks to interact with each other quickly and efficiently to ensure one customer’s payment becomes another’s deposit, we are fulfilling our role in providing a fair and equitable payment system.

Another area where the Fed is assuming a mantle of leadership is in quantum computing, or QC, which has the potential to revolutionize security and problem-solving methodologies throughout the banking and financial services industry. But that upside also comes with a real downside risk, should other not-so-friendly actors co-opt QC for their own purposes.

Right now, individual institutions and other central banks globally are expanding their own research in QC. But just as these institutions look to the Fed for economic leadership, so, too, are they looking to us for technological leadership. So, I am especially proud that this System-wide effort is being led from right here at the Philadelphia Fed.

I could go on and talk about fintech for much longer. After all, I’m actually an engineer more than I am an economist. But I know that Rick is interested in starting our conversation, and I am sure that many of you are ready to participate.

But one last thought on fintech — my answers today aren’t going to be generated by ChatGPT.

On that note, Rick, thanks for allowing me the time to set up our discussion, and let’s start with the Q&A.

[archived PDF of the above speech]

FRBSF Economic Letter: Can Monetary Policy Tame Rent Inflation?

[from the Federal Reserve Bank of San Francisco Economic Letter]

by Zheng Liu and Mollie Pepper

Rent inflation has surged since early 2021. Because the cost of housing is an important component of total U.S. consumer spending, high rent inflation has contributed to elevated levels of overall inflation. Evidence suggests that, as monetary policy tightening cools housing markets, it can also reduce rent inflation, although this tends to adjust relatively slowly. A policy tightening equivalent to a 1 percentage point increase in the federal funds rate could reduce rent inflation as much as 3.2 percentage points over 2½ years.

“We’ve had a time of red-hot housing market all over the country… Shelter inflation is going to remain high for some time. We’re looking for it to come down, but it’s not exactly clear when that will happen. Hope for the best, plan for the worst.”

Federal Reserve Chair Jerome Powell (2022)

The rapid run-up of shelter costs—both house prices and rents—during the recovery from the pandemic has raised questions about how inflation pressures might affect housing affordability. Since March 2022, the Federal Reserve has rapidly lifted its federal funds rate target from near zero to over 4%, and policymakers have signaled that they are open to keeping the monetary policy stance sufficiently restrictive to return inflation to the longer-run goal of 2% on average. The tightened financial conditions following those policy changes, especially the surge in mortgage interest rates, have helped cool house price growth. However, rent inflation remains elevated.

This Economic Letter examines the effectiveness of monetary policy tightening for reducing rent inflation. We estimate that, during the period from 1988 to 2019, a policy tightening equivalent to a 1 percentage point increase in the federal funds rate can reduce rent inflation—measured by 12-month percentage changes in the personal consumption expenditures (PCE) housing price index—by about 3.2 percentage points, but the full impact takes about 2½ years to materialize. Based on housing costs’ share in total PCE, this translates to a reduction in headline PCE inflation of about 0.5 percentage point over the same time horizon.

Rising housing costs

Following the COVID-19 recession, house prices and rents both surged in the United States. For example, the 12-month growth rate of Standard & Poor’s CoreLogic Case-Shiller Home Price Index accelerated from about 10% in December 2020 to over 20% in March 2022. After the Federal Reserve started raising the target for the federal funds rate in March, house price growth has slowed significantly, to about 9% in October 2022.

Rent inflation also accelerated during the pandemic period. Figure 1 shows that rent inflation—measured using 12-month changes in the PCE housing price index and including rents for tenant-occupied housing and imputed rents for owner-occupied housing—rose from a low point of about 2% in early 2021 to 7.7% by December 2022, the highest level since 1986. During the same period, rent inflation measured by 12-month changes in the shelter component of the consumer price index (CPI) experienced a similar increase. Thus, following the tightening of monetary policy, house price growth has slowed but rent inflation continues to rise.

Figure 1: PCE and CPI measures of rent inflation
Source: Bureau of Economic Analysis, Bureau of Labor Statistics, and Haver Analytics.
Note: Twelve-month percentage changes. Gray shading indicates NBER recession dates.

Economic theory suggests that some common forces such as changes in housing demand can drive both rents and house prices. For example, the expansion of remote work since the COVID-19 pandemic has increased demand for housing, raising both house prices and rents (Kmetz, Mondragon, and Wieland 2022). To the extent that the stream of current and future rents reflects the fundamental value of a house, house prices can be a leading indicator of future rent inflation (Lansing, Oliveira, and Shapiro 2022). Thus, monetary policy can affect both house prices and rents by cooling housing demand.

Housing demand responds to changes in financial conditions, such as increases in mortgage interest rates. However, theory suggests that house prices are more sensitive than rental prices to changes in financial conditions, because home purchases typically require longer-term mortgage financing. In addition, unlike rents, house prices can be partly driven by investor sentiments or beliefs, which explains the observed larger swings in house prices than in rents over business cycles (Dong et al. 2022). Long-term rental contracts can also contribute to slow adjustments in rent inflation.

Rent inflation is an important contributor to overall inflation because housing costs are an important component of total consumption expenditures. On average, housing expenditures represent about 15% of total PCE and 25% of the services component of PCE. In CPI, shelter costs represent an even larger share, accounting for about 30% of total consumption of all urban consumers and about 40% of core consumption expenditures excluding volatile food and energy components.

The contribution of rent inflation to overall PCE inflation has increased since early 2021. As Figure 2 shows, in the first quarter of 2021, rent inflation accounted for about 22% of the four-quarter change in the PCE services price index, excluding energy: 0.5 of the 2.3 percentage points increase in service prices was attributable to rent inflation. By the third quarter of 2022, the contribution of rent inflation had climbed to about one-third, or 1.5 of the 4.7 percentage point increase in service prices.

Figure 2: Rising contribution of rent inflation to services inflation
Source: Bureau of Economic Analysis, Haver Analytics, and authors’ calculations.
Note: Four-quarter changes in PCE services price index excluding energy.

Measuring policy effects

Given the rising contribution of rent inflation to overall inflation, it is important to assess the quantitative effects of monetary policy tightening on rent inflation.

For our analysis, we use a measure of monetary policy surprises constructed by Bauer and Swanson (2022). Their measure focuses on high-frequency changes in financial market indicators within a short period surrounding the Federal Open Market Committee (FOMC) policy announcements. If the public fully anticipates a policy change, then the financial market would not react to new policy announcements. However, if the market does react to an announcement, then the policy change must contain a surprise element. Thus, changes in financial market indicators, such as the price of Eurodollar futures, in a narrow window around an FOMC announcement can capture policy surprises. In practice, however, the data constructed this way are not complete surprises because they can be predicted by some macro and financial variables shortly before FOMC announcements. We follow the approach of Bauer and Swanson (2022) to purge the influences of those macro and financial variables from the measure of policy surprises. We use the resulting quarterly time series to measure monetary policy shocks, with a sample period from 1988 to 2019.

We then use a local projections model—a statistical tool proposed by Jordà (2005)—to project how rent inflation responds over time to a tightening of monetary policy equivalent to a 1 percentage point unanticipated increase in the federal funds rate in a given quarter. The model takes into account how monetary policy shocks interact with other macroeconomic variables, including lags of rent inflation, real GDP growth, and core PCE inflation.

In the final step, we compute the responses of rent inflation relative to its preshock level over a period up to 20 quarters after the initial increase in the federal funds rate.

Gradual impact of policy tightening on rent inflation

Figure 3 shows the response of rent inflation during the first 20 quarters after an unanticipated tightening of monetary policy (solid blue line). The shaded area shows the confidence band, indicating the statistical uncertainty in estimating the responses. Under the assumption that the model is correct, the shaded area contains the actual value of the rent inflation responses to the monetary policy shock roughly two-thirds of the time. The policy shock is normalized such that it is equivalent to a 1 percentage point unanticipated increase in the federal funds rate.

Figure 3: Response of rent inflation to monetary policy tightening
Source: Bureau of Economic Analysis, Bauer and Swanson (2022), and authors’ calculations.
Note: Response of rent inflation to a monetary policy shock equivalent to a 1 percentage point surprise increase in the federal funds rate. Shaded region shows 68% confidence band around the estimate.

The figure shows that monetary policy tightening has significant and gradual effects on rent inflation. On impact, a 1 percentage point increase in the federal funds rate reduces rent inflation about 0.6 percentage point relative to its preshock level. Over time, rent inflation declines gradually, falling about 3.2 percentage points in the 10 quarters following the impact. The slow adjustment in rent inflation partly reflects the stickiness in nominal rents due to long-term rental contracts. Since housing expenditures account for about 15% of total PCE, this estimate translates to a reduction in headline PCE inflation of about 0.5 percentage point, stemming from the decline in rent inflation over a period of 2½ years.

The rent component of PCE is measured based on average rents, including those locked in long-term rental contracts, which are slow to adjust to changes in economic and financial conditions. Rents on new leases, however, are more flexible. For example, the 12-month growth in Zillow’s observed rent index, which measures changes in asking rents on new leases, has slowed significantly since March 2022 (see Figure 4). Asking rents are typically a leading indicator of future average rents. Thus, the slowdown in asking rent growth could portend lower future rent inflation.

Figure 4: Year-over-year observed rent growth starting to slow
Source: Zillow and Haver Analytics.
Note: Twelve-month percentage changes in Zillow’s observed rent index. Gray shading indicates NBER recession dates.

Conclusion

Rents are an important component of consumer expenditures. Recent surges in rent inflation have led to concerns that overall inflation might stay persistently high despite tightening of monetary policy. We present evidence that monetary policy tightening is effective for reducing rent inflation, although the full impact takes time to materialize. A policy tightening equivalent to a 1 percentage point increase in the federal funds rate can reduce rent inflation up to 3.2 percentage points over the course of 2½ years. This translates to a maximum reduction in headline PCE inflation of about 0.5 percentage point over the same time horizon. Although average rents are slow to respond to policy changes, growth of asking rents on new leases has started to slow following recent monetary policy tightening. Our finding suggests that this tightening will gradually bring rent inflation down over time, thereby helping to reduce overall inflation.

Zheng Liu — Vice President and Director of the Center for Pacific Basin Studies, Economic Research Department, Federal Reserve Bank of San Francisco

Mollie Pepper — Research Associate, Economic Research Department, Federal Reserve Bank of San Francisco

[Archived PDF]