The Atlanta Fed's sticky-price consumer price index (CPI)—a weighted basket of items that change price relatively slowly—increased 5.4 percent (on an annualized basis) in July, following an 8.1 percent increase in June. On a year-over-year basis, the series is up 5.8 percent.

On a core basis (excluding food and energy), the sticky-price index increased 5.2 percent (annualized) in July, and its 12-month percent change was 5.6 percent.

The flexible cut of the CPI—a weighted basket of items that change price relatively frequently—fell by 11.3 percent (annualized) in July and is up 16.3 percent on a year-over-year basis.

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. Our 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. In particular, it does not capture the impact of COVID-19 and social mobility beyond their impact on GDP source data and relevant economic reports that have already been released. It does not anticipate their impact on forthcoming economic reports beyond the standard internal...

Presented by Supervision, Regulation, and Credit

Join us August 16 at 2 p.m. (ET) for the next event in the Atlanta Fed's Supervision, Regulation, and Credit (SRC) Division real estate webinar series. In this series, our residential and commercial real estate experts share their market insights, industry color, and data analytics and tools. This webinar features residential real estate subject matter expert Domonic Purviance, who will cover current conditions and trends in residential real estate and the potential risks that lie ahead as the market confronts rising mortgage rates and declining home ownership affordability.

For questions or to subscribe for HOAM updates, email supervision@atl.frb.org.

Domonic Purviance

As a subject matter expert within the Supervision, Regulation and Credit (SRC) Division at the Federal Reserve Bank of Atlanta, Domonic Purviance is primarily responsible for conducting an ongoing assessment of risks associated...

Take On Payments, a blog sponsored by the Retail Payments Risk Forum of the Federal Reserve Bank of Atlanta, is intended to foster dialogue on emerging risks in retail payment systems and enhance collaborative efforts to improve risk detection and mitigation. We encourage your active participation in Take on Payments and look forward to collaborating with you.

Inflation expectations: Firms' year-ahead inflation expectations were relatively unchanged at 3.1 percent, on average. Current economic environment: Sales levels "compared to normal" decreased to a neutral level. However, profit margins remain unchanged. Year-over-year unit cost growth is relatively unchanged at 3.2 percent, on average. Quarterly question: Firms' long-term (per year, over the next five to 10 years) inflation expectations were relatively unchanged at 3.0 percent, on average. Special question: Firms were asked whether they faced supply chain disruptions and what actions, if any, they took to mitigate them. They were then asked how important these actions were to the firm's continuity. A breakdown of the results can be found in the special question section below.

The myCPI tool captures the uniqueness of the selection of goods that individuals purchase. It is a more individualized measure of price change than the CPI (Consumer Price Index). While the aim of the CPI is to measure the change in prices that the typical consumer pays for a fixed basket of goods, myCPI captures some of the variation that occurs across different demographic characteristics including sex, size of household, age, income, education, and housing status. The result is 144 different market baskets that could yield a closer approximation to your cost of living than one based on the average consumer. Learn more about myCPI.

On July 15, 2021, staff from the Federal Reserve hosted an Ask the Fed webinar on the SCALE method and tool for determining expected credit losses under CECL. The Financial Accounting Standards Board (FASB) and the Conference of State Bank Supervisors (CSBS) also participated in the webinar. A recording of the webinar can be accessed by clicking here.

The SCALE method is a simple, spreadsheet-based method developed by the Federal Reserve to assist smaller community banks in calculating their CECL compliant allowances for credit losses (ACLs) using proxy expected lifetime loss rates. 

The SCALE tool, also developed by the Federal Reserve, is a template that smaller community banks with total assets of less than $1 billion can use if they wish to use the SCALE method. This tool uses publicly available data from Schedule RI-C of the Call Report to derive the initial proxy expected lifetime loss rates. If a bank uses the SCALE tool, bank management...

In partnership with Steven Davis of the University of Chicago Booth School of Business and Nicholas Bloom of Stanford University, the Federal Reserve Bank of Atlanta has created the Atlanta Fed/Chicago Booth/Stanford Survey of Business Uncertainty (SBU). This innovative panel survey measures the one-year-ahead expectations and uncertainties that firms have about their own employment and sales. The sample covers all regions of the U.S. economy, every industry sector except agriculture and government, and a broad range of firm sizes.

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. Our 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. In particular, it does not capture the impact of COVID-19 and social mobility beyond their impact on GDP source data and relevant economic reports that have already been released. It does not anticipate their impact on forthcoming economic reports beyond the standard internal...

Full text 

Abstract: A tighter monetary policy is generally associated with higher real interest rates on deposits and loans, weaker performance of equities and real estate, and slower growth in employment and wages. How does a household’s exposure to monetary policy vary with its age? The size and composition of both household income and asset portfolios exhibit large variation over the lifecycle in Japanese data. We formulate an overlapping-generations model that reproduces these observations and use it to analyze how household responses to monetary policy shocks vary over the lifecycle. Both the signs and the magnitudes of the responses of a household's net worth, disposable income, and consumption depend on its age.

JEL classification: E52, E62, G51, D15

Key words: monetary policy, lifecycle, portfolio choice, nominal government debt

https://doi.org/10.29338/wp2021-20

A recent study by Feiveson et al.  establishes the Federal Open Market Committee's interest in the distributional effects of monetary policy. The size and the composition of household income exhibit large variation over the life cycle, so it is likely that household exposures to monetary policy also depend on age. This post summarizes new research by Daisuke Ikeda and me that uses a life cycle model to measure the age profile of household exposures to monetary policy. In the model, a higher nominal interest rate increases the wealth and consumption of households between the ages of 60 and 80, but it reduces the wealth and consumption of younger working-age households and the oldest retirees. The former group also has the highest net worth, and it follows that net worth and consumption inequality increase in the model.

Our new research took as its jumping-off point the premise that a household's age affects its economic opportunities. Both the size and the...