Brent Meyer

We examine businesses' price-setting practices via open-ended interviews and in a quantitative survey module with business contacts from the Federal Reserve Banks of Atlanta, Cleveland, and New York in December 2022 and January 2023. Businesses indicated that their prices were strongly influenced by demand, a desire to maintain steady profit margins, and wages and labor costs. Survey respondents expected reduced growth in costs and prices of about 5 percent on average over the next year. Backward-looking, forward-looking, and hypothetical scenarios reveal average cost-price passthrough of around 60 percent, with meaningful heterogeneity across firms.

In this paper we investigate the forecasting performance of the median consumer price index (CPI) in a variety of Bayesian vector autoregressions (BVARs) that are often used for monetary policy. Until now, the use of trimmed-mean price statistics in forecasting inflation has often been relegated to simple univariate or "Phillips-curve" approaches, thus limiting their usefulness in applications that require consistent forecasts of multiple macro variables. We find that inclusion of an extreme trimmed-mean measure—the median CPI—improves the forecasts of both core and headline inflation (CPI and PCE) across our set of monthly and quarterly BVARs. While the inflation forecasting improvements are perhaps not surprising given the current literature on core inflation statistics, we also find that inclusion of the median CPI improves the forecasting accuracy of the central bank's primary instrument for monetary policy—the federal funds rate. We conclude with a few illustrative exercises that highlight the usefulness of using the median CPI.

This paper evaluates the ability of autoregressive models, professional forecasters, and models that leverage unemployment flows to forecast the unemployment rate.

This paper reinvestigates the performance of trimmed-mean inflation measures some 20 years since their inception, asking whether there is a particular trimmed-mean measure that dominates the median CPI.

In this paper we investigate the forecasting performance of the median CPI in a variety of Bayesian VARs (BVARs) that are often used for monetary policy. Until now, the use of trimmed-mean price statistics in forecasting inflation has often been relegated to simple univariate or "Philips-curve" approaches, thus limiting their usefulness in applications that require consistent forecasts of multiple macro variables. We find that inclusion of an extreme trimmed-mean measure—the median CPI—significantly improves the forecasts of both headline and core CPI across our wide-ranging set of BVARs. While the inflation forecasting improvements are perhaps not surprising given the current literature on core inflation statistics, we also find that inclusion of the median CPI improves the forecasting accuracy of the central bank's primary instrument for monetary policy—the federal funds rate. We conclude with a few illustrative exercises that highlight the usefulness of using the median CPI.

This paper reinvestigates the performance of trimmed-mean inflation measures some 20 years since their inception, asking whether there is a particular trimmed-mean measure that dominates the median CPI.

Equal access to small-business credit is a critical underpinning to equity in economic opportunity; however, it is difficult to regularly assess the fairness of credit provision. Prior research has focused on the Federal Reserve Board’s Survey of Small Business Finance, but the most recent data from this source is from 2003. This article provides preliminary results on new credit access questions added to the Census Bureau’s 2021 Annual Business Survey. We find that minority-owned businesses generally were just as likely to apply for credit in 2020, but Black-, Asian-, and Hispanic-owned businesses were less likely than white-owned businesses to report receiving all of the credit that they sought. Also, Black-, Asian-, and Hispanic-owned businesses more frequently reported seeking credit in order to cover operating expenses rather than for financing capital expenditures or expansion. Heading into 2022, minority-owned businesses report weaker ongoing viability.

The Median CPI is well-known as an accurate predictor of future inflation. But it’s just one of many possible trimmed-mean inflation measures. Recent research compares these types of measures to see which tracks future inflation best. Not only does the Median CPI outperform other trims in predicting CPI inflation, it also does a better job of predicting PCE inflation, the FOMC’s preferred measure, than the core PCE.

Okun’s law is a statistical relationship between unemployment and GDP that is widely used as a rule of thumb for assessing the unemployment rate.

In the face of falling house prices, decreasing rates of homeownership, and a glut of vacant homes, the Consumer Price Index’s measure of the cost of owner-occupied housing has begun to accelerate.

It has often been reported that different demographic groups show persistent differences in their inflation expectations.

There are many ways to forecast the future rate of inflation, ranging from sophisticated statistical models involving hundreds of variables to hunches based on past experience.

Some items that make up the CPI change prices frequently, while others are slow to change. We explore whether these two sets of prices-sticky and flexible-provide insight on different aspects of the inflation process.

When will the world’s production of oil peak, and what will the economic consequences be?

Frequently asked questions about inflation ranging from how to achieve price stability to the Federal Reserve’s dual mandate to how to gauge when people are concerned about inflation.