FEDS Paper: Lost in Aggregation: Geographic Mismeasurement of Income and Spending

Sinem Hacioglu-Hoke, Leo Feler, and Jack ChylakUsing zip-code median income as a proxy for household income is common in economics but can mask heterogeneity and yield misleading conclusions. Using zip-code median income and self-reported household incomes from a representative panel of 150,000 U.S. households, we decompose average retail spending for 2018-2024. When using self-reported incomes, we observe substantial divergence in spending between low- and high-income households starting in mid-2021.

FEDS Paper: Trading Costs v. Indicative Liquidity in the Off-the-Run Treasury Market

Oleg SokolinskiyThis paper estimates trading costs in the off-the-run Treasury market using comprehensive transactions data and machine learning techniques. The analysis reveals several key findings that enhance the understanding of the off-the-run Treasury market liquidity. First, the indicative bid-ask spread is shown to be a biased measure of liquidity, even when not considering transaction volume.

FEDS Paper: Gauging the Sentiment of Federal Open Market Committee Communications through the Eyes of the Financial Press

Shantanu Banerjee, Paul Cordova, Michiel De Pooter, and Olesya V. GrishchenkoWe apply natural language processing tools to news articles in the financial press to construct a sentiment index—an index of the perceived semantic orientation of monetary policy communications around scheduled Federal Open Market Committee (FOMC) meetings. To that end, we develop several dictionaries that capture various monetary policy tools: conventional monetary policy, asset purchases, and forward guidance.

FEDS Paper: Soft Landing or Stagnation? A Framework for Estimating the Probabilities of Macro Scenarios

Eric EngstromAmid ongoing trade policy shifts and geopolitical uncertainty, concerns about stagflation have reemerged as a key macroeconomic risk. This paper develops a probabilistic framework to estimate the likelihood of stagflation versus soft landing scenarios over a four-quarter horizon. Building on Bekaert, Engstrom, and Ermolov (2025), the model integrates survey forecasts, structural shock decomposition, and a non-Gaussian BEGE-GARCH approach to capture time-varying volatility and skewness.

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