Financial institutions

FEDS Paper: Paying More and Buying Less: 2025 Tariffs and U.S. Household Spending

Sinem Hacıoğlu Hoke and Leo FelerThis paper estimates the effects of the 2025 U.S. tariffs on household spending using transaction-level data linked to tariff exposure and a tariff sentiment survey. Comparing high versus low tariff-exposed categories, we find 15 to 20 percent price pass-through. At the mean increase in tariff exposure, prices rise by 1 to 2 percent while spending falls by roughly 4 percent.

FEDS Paper: Financial Liberalizations, Booms, and Crashes

Maximilian Grimm, Moritz Schularick, and Emil VernerFinancial liberalization is often seen as a way to deepen credit markets and stimulate economic growth, but it may also fuel credit booms that end in crisis. We construct a new cross-country database of banking regulation policies covering 21 regulatory indicators for 18 advanced economies since World War II. We distinguish liberalizations that directly relax constraints on credit supply from broader financial reforms.

FEDS Paper: Alternative Scenarios at the Federal Reserve from 1968 to 2020: Data, Interpretation, and Evaluation

Edward Herbst, Scott Konzem, and Cristina ScofieldWe comprehensively document 1,265 Federal Reserve staff alternative scenarios presented to the Federal Open Market Committee in publicly released materials from 1968 to 2020. Scenarios grew in frequency and sophistication, typically spanning a range of outcomes around the baseline.

FEDS Paper: Skill and Efficiency in the U.S. Mutual Fund Industry

Dong Hwan Oh and Andrew J. PattonWe propose a new measure of mutual fund manager ability: "efficiency" is the ability to accrue the risk premium associated with a risk factor. The familiar abnormal return, or alpha, is shown to be the sum of two distinct measures of ability: "aggregate efficiency" which is the beta-weighted sum of the fund's (in)efficiencies across risk factors, and "skill," the component that is unrelated to factor exposures. Using a panel of U.S.

Firm level heterogeneity and the impact of monetary policy on labour demand

Monetary policy asymmetrically affects the response of firms’ employment to an output shock and plays a role in cushioning employment adjustment over the business cycle. Combining annual firm-level data until 2020 with quarterly firm-level data until 2023 and high-frequency monetary policy surprises, we show that for a given change in output, monetary policy influences the extent to which firms hold on to labour, or “labour hoard”.

Firm level heterogeneity and the impact of monetary policy on labour demand

Monetary policy asymmetrically affects the response of firms’ employment to an output shock and plays a role in cushioning employment adjustment over the business cycle. Combining annual firm-level data until 2020 with quarterly firm-level data until 2023 and high-frequency monetary policy surprises, we show that for a given change in output, monetary policy influences the extent to which firms hold on to labour, or “labour hoard”.

Stockholding in Europe: Evidence from the Consumer Expectations Survey

We examine recent changes in stock market participation using newly available survey data from eleven euro area countries over the period 2020–2024. The evidence points to substantial turnover, with around 10% of non-stockholders entering the market each year, and more than 20% of stockholders exiting. New entrants tend to have lower education, income, financial literacy, and risk tolerance than established investors, indicating a shift in the composition of market participants. We also highlight the growing importance of cryptocurrency investments among retail investors.

Identifying relationship-level effects using covariance restrictions

We propose a new model in which relationship-specific effects or shocks are identified in a bipartite network under mild covariance restrictions, generalizing the influential Abowd et al. (1999) framework. For example, separate demand shocks are identified for each bank from which a firm borrows. We show how previous approaches break down when confronted with such heterogeneity, while our novel identification strategy yields a simple estimator that is consistent and asymptotically normal, under weaker network density assumptions than previous approaches.

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