Financial institutions

FEDS Paper: Validating Large Language Model Annotations

Anne Lundgaard HansenThis paper proposes a validation framework for LLM-generated measurements when reliable benchmarks are unavailable. Validity is established by testing whether an LLM can reconstruct passages from annotated labels while maintaining semantic consistency with the original text. The framework avoids circular reasoning by establishing testable prerequisite properties that must be met for a validation to be considered successful.

Green supply chains at risk: measuring the true economic and environmental costs

Our new methodology builds an inter-country input-output table that distinguishes green products from the rest, allowing us to assess vulnerabilities in green value chains. In a multi-country, multi-sector model, our table reveals that a decoupling of green supply chains between a US-centric West and a China-centric East could globally cut trade in green products by up to 20%, lower welfare by up to 3% and raise yearly global greenhouse gas emissions by about 50 million tonnes.

FEDS Paper: AI and Coder Employment: Compiling the Evidence

Leland D. Crane and Paul E. SotoWe evaluate whether LLMs have had any discernible impact on the aggregate labor market so far. We focus on occupations that are computer programming-intensive, motivated by data showing that coding is one of the most LLM-exposed tasks. Linking O*NET to CPS we find that aggregate employment of coders has decelerated sharply since the introduction of ChatGPT.

FEDS Paper: Queuing, Service Time, and Price Dynamics in Residential Mortgage Lending

Akos Horvath and Benjamin S. KayBuilding on queuing theory, we develop and empirically validate a novel theoretical model of residential mortgage supply. Our model gives insight into how the stochastic arrival and sequential servicing of loan applications affect mortgage origination. The model provides closed-form predictions for lenders’ optimal response to changes in the level and price elasticity of mortgage demand.

IFDP Paper: Risk in a Data-Rich Model

Dario Caldara, Haroon Mumtaz, and Molin ZhongWe characterize asymmetric tail risk across over one hundred U.S. macroeconomic and financial variables using a dynamic factor model with stochastic volatility. The model unifies growth-at-risk, inflation-at-risk, and sectoral heterogeneity through common factors whose volatility responds endogenously to shocks, combined with heterogeneous factor loadings.

IFDP Paper: The Design and Effect of Tariff Retaliation: Evidence from the European Union

Ece Fisgin, Johannes Fleck, Keith RichardsWe show that the EU’s 2018 retaliation against US steel and aluminum tariffs targeted goods with low US import dependence and high substitutability. For the majority of tariffed goods, the US share of EU imports declined notably and remained below pre-2018 levels even after the retaliatory tariffs were lifted, reflecting asymmetric effects of tariffs on trade diversion.

IFDP Paper: Volatile Rates, Fragile Growth: Global Financial Risk and Productivity Dynamics

Nils Gornemann, Eugenio Rojas, Felipe SaffieDoes global financial risk affect long-run growth? Using a panel state-space model for emerging and advanced small open economies, we measure the effects of U.S. monetary policy uncertainty shocks. A one-standard-deviation shock lowers the level of the stochastic trend in emerging markets by at least 25 basis points after three years, with little effect in advanced economies.

FEDS Paper: Income Mobility of the Top One Percent

David Splinter and Jeff LarrimoreCirculation into and out of the top one percent is pronounced in the U.S. One third exit after a year and two-thirds exit after a decade. This mobility lowers top income shares when shifting from annual to multi-year income measures. Intragenerational mobility over two decades lowers recent top one percent fiscal income shares by over 10 percent. Two-decade mobility reduces top 0.1% shares by over 20 percent, top 0.01% shares by 30 percent, and top 0.001% shares by 40 percent.

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