Financial institutions

FEDS Paper: How Firms Form Beliefs and the Implications for Inflation

Robert Minton and Hugo MonneryUsing survey data from U.S. firms, we study the primitive beliefs for pricesetting: firms’ forecasts of their own marginal costs. These forecasts are disconnected from CPI expectations, (over)react to current and past costs systematically, and underreact to aggregate shocks until costs move. We show that under empirically realistic cost beliefs the New Keynesian Phillips curve is steeper and less forward-looking. Supply shocks are more inflationary because they hit costs quickly.

Let the tree decide: FABART. A non-parametric factor model for nonlinear oil shock transmission

The question of how oil supply news shocks transmit to real activity, financial conditions, and regional labor markets is back at the center of the macroeconomic research agenda. To answer this question, we introduce the Factor Bayesian Additive Regression Tree (FABART) model, a nonlinear factor-augmented vector autoregression model, and apply it to a large U.S. macro-financial dataset with externally identified oil supply news shocks.

Subjective earnings and employment dynamics

We develop a new approach to estimating earnings, job, and employment dynamics using subjective expectations data from the NY Fed Survey of Consumer Expectations. These data provide beliefs about future earnings offers and acceptance probabilities, offering direct information on counterfactual outcomes and enabling identification under weaker assumptions. Our framework avoids biases from selection and unobserved heterogeneity that affect models using realized outcomes.

Let the tree decide: FABART. A non-parametric factor model for nonlinear oil shock transmission

The question of how oil supply news shocks transmit to real activity, financial conditions, and regional labor markets is back at the center of the macroeconomic research agenda. To answer this question, we introduce the Factor Bayesian Additive Regression Tree (FABART) model, a nonlinear factor-augmented vector autoregression model, and apply it to a large U.S. macro-financial dataset with externally identified oil supply news shocks.

Subjective earnings and employment dynamics

We develop a new approach to estimating earnings, job, and employment dynamics using subjective expectations data from the NY Fed Survey of Consumer Expectations. These data provide beliefs about future earnings offers and acceptance probabilities, offering direct information on counterfactual outcomes and enabling identification under weaker assumptions. Our framework avoids biases from selection and unobserved heterogeneity that affect models using realized outcomes.

A SPOT in the dark: using AI to assess financial stability risks

Financial stability risks consist of two distinct components: vulnerabilities and possible trigger events. While there has been considerable progress regarding the measurement of vulnerabilities, the assessment of possible trigger events remains largely qualitative. To fill this gap, we employ Large Language Models to extract information about the Severity and Probability Of potential Trigger events (SPOT) from a large dataset of financial news articles over the period2005 – 2026.

A SPOT in the dark: using AI to assess financial stability risks

Financial stability risks consist of two distinct components: vulnerabilities and possible trigger events. While there has been considerable progress regarding the measurement of vulnerabilities, the assessment of possible trigger events remains largely qualitative. To fill this gap, we employ Large Language Models to extract information about the Severity and Probability Of potential Trigger events (SPOT) from a large dataset of financial news articles over the period2005 – 2026.

Threshold endogeneity in vector autoregressions: reassessing monetary state dependence

We develop an endogenous threshold VAR that addresses contemporaneous dependence between the threshold variable and reduced-form innovations— a pervasive issue when regime indicators are jointly determined with system dynamics. A regime-specific copula-based control function removes this dependence instrument-free, without parametric assumptions on the threshold’s marginal distribution, while preserving the linear regime-wise least-squares structure.

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