Central banks

Tracing the ripple effects of the Middle East war on euro area consumption

08/03/2026 European Central Bank Central banks

The onset of the war in the Middle East triggered a sharp deterioration in consumer confidence across the euro area, comparable in magnitude to that observed after Russia’s invasion of Ukraine. This box examines the extent to which the decline in confidence is associated with actual consumption behaviour using microdata from the ECB Consumer Expectations Survey. The analysis reveals that nominal consumption growth softened materially in April 2026, driven mainly by reduced discretionary spending, particularly among higher-income households.

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

07/31/2026 Federal Reserve Central banks

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.

FEDS Paper: Credit Surfaces and Economic Uncertainty

07/31/2026 Federal Reserve Central banks

John Geanakoplos and David E. RappoportThe Credit Surface along the leverage dimension gives the bond spread as a function of the loan-to-value ratio. Empirically, we show that uncertainty shocks typically increase spreads and steepen the credit surface, profoundly affecting the supply of credit. Theoretically, we derive necessary and sufficient conditions for the convexity of the credit surface, and for changes in the anticipated distribution of collateral prices that lead to steepening of the credit surface.

Subjective earnings and employment dynamics

07/30/2026 European Central Bank Central banks

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

07/30/2026 European Central Bank Central banks

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

07/30/2026 European Central Bank Central banks

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

07/30/2026 European Central Bank Central banks

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.

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