European Central Bank

We develop a direct approach to incorporating survey density forecasts into model-based predictive distributions. Histogram forecasts from the U.S. Survey of Professional Forecasters (SPF) carry rich nonparametric information about expected outcomes, but existing methods rely on moment-based approximations that discard part of it. We instead tilt entropically to the histogram probabilities themselves, matching them exactly.

Measuring sentiment from financial news is a central task in economics and finance, yet most existing indicators rely on dictionary-based approaches that infer sentiment from word counts and only partially capture context, negation, and semantic structure. This paper proposes a framework for constructing daily news mood indices using transformer-based language models and evaluates whether they better represent sentiment than dictionary-based alternatives.

Estimates of potential output and the output gap are widely used in monetary, fiscal and structural policy analysis, but they are unobservable and subject to substantial real-time uncertainty. This paper examines revisions to output gap and potential growth estimates produced by the European Commission, the Eurosystem, the International Monetary Fund (IMF) and the Organisation for Economic Co-operation and Development (OECD) for the euro area and its member countries.

Suspending loan repayments is a widely used policy tool to provide liquidity during crises. We study the take-up and real effects of the 2020 Austrian corporate debt moratoria, which required banks to temporarily postpone loan repayments for eligible firms. Exploiting a discontinuity in eligibility at a two-million-euro asset threshold, we document a take-up rate of 44%, well below full participation, reflecting both the pecuniary cost of the policy and firms’ fear of stigmatization.