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Elmar Mertens
Research
- Division
Monetary Policy Research
- Current Position
-
Principal Economist
- Fields of interest
-
Macroeconomics and Monetary Economics,Mathematical and Quantitative Methods
- Education
- 2004-2007
PhD in Economics, University of Lausanne, Switzerland
- 2002-2004
Swiss Program for Beginning Doctoral Students, Study Center Gerzensee, Switzerland
- 1995-2000
Master of Arts (HSG), University of St. Gallen, Switzerland
- Professional experience
- 2025-
Principal Economist, Monetary Policy Research, Directorate General Research, European Central Bank, Frankfurt, Germany
- 2018-2025
Senior Economist, Deutsche Bundesbank, Frankfurt, Germany
- 2017-2018
Senior Economist, Bank for International Settlements, Basel, Switzerland
- 2008-2016
Economist (Senior/Principal), Monetary Affairs Division, Federal Reserve Board, Washington DC, USA
- 17 September 2026
- WORKING PAPER SERIES - No. 3284Details
- Abstract
- 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. After reformulating the single-histogram problem, we derive a new analytic characterization of the multiple-histogram case, solved by Iterative Proportional Fitting and applicable to simulated densities from essentially any model. Applying the method to real-time forecasts from a Bayesian VAR with time-varying volatility, we find that tilting to SPF histograms substantially improves accuracy relative to the model’s baseline forecasts, especially during the Great Recession and the COVID-19 pandemic. The gains extend beyond the variables the SPF targets, improving forecasts for other variables in the system as well.
- JEL Code
- C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
- 15 June 2026
- DISCUSSION PAPER SERIES - No. 30Details
- Abstract
- The paper documents models used to analyse the interactions and trade-offs between price and financial stability at the European Central Bank. The paper describes a simple conceptual framework to think about the short- and medium-term trade-offs between price and financial stability. Short-term trade-offs arise whenever current inflationary pressure is high, but the financial system is experiencing stress. Medium-term trade-offs arise whenever current inflationary pressure is low, but risk is building up in the financial system. We document four main sets of models used to quantify trade-offs: time series models, balance sheet models, credit risk models and DSGE models with banking and financial frictions.
- JEL Code
- E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation