When generating conditional forecasts in dynamic models it is common to impose the conditions as restrictions on future structural shocks. However, these conditional forecasts often ignore that there may be uncertainty about the future development of the restricted variables. Our paper therefore...

We use text analysis and a novel dataset to measure the sentiment component of central bank communications in 23 countries over the 2002-2017 period. Our analysis yields three key results. First, using directed networks, we show that comovement in sentiment across central banks is not reducible...

There are many indications that formal methods are not used to their full potential by central banks today. In this paper we demonstrate how BVAR and DSGE models can be used to shed light on questions that policy makers deal with in practice using data from Sweden. We compare the forecast...

Using an empirical New-Keynesian model with optimal discretionary monetary policy, we calibrate key parameters - the central bank's preference parameters; the degree of forward-looking behavior in the determination of inflation and output; and the variances of inflation and output shocks - to...

Increasingly many central banks announce likely paths for future policy rates. Recent experience suggest that market forward rates can differ substantially from those announced. Models commonly adopted in policy analysis ignore such differences. This paper studies a simple model that can capture...

We investigate, theoretically and empirically, the relationship between monetary policy and the term structure of interest rates. In particular, we show in a dynamic macroeconomic model that if monetary policy reveals information about economic developments, interest rates of all maturities move...

Research on quantum technology spans multiple disciplines: physics, computer science, engineering, and mathematics. The objective of this manuscript is to provide an accessible introduction to this emerging field for economists that is centered around quantum computing and quantum money. We...

We propose a dynamic semi-parametric framework to study time variation in tail parameters. The framework builds on the Generalized Pareto Distribution (GPD) for modeling peaks over thresholds as in Extreme Value Theory, but casts the model in a conditional framework to allow for time-variation...

Yes, it makes a lot of sense. This paper studies how to design simple loss functions for central banks, as parsimonious approximations to social welfare. We show, both analytically and quantitatively, that simple loss functions should feature a high weight on measures of economic activity,...

We introduce time-varying systemic risk (à la He and Krishnamurthy, 2014) in an otherwise standard New-Keynesian model to study whether simple leaning-against-the-wind interest rate rules can reduce systemic risk and improve welfare. We find that while financial sector leverage contains...