In the presence of financial frictions, banks' capital position may constrain their ability to provide loans. The banking sector may thus have important feedback effects on the macroeconomy. To shed new light on this issue, we combine two approaches. First, we use microeconomic balance sheet...

This paper investigates how government bond purchases affect leverage-constrained banks and non-financial firms by utilising a stochastic general equilibrium model. My results indicate that government bond purchases not only reduce non-financial firms' borrowing costs, amplified through a...

Economic theories are often encoded in equilibrium models that cannot be directly estimated because they lack features that, while inessential to the theoretical mechanism that is central to the specific theory, would be essential to fit the data well. We propose an econometric approach that...

We investigate whether frictions in US financial markets amplify the international propagation of US financial shocks. The dynamics of the US economy is modeled jointly with global macroeconomic and financial variables using a threshold vector autoregression that allows us to capture...

The European Central Bank (ECB) has adopted a mixture of conventional and unconventional tools in order to achieve its mandate of price stability in the current low-inflation, low-interest-rate scenario. This paper contributes to the existing literature by providing a taxonomy of the ECB’s...

This paper investigates how the ordering of variables affects properties of the time-varying covariance matrix in the Cholesky multivariate stochastic volatility model.It establishes that systematically different dynamic restrictions are imposed whenthe ratio of volatilities is time-varying....

We provide a simulation smoother to a exible state-space model with lagged states and lagged dependent variables. Qian (2014) has introduced this state-space model and proposes a fast Kalman filter with time-varying state dimension in the presence of missing observations in the data. In this...

The severity function approach (abbreviated SFA) is a method of selecting adverse scenarios from a multivariate density. It requires the scenario user (e.g. an agency that runs banking sector stress tests) to specify a "severity function", which maps candidate scenarios into a scalar severity...

We analyze Granger causality testing in a mixed-frequency VAR, where the difference in sampling frequencies of the variables is large. Given a realistic sample size, the number of high-frequency observations per low-frequency period leads to parameter proliferation problems in case we attempt to...