We study the state-dependent trading behavior of financial intermediaries in the oil futures market, using structural vector autoregressions with Markov switching in heteroskedasticity. We decompose changes in futures price volatility into changes in the slopes of traders' demand curves and in...

We quantify the causal link between exchange rate movements and sovereign risk of 16 major emerging market economies (EMEs) by means of structural vector autoregressive models (SVARs) using data from 10/2004 through 12/2016. We apply a novel data based identification approach of the structural...

This paper investigates whether there are bubbles in stock prices. We do this using a previously studied structural vector autoregressive (SVAR) model claiming to distinguish fundamental and non-fundamental shocks to real stock prices. The SVAR model relies on an identification restriction in...

In proxy vector autoregressive models, the structural shocks of interest are identified by an instrument. Although heteroskedasticity is occasionally allowed for, it is typically taken for granted that the impact effects of the structural shocks are time-invariant despite the change in their...

We construct a news-based viral disease index and study the dynamic impact of epidemics on the world economy, using structural vector autoregressions. Epidemic shocks have persistently negative effects, both directly and indirectly, on affected countries and on world output. The shocks lead to a...

Tests for identification through heteroskedasticity in structural vector autoregressive analysis are developed for models with two volatility states where the time point of volatility change is known. The tests are Wald type tests for which only the unrestricted model including the covariance...

Methods for constructing joint confidence bands for impulse response functions which are commonly used in vector autoregressive analysis are reviewed. While considering separate intervals for each horizon individually still seems to be the most common approach, a substantial number of methods...

Different bootstrap methods and estimation techniques for inference for structural vector autoregressive (SVAR) models identified by conditional heteroskedasticity are reviewed and compared in a Monte Carlo study. The model is a SVAR model with generalized autoregressive conditional...

We develop a vector autoregressive framework for combining the information in an external instrument with the information in the second moments of the data to identify latent monetary shocks in the United States. We show that the framework improves the identification of the structural model and...

In order to identify structural shocks that affect economic variables, restrictions need to be imposed on the parameters of structural vector autoregressive (SVAR) models. Economic theory is the primary source of such restrictions. However, only over-identifying restrictions can be tested with...