This paper studies the existence of risk premia in crude oil futures prices with simple regression and Bayesian VAR models. It also studies the importance of three main risk premia models in explaining and forecasting the risk premia in practice. Whilst the existence of the premia and the...

We propose simulation-based forecasting methods for the noncausal vector autoregressive model proposed by Lanne and Saikkonen (2012). Simulation or numerical methods are required because the prediction problem is generally nonlinear and, therefore, its analytical solution is not available. It...

We employ a parsimonious nonlinear Interacted-VAR to examine whether the real effects of uncertainty shocks are greater when the economy is at the Zero Lower Bound. We find the contractionary effects of uncertainty shocks to be statistically larger when the ZLB is binding, with differences that...

In this paper, we propose a new noncausal vector autoregressive (VAR) model for non-Gaussian time series. The assumption of non-Gaussianity is needed for reasons of identifiability. Assuming that the error distribution belongs to a fairly general class of elliptical distributions, we develop an...

Persistent shifts in equilibria are likely to arise in oligopolistic markets and may be detrimental to the measurement of conduct, related markups and intensity of competition. We develop a cointegrated VAR (vector autoregression) based approach to detect long-run changes in conduct when data...

We examine bank capital shocks using a recent new approach based on non-normal errors in vector autoregressive models. Using a sample of 14 European economies over January 2004 through March 2018 we identify two distinct classes of bank capital shocks, capital tightening shocks, and bank...

We propose a new non-recursive identification scheme for uncertainty shocks, which exploits breaks in the unconditional volatility of macroeconomic variables. Such identification approach allows us to simultaneously address two major questions in the empirical literature on uncertainty: (i) Does...

This study provides estimates of the real effects of macro-uncertainty de- composed into fundamental and overconfidence bias components. Crucially, overconfidence biases lower ex-ante measures of uncertainty, while fundamen- tal uncertainty raises both ex-ante and ex-post measures. This...

We investigate the role played by systematic monetary policy in tackling the real effects of uncertainty shocks in U.S. recessions and expansions. We model key indicators of the business cycle with a nonlinear VAR that allows for different dynamics in busts and booms. Uncertainty shocks are...

Reporting point estimates and error bands for structural vector autoregressions that are only set identified is a very common practice. However, unless the researcher is persuaded on the basis of prior information that some parameter values are more plausible than others, this common practice...