The role of expectations for economic fluctuations has received considerable attention in recent business cycle analysis. We exploit Markov regime switching models to identify shocks in cointegrated structural vector autoregressions and investigate different identification schemes for bi-variate...

This paper exploits the fact that implied volatilities calculated from identical call and put options have often been empirically found to differ, although they should be equal in theory. We propose a new bivariate mixture multiplicative error model and show that it is a good fit to Nikkei 225...

Tests of the Fisher effect are plagued by high persistence in interest rates. Instead of standard regression analysis and asymptotic results, methods relying on local-to-unity asymptotics are employed in testing for the Fisher effect with monthly U.S. data covering the period 1953:1-1990:12....

Using GARCH-in-Mean models, we study the robustness of the risk-return relationship in monthly U.S. stock market returns (1928:1-2004:12) with respect to the specification of the conditional mean equation. The issue is important because in this commonly used framework, unnecessarily including an...

In this paper, we propose a new GARCH-in-Mean (GARCH-M) model allowing for conditional skewness. The model is based on the so-called z distribution capable of modeling skewness and kurtosis of the size typically encountered in stock return series. The need to allow for skewness can also be...

We propose a new methodology for ranking in probability the commonly proposed drivers of inflation in the New Keynesian model. The approach is based on Bayesian model selection among restricted VAR models, each of which embodies only one or none of the candidate variables as the driver....

type="main" xml:id="obes12041-abs-0001" <title type="main">Abstract</title> <p>We propose a new methodology for ranking in probability the commonly proposed drivers of inflation in the new Keynesian model. The approach is based on Bayesian model selection among restricted vector autoregressive (VAR) models, each of which...</p>

This is a supplementary appendix to "Noncausal Vector Autoregression".