This paper analyses three Granger noncausality hypotheses within a conditionally Gaussian MS-VAR model. Noncausality in mean is based on Granger´s original concept for linear predictors by defining noncausality from the 1-step ahead forecast error variance for the conditional expectation....

This paper proposes a parsimoniously time varying parameter vector autoregressive model (with exogenous variables, VARX) and studies the properties of the Lasso and adaptive Lasso as estimators of this model. The parameters of the model are assumed to follow parsimonious random walks, where...

We analyze the issue of the impact of multiple breaks on monetary neutrality results, using a long annual international data set. We empirically verify whether neutrality propositions remain addressable (and if so, whether they hold or not), when unit root tests are carried out allowing for...

We assess the efficiency of monetary policy to guide inflation expectations in high and low regimes. Using quantile regression we analyze the persistence of inflation expectations from the Consensus Economics Survey at different quantiles. We find a) empirical evidence that expectations are not...

In this paper we study 2-state Markov switching VAR models of monthly unemployment and inflation for three countries: Sweden, United Kingdom, and the United States. The primary purpose is to examine if periods of low inflation are associated with high or low unemployment volatility. We find that...

This paper presents a framework for empirical analysis of dynamic macroeconomic models using Bayesian Öltering, with a speciÖc focus on the state-space formulation of Dynamic Stochastic General Equilibrium (DSGE) models with multiple regimes. We outline the theoretical foundations of model...

The inference for hidden Markov chain models in which the structure is a multiple-equation macroeconomic model raises a number of difficulties that are not as likely to appear in smaller models. One is likely to want to allow for many states in the Markov chain without allowing the number of...

Markov models introduce persistence in the mixture distribution. In time series analysis, the mixture components relate to different persistent states characterizing the state-specific time series process. Model specification is discussed in a general form. Emphasis is put on the functional form...

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...

We investigate whether the response of the macro-economy to oil price shocks undergoes episodic changes. Employing a regime-switching vector autoregressive model we identify two regimes that are characterized by qualitatively different patterns in economic activity and inflation following oil...