In this paper we put forward a Bayesian Model Averaging method dealing with model uncertainty in the presence of potential spatial autocorrelation. The method uses spatial filtering in order to account for different types of spatial links. We contribute to existing methods that handle spatial...

Using a two-sector endogenous growth model, this paper explores how productivity shocks in the goods and human capital producing sectors contribute to explaining aggregate cycles in output, consumption, investment and hours. To contextualize our findings, we also assess whether the human capital...

One of the more common methods used to model international real business cycles is through the use of a dynamic stochastic general equilibrium (DSGE) model. Guo and Sturzenegger (1998) argue that an increasing returns to scale production technology can improve the performance of such a model....

This paper conducts an empirical analysis of the heterogeneity of recessions in monthly U.S. coincident and leading indicator variables. Univariate Markovswitching models indicate that it is appropriate to allow for two distinct recession regimes, corresponding with 'mild' and 'severe'...

In this paper, we assess whether key relations between US interest rates have been stable over time. This is done by estimating trivariate hybrid time-varying parameter Bayesian VAR models with stochastic volatility for the three-month Treasury bill rate, the slope of the Treasury yield curve...

We estimate a Markov-switching mixture of two familiar macroeconomic models: a richly parameterized dynamic stochastic general equilibrium (DSGE) model and a corresponding Bayesian vector autoregression (BVAR) model. We show that the Markov-switching mixture model dominates both individual...

By means of a very simple example, this note illustrates the appeal of using Bayesian rather than classical methods to produce inference on hidden states in models of Markovian regime switching.

Koop, Pesaran and Smith (2011) suggest a simple diagnostic indicator for the Bayesian estimation of the parameters of a DSGE model. They show that, if a parameter is well identified, the precision of the posterior should improve as the (artificial) data size T increases, and the indicator checks...

In recent years, the role attached to the autonomous components of aggregate demand has attracted rising attention, as testified by the development of the Sraffian Supermulti plier model (SSM) and the attempts to include autonomous demand in the Neo-Kaleckian model. This paper reviews and...