How do changes in the market architecture affect the dynamics of deregulated electricity prices? We investigate this issue in the context of the Italian Power Exchange (IPEX), using data on the daily average day-ahead price (PUN) between April 2004 and December 2008. Estimates of baseline time...

We consider maximum likelihood estimation of a particular noninvertible ARMA model with autoregressive conditionally heteroskedastic (ARCH) errors. The model can be seen as an extension to so-called all-pass models in that it allows for autocorrelation and for more fl exible forms of conditional...

The Reversible Jump Markov Chain Monte Carlo (RJMCMC) method can enhance Bayesian DSGE estimation by sampling from a posterior distribution spanning potentially nonnested models with parameter spaces of different dimensionality. We use the method to jointly sample from an ARMA process of unknown...

This study investigates the dynamics of quarterly real GDP per capita growth rates across four countries, the US, UK, Canada and France. I obtain estimates for ARIMA(p,q) processes for first differences of log quarterly real GDP per capita using Reversible Jump Markov Chain Monte Carlo, allowing...

In this paper, we introduce a new approach for volatility modeling in discrete and continuous time. We follow the stochastic volatility literature by assuming that the variance is a function of a state variable. However, instead of assuming that the loading function is ad hoc (e.g., exponential...

The standard state space model (SSM) treats observations as imprecise measures of the Markov latent states. Our flexible SSM treats the states and observables symmetrically, which are simultaneously determined by historical observations and up to first-lagged states. The only distinction between...

The Reversible Jump Markov Chain Monte Carlo (RJMCMC) method can enhance Bayesian DSGE estimation by sampling from a posterior distribution spanning potentially nonnested models with parameter spaces of different dimensionality. We use the method to jointly sample from an ARMA process of unknown...

We relax the standard assumption in the dynamic stochastic general equilibrium (DSGE) literature that exogenous processes are governed by AR(1) processes and estimate ARMA (p,q) orders and parameters of exogenous processes. Methodologically, we contribute to the Bayesian DSGE literature by using...

We consider maximum likelihood estimation of a particular noninvertible ARMA model with autoregressive conditionally heteroskedastic (ARCH) errors. The model can be seen as an extension to so-called all-pass models in that it allows for autocorrelation and for more fl exible forms of conditional...

The aim of this paper is to provide a detailed econometric analysis of the changes in the nominal exchange rate, inflation rate, nominal interest rate and the real gross domestic product in Turkey for the period from January 1987 to December 2007, based on the monthly data. To this end, both...