Sequential Monte Carlo (SMC) methods are widely used for filtering purposes of non-linear economic or financial models. Nevertheless the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov- Chain...

In this paper we assess whether exible modelling of innovations impact the predictive performance of the dividend price ratio for returns and dividend growth. Using Bayesian vector autoregressions we allow for stochastic volatility, heavy tails and skewness in the innovations. Our results...

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

This paper proposes an equilibrium relationship between expected exchange rate changes and differentials in expected returns on risky assets. We show that when expected returns on a risky asset in a certain economy are higher than the returns that are expected from investing in a risky asset in...

With the aim of constructing predictive distributions for daily returns, we introduce a new Markov normal mixture model in which the components are themselves normal mixtures. We derive the restrictions on the autocovariances and linear representation of integer powers of the time series in...

This paper is an empirical investigation into the role of credit history in determining the spread on sovereign bank loans. It employs an error-in-variables approach used in rational-expectations-macro-econometrics to set up a structural model that links sovereign loan spreads to realized...

Under inflation targeting inflation exhibits negative serial correlation in the United Kingdom, and little or no persistence in Canada, Sweden and New Zealand, and estimates of the indexation parameter in hybrid New Keynesian Phillips curves are either equal to zero, or very low, in all...

We consider estimation and inference for a regression coefficient in panels with interactive fixed effects (i.e., with a factor structure). We show that previously developed estimators and confidence intervals (CIs) might be heavily biased and size-distorted when some of the factors are weak. We...