Purpose – The purpose of this paper is to propose and test empirically an inflation model containing permanent and transitory heteroskedastic components for the G7 countries. More specifically, recent evidences from the literature are gathered to construct a model with a heteroskedastic global...

A novel multivariate factor GARCH specification is used to obtain conditional covariance matrices of minimum variance portfolios containing a very large number of assets. The approach allows for time varying factor loads, and achieves great flexibility by allowing alternative specifications for...

We use panel probit models with unobserved heterogeneity and serially correlated errors in order to analyze the determinants and the dynamics of current-account reversals for a panel of developing and emerging countries. The likelihood evaluation of these models requires high-dimensional...

We develop a numerical procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-Gaussian state-space models. The procedure approximates necessary integrals using continuous approximations of target densities. Construction is achieved via efficient...

We use panel probit models with unobserved heterogeneity, state-dependence and serially correlated errors in order to analyze the determinants and the dynamics of current-account reversals for a panel of developing and emerging countries. The likelihood-based inference of these models requires...

This article proposes a multivariate model of inflation with conditionally heteroskedastic common and country-specific components. The model is estimated in one-step via Quasi-Maximum Likelihood for the G7 countries for the period Q1-1960 to Q4-2009. It is found that various model specifications...

This article investigates the statistical and economic implications of adaptive forecasting of exchange rates with panel data. The candidate exchange rate predictors are drawn from (i) macroeconomic ‘fundamentals’, (ii) returns/volatility of asset markets, and (iii) cyclical and confidence...

We develop a numerical procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-Gaussian state-space models. The procedure employs continuous approximations of filtering densities, and delivers unconditionally optimal global approximations of...