In this paper a likelihood-based multivariate unit root testing framework is utilized to test whether the real exchange rates of G10 countries are non-stationary. The framework uses a likelihood ratio statistic which combines the information across all involved countries while retaining...

In this paper we propose a Bayesian analysis of seasonal unit roots in quarterly observed time series. Seasonal unit root processes are useful to describe economic series with changing seasonal fluctuations. A natural alternative model for similar purposes contains deterministic seasonal mean...

We develop a new Bayesian approach to estimate the parameters of a latent-class model for the joint clustering of both modes of two-mode data matrices. Posterior results are obtained using a Gibbs sampler with data augmentation. Our Bayesian approach has three advantages over existing methods....

We develop a formal statistical approach to investigate the possibility that leading indicator variables have different lead times at business cycle peaks and troughs. For this purpose, we propose a novel Markov switching vector autoregressive model, where economic growth and leading indicators...

In applied economic research computable general equilibrium [CGE] models in which the behavior of economic agents are modeled, are widely used. In many CGE models, the Linear Expenditure System [LES] is used to model behavior of the household sector. The disadvantage of LES is that the Engel...

We propose a new and simple methodology to estimate the loss function associated with experts' forecasts. Under the assumption of conditional normality of the data and the forecast distribution, the asymmetry parameter of the lin-lin and linex loss function can easily be estimated using a linear...

We propose a novel Bayesian test under a (noninformative) Jeffreys’ prior specifica- tion. We check whether the fixed scalar value of the so-called Bayesian Score Statistic (BSS) under the null hypothesis is a plausible realization from its known and standard- ized distribution under the...

We propose a multivariate nonlinear econometric time series model, which can be used to examine if there is common nonlinearity across economic variables. The model is a multivariate censored latent effects autoregression. The key feature of this model is that nonlinearity appears as separate...

A new time series model is proposed to describe observed asymmetries in postwar unemployment data. We assume that recession periods, when unemployment increases rapidly, are caused by unobserved positive shocks. The generating mechanism of these latent shocks is a censored regression model,...

This paper is concerned with forecasting univariate seasonal time series data using periodic autoregressive models. We show how one should account for unit roots and deterministic terms when generating out-of-sample forecasts. We illustrate the models for various quarterly UK consumption series.