Add to ORKGWe apply a recently proposed Bayesian model selection technique, known as stochastic model specification search, for characterising the nature of the trend in macroeconomic time series. We illustrate that the methodology can be quite successfully applied to discriminate between stochastic and deterministic trends. In particular, we formulate autoregressive models with stochastic trends components and decide on whether a specific feature of the series, i.e. the underlying level and/or the rate of drift, are fixed or evolutive
This paper builds on some recent work by the author and Werner Ploberger (1991, 1994) on the develop...
We apply a recent methodology, Bayesian stochastic model specification search (SMSS), for the select...
Multiple time series models with stochastic regressors are considered and primary attention is given...
We apply a recently proposed Bayesian model selection technique, known as stochastic model specifica...
We apply a recently proposed Bayesian model selection technique, known as stochastic model specifica...
A recently proposed Bayesian model selection technique, stochastic model specification search, is ca...
We develop Bayesian techniques for estimation and model comparison in a novel Generalised Stochastic...
An important issue in modelling economic time series is whether key unobserved components representi...
An important issue in modelling economic time series is whether key unobserved components representi...
We develop Bayesian techniques for estimation and model comparison in a novel Generalized Stochastic...
This paper makes use of the novel Generalized Stochastic Unit Root (GSTUR) model, Bayesian model est...
This paper makes use of the novel Generalized Stochastic Unit Root (GSTUR) model, Bayesian model est...
Applied economists working with time series data face a dilemma in selecting between models with det...
In this paper we provide a comprehensive Bayesian posterior analysis of trend determination in gener...
Applied economists working with time series data face a dilemma in selecting between models with det...
This paper builds on some recent work by the author and Werner Ploberger (1991, 1994) on the develop...
We apply a recent methodology, Bayesian stochastic model specification search (SMSS), for the select...
Multiple time series models with stochastic regressors are considered and primary attention is given...
We apply a recently proposed Bayesian model selection technique, known as stochastic model specifica...
We apply a recently proposed Bayesian model selection technique, known as stochastic model specifica...
A recently proposed Bayesian model selection technique, stochastic model specification search, is ca...
We develop Bayesian techniques for estimation and model comparison in a novel Generalised Stochastic...
An important issue in modelling economic time series is whether key unobserved components representi...
An important issue in modelling economic time series is whether key unobserved components representi...
We develop Bayesian techniques for estimation and model comparison in a novel Generalized Stochastic...
This paper makes use of the novel Generalized Stochastic Unit Root (GSTUR) model, Bayesian model est...
This paper makes use of the novel Generalized Stochastic Unit Root (GSTUR) model, Bayesian model est...
Applied economists working with time series data face a dilemma in selecting between models with det...
In this paper we provide a comprehensive Bayesian posterior analysis of trend determination in gener...
Applied economists working with time series data face a dilemma in selecting between models with det...
This paper builds on some recent work by the author and Werner Ploberger (1991, 1994) on the develop...
We apply a recent methodology, Bayesian stochastic model specification search (SMSS), for the select...
Multiple time series models with stochastic regressors are considered and primary attention is given...