The class of periodic autoregressive (PAR) models, suitably extended so as to allow for 'periodic integration', has recently found widespread application to economic time series as an alternative to the time-invariant models available in the literature. An elaborate modelling strategy has been...

An extensive literature in econometrics focuses on finding the exact and approximate first and second moments of the least-squares estimator in the stable first-order linear autoregressive model with normally distributed errors. Recently, Kiviet and Phillips (2005) developed approximate moments...

We assess market integration and price transmission of perishable agricultural produce in Sub-Saharan Africa by studying Ghanaian tomato markets which are characterized by pronounced seasonality in production and trade flows. We analyse the tomato markets of Ghana by simultaneously regarding its...

In this paper we examine the asymptotic properties of the estimator of the long-run coefficient (LRC) in a dynamic regression model with integrated regressors and serially correlated errors. We show that the OLS estimators of the regression coefficients are inconsistent but the OLS-based...

We consider Particle Gibbs (PG) as a tool for Bayesian analysis of non-linear non-Gaussian state-space models. PG is a Monte Carlo (MC) approximation of the standard Gibbs procedure which uses sequential MC (SMC) importance sampling inside the Gibbs procedure to update the latent and potentially...

In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches and we consider both parametric and semiparametric estimation methods. The...

Outlying observations in time series influence parameter estimation and testing procedures, leading to biased estimates and spurious test decisions. Further inference based on these results will be misleading. In this paper the effects of outliers on the performance of ratio-based tests for a...

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model...

This note presents the R package bayesGARCH (Ardia, 2007) which provides functions for the Bayesian estimation of the parsimonious and effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids the tedious task of tuning a MCMC sampling...