This study extends the existing forecasting accuracy debate in the tourism literature by examining the forecasting performance of various vector autoregressive (VAR) models. In particular, this study seeks to ascertain whether the introduction of the Bayesian restrictions (priors) to the unrestricted VAR process would lead to an improvement in forecasting performance in terms of achieving a hig...

In this paper we present a simultaneous modelling of bi-dimensional monthly time series representing the number of cases of two types of voluntary interruption of pregnancy (VIP) using vector autoregressive (VAR) model. The analysis confirms the existence of a causality relationship in the Granger sense between two types of VIP and a very high validity of the proposed model to describe it.

Building on Koop, Pesaran and Potter (1996), we propose the `generalized' impulse response analysis for unrestricted vector autoregressive (VAR) and cointegrated VAR models. Unlike the traditional impulse response analysis, our approach does not require orthogonalization of shocks and is invariant to the ordering of the variables in the VAR. The approach is also used in the construction of orde...

 We consider the problem of model selection in vector autoregressive model with Normal innovation. Tests such as Vuong's and Cox's tests are provided for order and model selection, i.e. for selecting the order and a suitable subset of regressors, in vector autoregressive model. We propose a test as a modified log-likelihood ratio test for selecting subsets of regressors. The Europe oil prices, ...

This paper investigates limit theory for the likelihood analysis of an I(2) cointegrated vector autoregressive (VAR) model in the presence of deterministic shifts. A log likelihood ratio (logLR) test statistic for integration indices is considered, and it is demonstrated that the asymptotic distribution of the statistic is given in the form of a generalised Dicky-Fuller type distribution. A log...

VECTOR AUTOREGRESSIVE PROCESSES WITH COMMON CYCLES MASSIMO FRANCHI & PAOLO PARUOLO JANUARY 7, 2009 Abstract. We give necessary and su cient conditions on the autoregressive polynomial for the existence of (possibly polynomial-) serial correlation common features as well as for other forms of common cycles. We characterize the resulting moving average representations. These conditions allow to d...

Generalized Space-Time Autoregressive (GSTAR) model is one of the models that usually used for modeling and forecasting space and time series data. The aim of this paper is to study further about the stationarity conditions for parameters in the GSTAR model and the relation to Vector Autoregressive (VAR) model. We focus on the theoretical study about stationarity condition in GSTAR(11) and the ...

This paper presents a procedure for estimating VAR using Sequential Discounting VAR (SDVAR) algorithm for online model learning to detect fraudulent acts using the telecommunications call detailed records (CDR). The volatility of the VAR is observed allowing for non-linearity, outliers and change points based on the works of [1]. This paper extends their procedure from univariate to multivariat...