In this paper, we model and forecast Australian domestic tourism demand. We use a regression framework to estimate important economic relationships for domestic tourism demand. We also identify the impact of world events such as the 2000 Sydney Olympics and the 2002 Bali bombings on Australian...

VAR models are used in practice in preference to VARMA models due to the difficult issues involved in the identification and estimation of VARMA models. This paper examines if VAR models are good enough for forecasting macroeconomic variables. To answer this question, we extend the Tiao and Tsay...

This paper has a focus on non-stationary time series formed from small non-negative integer values which may contain many zeros and may be over-dispersed. It describes a study undertaken to compare various suitable adaptations of the simple exponential smoothing method of forecasting on a...

In this paper, we propose a new Empirical Information Criterion (EIC) for model selection which penalizes the likelihood of the data by a function of the number of parameters in the model. It is designed to be used where there are a large number of time series to be forecast. However, a...

This paper revisits the least squares estimator of the linear regression with a structural break. We view the model as an approximation to the true data generating process whose exact nature is unknown but perhaps changing over time either continuously or with some jumps. This view is widely...

This paper shows that in the presence of model mis-specification, the conventional inference procedures for structural-break models are invalid. In doing so, we establish new distribution theory for structural break models under the relaxed assumption that our structural break model is the best...

Using an innovations state space approach, it has been found that the Akaike information criterion (AIC) works slightly better, on average, than prediction validation on withheld data, for choosing between the various common methods of exponential smoothing for forecasting. There is, however, a...

Intermittent demand commonly occurs with inventory data, with many time periods having no demand and small demand in the other periods. Croston's method is a widely used procedure for intermittent demand forecasting. However, it is an ad hoc method with no properly formulated underlying...

A Kalman filter, suitable for application to a stationary or a non-stationary time series, is proposed. It works on time series with missing values. It can be used on seasonal time series where the associated state space model may not satisfy the traditional observability condition. A new...

When people forecast, they often use analogies but in an unstructured manner. We propose a structured judgmental procedure that involves asking experts to list as many analogies as they can, rate how similar the analogies are to the target situation, and match the outcomes of the analogies with...