Statistical models can play a crucial role in decision making. Traditional model validation tests typically make restrictive parametric assumptions about the model under the null and the alternative hypotheses. The majority of these tests examine one type of change at a time. This paper presents...

This paper develops a new non-linear model to analyse the business cycle by exploiting the relationship between the asymmetrical behaviour of the cycle and leading indicators. The model proposed is an innovations form of the structural model underlying simple exponential smoothing that is...

Theoretical results on the properties of forecasts obtained using singular spectrum analysis are presented in this paper. The mean squared forecast error is derived under broad regularity conditions, and it is shown that the forecasts obtained in practice will converge to their population...

In this paper we study a statistical method of implementing quasi-Bayes estimators for nonlinear and nonseparable GMM models, that is motivated by the ideas proposed in Chernozhukov and Hong (2003) and Creel and Kristensen (2011) and that combines simulation with nonparametric regression in the...

In this paper we propose a new methodology for selecting the window length in Singular Spectral Analysis in which the window length is determined from the data prior to the commencement of modeling. The selection procedure is based on statistical tests designed to test the convergence of the...

This paper proposes two new weighting schemes that average forecasts using different estimation windows to account for structural change. We let the weights reflect the probability of each time point being the most-recent break point, and we use the reversed ordered Cusum test statistics to...

Long-term electricity demand forecasting plays an important role in planning for future generation facilities and transmission augmentation. In a long term context, planners must adopt a probabilistic view of potential peak demand levels, therefore density forecasts (providing estimates of the...

Short-term load forecasting is an essential instrument in power system planning, operation and control. Many operating decisions are based on load forecasts, such as dispatch scheduling of generating capacity, reliability analysis, and maintenance planning for the generators. Overestimation of...

The local linear trend and global linear trend models embody extreme assumptions about trends. According to the local linear trend formulation the level and growth rate are allowed to rapidly adapt to changes in the data path. On the other hand, the Glaobal linear trend model makes no allowance...

Estimation of unknown parameters and functions involved in complex nonlinear econometric models is a very important issue. Existing estimation methods include generalised method of moments (GMM) by Hansen (1982) and others, efficient method of moments (EMM) by Gallant and Tauchen (1997), Markov...