In the context of the multivariate Normal regression model, a mean squared error of prediction is developed for making the choice of subset of explanatory variables for predicting the response variable in future samples

A general statistical modeling problem is that given a class of competing models and new data, how one can improve the overall model performance. In general, there exist two solutions for this problem, namely model selection and model combination. Model selection is to select a single best model...

Accurate forecasts of incoming calls are crucial to optimal staffing decisions in call centers. This paper evaluates a wide range of models and forecast combination techniques by means of statistical and economic criteria. Relative to the previous literature, this paper is novel in several...

This paper applies the model confidence sets (MCS) procedure to a set of volatility models. A MSC is analogous to a confidence interval of parameter in the sense that the former contains the best forecasting model with a certain probability. The key to the MCS is that it acknowledges the...

This paper presents a new Bayesian methodology for predicting a turning point in an economic system. The methodology utilizes information-theoretic measurements for assessing likelihood functions for a turning point. This methodology shows that the total information of a likelihood function...

This paper examines the behaviour of the demand for money in Greece during 1976:1-2000:4, a period that included many of the influences that cause money-demand instability. Two empirical methodologies, vector error correction (VEC) modelling and second-generation random coefficient (RC)...