As mixture regression models increasingly receive attention from both theory and practice, the question of selecting the correct number of segments gains urgency. A misspecification can lead to an under- or oversegmentation, thus resulting in flawed management decisions on customer targeting or...

In contrast to conventional model selection criteria, the Focused Information Criterion (FIC) allows for the purpose-specific choice of model specifications. This accommodates the idea that one kind of model might be highly appropriate for inferences on a particular focus parameter, but not for...

This chapter reviews methods for selecting empirically relevant predictors from a set of N potentially relevant ones for the purpose of forecasting a scalar time series. First, criterion-based procedures in the conventional case when N is small relative to the sample size, T , are reviewed. Then...

This paper considers the problem of aggregation in the case of large linear dynamic panels, where each micro unit is potentially related to all other micro units, and where micro innovations are allowed to be cross sectionally dependent. Following Pesaran (2003), an optimal aggregate function is...