Regressions for predicting long-term stock returns often use moving averages of earnings as the earnings trend. We show that the earnings trend can be directly estimated using unobserved components models. The estimated trends improve the fit of predictive regressions.

We propose an alternative approach to obtaining a permanent equilibrium exchange rate (PEER), based on an unobserved components (UC) model. This approach offers a number of advantages over the conventional cointegration-based PEER. Firstly, we do not rely on the prerequisite that cointegration...

The primary objective of this paper is to establish the superiority of Unobserved Components Models (UCMs) as a measure of core inflation over alternative econometric methods, namely Structural Vector Autoregressive (SVAR). UCMs have the advantage of allowing the policy makers to decide which...

This paper presents new models for aggregate UK data on mortgage possessions (foreclosures) and mortgage arrears (payment delinquencies). The innovations include the treatment of difficult to observe variations in loan quality and shifts in forbearance policy by lenders, by common latent...

This paper examines the relationship between the environmental and economic performance of firms in the European paper manufacturing industry. Based on panel data, it first investigates the relationship separately, with the analysis based on four hypotheses formulated with regard to country...

In this paper we derive asymptotic x 2 - tests for general linear hypotheses on variance components using repeated variance components models. In two examples, the two-way nested classification model and the two-way crossed classification model with interaction, we explicitly investigate the...

In this paper we derive asymptotic x 2 - tests for general linear hypotheses on variance components using repeated variance components models. In two examples, the two-way nested classification model and the two-way crossed classification model with interaction, we explicitly investigate the...