Nonparametric unit-root tests are a useful addendum to the tool-box of time-series analysis. They tend to trade off power for enhanced robustness features. We consider combinations of the RURS (seasonal range unit roots) test statistic and a variant of the level-crossings count. This combination...

We explore the benefits of forecast combinations based on forecast-encompassing tests compared to simple averages and to Bates-Granger combinations. We also consider a new combination method that fuses test-based and Bates-Granger weighting. For a realistic simulation design, we generate...

In evaluating prediction models, many researchers flank comparative ex-ante prediction experiments by significance tests on accuracy improvement, such as the Diebold-Mariano test. We argue that basing the choice of prediction models on such significance tests is problematic, as this practice may...

We study the benefits of forecast combinations based on forecast-encompassing tests relative to uniformly weighted forecast averages across rival models. For a realistic simulation design, we generate multivariate time-series samples of size 40 to 200 from a macroeconomic DSGE-VAR model....

For many economic time-series variables that are observed regularly and frequently, for example weekly, the underlying activity is not distributed uniformly across the year. For the aim of predicting annual data, one may consider temporal aggregation into larger subannual units based on an...

This paper examines the relevance of incorporating seasonality in agricultural supply models. Former studies have eliminated the problem of seasonality by using seasonally adjusted data. Recent developments in cointegration techniques allow the comprehensive modelling of error-correcting...

The problem of optimal decision among unit roots, trend stationarity, and trend stationarity with structural breaks is considered. Each class is represented by a hierarchically random process whose parameters are distributed in a non-informative way. The prior frequency for all three processes...

Modelling the growth rate of economic time series with a Markov switching process in their mean and/or their variance allows to take account of two facts that are often encountered in such series, namely that the periods in which each mean is prevailing differ in their duration and that the...

In a panel of West African countries, we investigate whether data on immigrant remittance flows can be used to improve on predictive accuracy of aggregate demand in a systematic way. The results of the prediction experiments are compared to traditional significance tests of asymmetric error...

We use data generated by a macroeconomic DSGE model to study the relative benefits of forecast combinations based on forecast-encompassing tests relative to simple uniformly weighted forecast averages across rival models. Assumed rival models are four linear autoregressive specifications, one of...