Macroeconomic time series such as total unemployment or total industrial production concern data which are aggregated across regions, sectors, or age categories. In this paper we examine if forecasts for these aggregates can be improved by considering panel models for the disaggregate series. As...

Poland has historically demonstrated exceptional resiliency in the face of change. This paper examines how Poland coped with huge structural realignments from the rise of Solidarity until the present, seeking to provide an objective analysis of Poland’s evolution of trade structures while it...

Many series are subject to data irregularities such as missing values, outliers, structural breaks and irregular spacing. Data can also be messy, and hence difficult to handle by standard procedures, when they are intrinsically non-Gaussian or contain complicated periodic patterns because they...

The conduct of time series analysis on the Euro Area currently presents problems in terms of availability of sufficiently long data sets. The ECB has provided a dataset of quarterly data from 1970 covering many data series in its Area Wide Model (AWM), but not for a number of important financial...

This paper presents a new method for sensory evaluation of industrial products with uncertain information. In this approach, sensory data provided by different evaluators are transformed into measures of consistency on fuzzy satisfaction degrees. Based on these measures of consistency, we obtain...

This paper compares the GDP forecasting performance of alternative factor models based on monthly time series for the French economy. These models are based on static and dynamic principal components. The dynamic principal components are obtained using time and frequency domain methods. The...