We analyze the properties of multiperiod forecasts which are formulated by a number of companies for a fixed horizon ahead which moves each month one period closer and are collected and diffused each month by some polling agency. Some descriptive evidence and a formal model suggest that knowing...

This note analyzes the distributional properties of Pareto Type III random variables. The orignal two parameters distribution proposed by Pareto is expanded in a three parameters version and both its density and characteristic function are derived. The analytic expression of the inverse...

The Western Balkans integration within the EU has started a legal process which is the rejection of former communist legal/political approaches and the transformation of former communist institutions. Indeed, the EU agenda has brought vertical/horizontal integration and Europeanization of...

Präsenzlücken entlang der Supply Chain sind ein häufig auftretendes Phänomen im Handel mit erheblichen Auswirkungen auf Umsatz und Gewinn. Vor diesem Hintergrund sind entscheidungsunterstützende Informationen zur Identifikation von Dauer und Ausmaß dieser Präsenzlücken, sowie über...

Selective attrition out of longitudinal datasets is a concern for empirical researchers. This paper discusses a simple way to identify both direction and magnitude of potential sample bias in household panels. The idea is to exploit multiple types of simultaneous entries into the panel. The...

Classical regression analysis uses partial coefficients to measure the influences of some variables (regressors) on another variable (regressand). However, a descriptive point of view shows that these coefficients are very bad measures of influence. Their interpretation as an average change of...

This paper constructs the probability space underlying the random variable of any time dependent econometric specification. The construction links concrete economic activity, both perceived and recorded, and econometric formulations. Furthermore, it is argued that the probability events...

Explained variance (R^2) is a familiar summary of the fit of a linear regression and has been generalized in various ways to multilevel (hierarchical) models. The multilevel models we consider in this paper are characterized by hierarchical data structures in which individuals are grouped into...

Various noninformative prior distributions have been suggested for scale parameters in hierarchical models. We construct a new folded-noncentral- t family of conditionally conjugate priors for hierarchical standard deviation parameters, and then consider noninformative and weakly informative...