We measure global real and nominal macroeconomic uncertainty and analyze its impact on individual countries’ macroeconomic performance. Global uncertainty is measured through the conditional variances of global factors in inflation and output growth, estimated from a bivariate dynamic factor model with GARCH errors. The impact of global uncertainty is measured by including the conditional varia...

In this article, a dynamic localization method based on multi-target tracking is presented. The originality of this method is its capability to manage and propagate uncertainties during the localization process. This multi-level uncertainty propagation stage is based on the use of the Dempster–Shafer theory. The perception system we use is composed of an omnidirectional vision system and a pano...

Uncertainty is ubiquitous. Depending on what information we have, we get different types of uncertainty. For each type of uncertainty, techniques have been developed for efficient representation and processing of this uncertainty. However, the plethora of different uncertainty techniques is often confusing for practitioners. The situation is especially difficult in frequent situations when we n...

We present an intertemporal, rational expectations equilibrium model where the cross-sectional covariances and correlations of international market returns increase during bad times, as a consequence of an endogenous increase in the “uncertainty” about the global economy. We assume that the drift rates of the fundamental processes of international economies are jointly affected by an unobservab...

We show how the Model-Free Prediction Principle of Politis (2013) can be applied to nonparametric regression with a univariate response and regressors that are high-dimensional or even infinite-dimensional, i.e., functional. Without assuming an additive model with i.i.d. errors, the Model-Free Principle is capable of yielding both consistent predictors as well as prediction intervals. 39.

We document the link between increased levels of economic and policy uncertainty and unemployment at the state-level during the 2007-2009 recession. The cross-sectional variation in uncertainty robustly matches the distribution of employment outcomes during this period. When we instrument for this cross-sectional variation using preexisting institutions, we find evidence for a causal role for u...

This paper analyses the concept of linkages and studies the development and the determinants of inter-firm linkages between electronics firms in Ireland and domestic sub-suppliers using firm level data for 1982 to 1995. We discuss the concept of inter-firm linkages and the effects of linkages. We argue that the concept of linkages developed by Hirschman (1958) is an inter-sectoral concept which...

The uncertainty theory solves problems with uncertain data. Often to perform arithmetic operations on uncertain data, the calculations on intervals are necessary. Interval arithmetic uses traditional mathematics in the calculations on intervals. There are many methods that solve the problems of uncertain data presented in the form of intervals, each of them can give in some cases different resu...

Visualization is a powerful way to facilitate data analysis, but it is crucial that visualization systems explicitly convey the presence, nature, and degree of uncertainty to users. Otherwise, there is a danger that data will be falsely interpreted, potentially leading to inaccurate conclusions. A common method for denoting uncertainty is to use error bars or similar techniques designed to conv...

Linked open data offers a set of design patterns and conventions for sharing data across the semantic web. In this position paper we enumerate some key uncertainty representation issues which apply to linked data and suggest approaches to tackling them. We suggest the need for vocabularies to enable representation of link certainty, to handle ambiguous or imprecise values and to express sets of...