Differences in Interest Rate Policy at the ECB and the Fed: An Investigation with a Medium-Scale DSGE Model.

Using two estimated models for the euro area and the United States, this paper investigates whether the observed difference in the amplitude of the interest rate cycle since 1999 in both areas is due to differences in the estimated monetary policy reaction function, differences in the structure of the economy or differences in the size and nature of the shocks hitting both economies. The paper concludes that differences in the type, size and persistence of shocks in both areas can largely explain the different interest rate setting.Policy activism ; DSGE model ; Interest rates ; Macroeconomic shocks.

Designing a Belief Function-Based Accessibility Indicator to Improve Web Browsing for Disabled People

The purpose of this study is to provide an accessibility measure of web-pages, in order to draw disabled users to the pages that have been designed to be ac-cessible to them. Our approach is based on the theory of belief functions, using data which are supplied by reports produced by automatic web content assessors that test the validity of criteria defined by the WCAG 2.0 guidelines proposed by the World Wide Web Consortium (W3C) organization. These tools detect errors with gradual degrees of certainty and their results do not always converge. For these reasons, to fuse information coming from the reports, we choose to use an information fusion framework which can take into account the uncertainty and imprecision of infor-mation as well as divergences between sources. Our accessibility indicator covers four categories of deficiencies. To validate the theoretical approach in this context, we propose an evaluation completed on a corpus of 100 most visited French news websites, and 2 evaluation tools. The results obtained illustrate the interest of our accessibility indicator

Second-Order Belief Hidden Markov Models

Hidden Markov Models (HMMs) are learning methods for pattern recognition. The probabilistic HMMs have been one of the most used techniques based on the Bayesian model. First-order probabilistic HMMs were adapted to the theory of belief functions such that Bayesian probabilities were replaced with mass functions. In this paper, we present a second-order Hidden Markov Model using belief functions. Previous works in belief HMMs have been focused on the first-order HMMs. We extend them to the second-order model

Evidence Propagation and Consensus Formation in Noisy Environments

We study the effectiveness of consensus formation in multi-agent systems where there is both belief updating based on direct evidence and also belief combination between agents. In particular, we consider the scenario in which a population of agents collaborate on the best-of-n problem where the aim is to reach a consensus about which is the best (alternatively, true) state from amongst a set of states, each with a different quality value (or level of evidence). Agents' beliefs are represented within Dempster-Shafer theory by mass functions and we investigate the macro-level properties of four well-known belief combination operators for this multi-agent consensus formation problem: Dempster's rule, Yager's rule, Dubois & Prade's operator and the averaging operator. The convergence properties of the operators are considered and simulation experiments are conducted for different evidence rates and noise levels. Results show that a combination of updating on direct evidence and belief combination between agents results in better consensus to the best state than does evidence updating alone. We also find that in this framework the operators are robust to noise. Broadly, Yager's rule is shown to be the better operator under various parameter values, i.e. convergence to the best state, robustness to noise, and scalability.Comment: 13th international conference on Scalable Uncertainty Managemen

Plasma Diffusion in Self-Consistent Fluctuations

The problem of particle diffusion in position space, as a consequence ofeleclromagnetic fluctuations is addressed. Numerical results obtained with a self-consistent hybrid code are presented, and a method to calculate diffusion coefficient in the direction perpendicular to the mean magnetic field is proposed. The diffusion is estimated for two different types of fluctuations. The first type (resuiting from an agyrotropic in itiai setting)is stationary, wide band white noise, and associated to Gaussian probability distribution function for the magnetic fluctuations. The second type (result ing from a Kelvin-Helmholtz instability) is non-stationary, with a power-law spectrum, and a non-Gaussian probabi lity distribution function. The results of the study allow revisiting the question of loading particles of solar wind origin in the Earth magnetosphere

Charting new territory for organizational ethnography : Insights from a team-based video ethnography

Purpose: Increasing complexity, fragmentation, mobility, pace, and technological intermediation of organizational life make “being there” increasingly difficult. Where do ethnographers have to be, when, for how long, and with whom to “be there” and grasp the practices, norms, and values that make the situation meaningful to natives? These novel complexities call for new forms of organizational ethnography. The purpose of this paper is to discuss the above issues. Design/methodology/approach: In this paper, the authors respond to these calls for innovative ethnographic methods in two ways. First, the paper reports on the practices and ethnographic experiences of conducting a year-long team-based video ethnography of reinsurance trading in London. Findings: Second, drawing on these experiences, the paper proposes a framework for systematizing new approaches to organizational ethnography and visualizing the ways in which they are “expanding” ethnography as it was traditionally practiced. Originality/value: The paper contributes to the ethnographic literature in three ways: first, the paper develops a framework for charting new approaches to ethnography and highlight its different dimensions – site, instrument, and fieldworker. Second, the paper outlines the opportunities and challenges associated with these expansions, specifically with regard to research design, analytical rigour, and communication of results. Third, drawing on the previous two contributions, the paper highlights configurations of methodological expansions on the aforementioned dimensions that are more promising than others in leveraging new technologies and approaches to claim new territory for organizational ethnography and enhance its relevance for understanding today's multifarious organizational realities

Evidential Communities for Complex Networks

Community detection is of great importance for understand-ing graph structure in social networks. The communities in real-world networks are often overlapped, i.e. some nodes may be a member of multiple clusters. How to uncover the overlapping communities/clusters in a complex network is a general problem in data mining of network data sets. In this paper, a novel algorithm to identify overlapping communi-ties in complex networks by a combination of an evidential modularity function, a spectral mapping method and evidential c-means clustering is devised. Experimental results indicate that this detection approach can take advantage of the theory of belief functions, and preforms good both at detecting community structure and determining the appropri-ate number of clusters. Moreover, the credal partition obtained by the proposed method could give us a deeper insight into the graph structure