Stronger evidence of long-run neutrality: a comment on Bernanke and Mihov

Few propositions in macroeconomics are less controversial than long-run money neutrality, yet clear and robust empirical support has not been found in time series studies. Bernanke and Mihov (1998) are comparatively successful in this hunt, but their output response to monetary policy shocks remains stubbornly persistent. This paper argues that the omission of a measure of output gap from the VAR estimated by Bernanke and Mihov lies at the heart of this ''excessive'' persistence. In the theoretical framework of a New Keynesian model similar to that of Svensson (1997) and Clarida, Gali and Gertler (1999), I prove that this omission induces persistence overestimation under relatively mild assumptions. The inclusion of a proxy for the output gap in the VAR is then shown to drastically increase the evidence for long-run money neutrality on US data, as predicted by the theoretical analysis.long-run money neutrality; technology shocks; output gap; VAR misspecification

An alternative explanation of the price puzzle

This paper proposes a simple explanation for the frequent appearance of a price puzzle in VARs designed for monetary policy analysis. It suggests that the best method of solving the puzzle implies a close connection between theory and empirics rather than the introduction of a commodity price. It proves that the omission of a measure of output gap (or potential output) spuriously produces a price puzzle (and several other incorrect conclusions) in a wide class of commonly used models. This can happen even if the model admits a triangular identification and if the forecasts produced by the misspecified VAR are optimal. When the model is tested on US data, all predictions are supported.Price puzzle; monetary policy; misspecification; output gap; potential output; technology shocks; VAR;

Improved User Tracking in 5G Millimeter Wave Mobile Networks via Refinement Operations

The millimeter wave (mmWave) frequencies offer the availability of huge bandwidths to provide unprecedented data rates to next-generation cellular mobile terminals. However, directional mmWave links are highly susceptible to rapid channel variations and suffer from severe isotropic pathloss. To face these impairments, this paper addresses the issue of tracking the channel quality of a moving user, an essential procedure for rate prediction, efficient handover and periodic monitoring and adaptation of the user's transmission configuration. The performance of an innovative tracking scheme, in which periodic refinements of the optimal steering direction are alternated to sparser refresh events, are analyzed in terms of both achievable data rate and energy consumption, and compared to those of a state-of-the-art approach. We aim at understanding in which circumstances the proposed scheme is a valid option to provide a robust and efficient mobility management solution. We show that our procedure is particularly well suited to highly variant and unstable mmWave environments.Comment: Accepted for publication to the 16th IEEE Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET), Jun. 201

Enriching Deontic Logic

It is well known that systems of action deontic logic emerging from a standard analysis of permission in terms of possibility of doing an action without incurring in a violation of the law are subject to paradoxes. In general, paradoxes are acknowledged as such if we have intuitions telling us that things should be different. The aim of this paper is to introduce a paradox-free deontic action system by (i) identifying the basic intuitions leading to the emergence of the paradoxes and (ii) exploiting these intuitions in order to develop a consistent deontic framework, where it can be shown why some phenomena seem to be paradoxical and why they are not so if interpreted in a correct way

Possibilistic and fuzzy clustering methods for robust analysis of non-precise data

This work focuses on robust clustering of data affected by imprecision. The imprecision is managed in terms of fuzzy sets. The clustering process is based on the fuzzy and possibilistic approaches. In both approaches the observations are assigned to the clusters by means of membership degrees. In fuzzy clustering the membership degrees express the degrees of sharing of the observations to the clusters. In contrast, in possibilistic clustering the membership degrees are degrees of typicality. These two sources of information are complementary because the former helps to discover the best fuzzy partition of the observations while the latter reflects how well the observations are described by the centroids and, therefore, is helpful to identify outliers. First, a fully possibilistic k-means clustering procedure is suggested. Then, in order to exploit the benefits of both the approaches, a joint possibilistic and fuzzy clustering method for fuzzy data is proposed. A selection procedure for choosing the parameters of the new clustering method is introduced. The effectiveness of the proposal is investigated by means of simulated and real-life data

An Efficient Requirement-Aware Attachment Policy for Future Millimeter Wave Vehicular Networks

The automotive industry is rapidly evolving towards connected and autonomous vehicles, whose ever more stringent data traffic requirements might exceed the capacity of traditional technologies for vehicular networks. In this scenario, densely deploying millimeter wave (mmWave) base stations is a promising approach to provide very high transmission speeds to the vehicles. However, mmWave signals suffer from high path and penetration losses which might render the communication unreliable and discontinuous. Coexistence between mmWave and Long Term Evolution (LTE) communication systems has therefore been considered to guarantee increased capacity and robustness through heterogeneous networking. Following this rationale, we face the challenge of designing fair and efficient attachment policies in heterogeneous vehicular networks. Traditional methods based on received signal quality criteria lack consideration of the vehicle's individual requirements and traffic demands, and lead to suboptimal resource allocation across the network. In this paper we propose a Quality-of-Service (QoS) aware attachment scheme which biases the cell selection as a function of the vehicular service requirements, preventing the overload of transmission links. Our simulations demonstrate that the proposed strategy significantly improves the percentage of vehicles satisfying application requirements and delivers efficient and fair association compared to state-of-the-art schemes.Comment: 8 pages, 8 figures, 2 tables, accepted to the 30th IEEE Intelligent Vehicles Symposiu

Symmetric Synchronous Collaborative Navigation

Synchronous collaborative navigation is a form of social navigation where users virtually share a web browser. In this paper, we present a symmetric, proxy-based architecture where each user can take the lead and guide others in visiting web sites, without the need for a special browser or other software. We show how we have applied this scheme to a problem-solving-oriented e-learning system

A possibilistic approach to latent structure analysis for symmetric fuzzy data.

In many situations the available amount of data is huge and can be intractable. When the data set is single valued, latent structure models are recognized techniques, which provide a useful compression of the information. This is done by considering a regression model between observed and unobserved (latent) fuzzy variables. In this paper, an extension of latent structure analysis to deal with fuzzy data is proposed. Our extension follows the possibilistic approach, widely used both in the cluster and regression frameworks. In this case, the possibilistic approach involves the formulation of a latent structure analysis for fuzzy data by optimization. Specifically, a non-linear programming problem in which the fuzziness of the model is minimized is introduced. In order to show how our model works, the results of two applications are given.Latent structure analysis, symmetric fuzzy data set, possibilistic approach.

The Immigration Policy Puzzle

This paper revisits the puzzle of immigration policy: standard economic theory predicts that free immigration improves natives' welfare, but (with few historical exceptions) an open door policy is never implemented in practice. What rationalizes the puzzle? We first review the model of immigration policy where the policy maker maximizes national income of natives net of the tax burden of immigration (Borjas, 1995). We show that this model fails to provide realistic policy outcomes when the receiving region's technology is described by a standard Cobb-Douglas or CES function, as the optimal policy imposes a complete ban on immigration or implies an unrealistically large number of immigrants relative to natives. Then the paper describes three extensions of this basic model that reconcile the theory with the evidence. The first introduces a cost of integration of the immigrant community in the destination country; the second takes into account the policy maker's redistributive concern across different social groups; the last extension considers positive spillover effects of (skilled) migrants on the receiving economy.Costs and benefits from immigration; immigration policy.