Gaussian Approximations of Small Noise Diffusions in Kullback-Leibler Divergence

We study Gaussian approximations to the distribution of a diffusion. The approximations are easy to compute: they are defined by two simple ordinary differential equations for the mean and the covariance. Time correlations can also be computed via solution of a linear stochastic differential equation. We show, using the Kullback-Leibler divergence, that the approximations are accurate in the small noise regime. An analogous discrete time setting is also studied. The results provide both theoretical support for the use of Gaussian processes in the approximation of diffusions, and methodological guidance in the construction of Gaussian approximations in applications

Innovation and job creation and destruction : evidence from Spain

In this paper we examine the effect of innovation on job creation and job destruction in Spanish manufacturing. Our empirical analysis is based on firm-level longitudinal data from which we have information on employment and innovation activity. The estimation approach consists of a two-step procedure that takes into account the fact that firms endogenously choose positive, negative or zero growth in employment, in which the selection mechanism is an ordered probit. Our results point out the importance of innovation variables on employment growth: innovative firms create more jobs -and destroy fewer- than non-innovative, and the degree of technological effort has a strong positive effect on net employment creation

FORECAST OF THE EXPECTED NON-EPIDEMIC MORBIDITY OF ACUTE DISEASES USING RESAMPLING METHODS

In epidemiological surveillance it is important that any unusual increase of reported cases be detected as rapidly as possible. Reliable forecasting based on a suitable time series model for an epidemiological indicator is necessary for estimating the expected non-epidemic indicator and to elaborate an alert threshold. Time series analysis of acute diseases often use Gaussian autoregressive integrated moving average models. However, these approaches could be adversely affected by departures from the true underlying distribution. The objective of this paper is to introduce a bootstrap procedure for obtaining prediction intervals in linear models in order to avoid the normality assumption. We present a Monte Carlo study comparing the finite sample properties of the bootstrap prediction intervals with those of alternative methods. Finally, we illustrate the performance of the proposed method with a meningococcal disease incidence series.

Chiral low-energy constants from tau data

We analyze how the recent precise hadronic tau-decay data on the V-A spectral function and general properties of QCD such as analyticity, the operator product expansion and chiral perturbation theory (ChPT), can be used to improve the knowledge of some of the low-energy constants of ChPT. In particular we find the most precise values of L_{9,10} (or equivalently l_{5,6}) at order p^4 and p^6 and the first phenomenological determination of C_87 (c_50).Comment: Proceedings of the 6th International Workshop on Chiral Dynamics (Bern, Switzerland, July 6-10, 2009). 9 pages, 3 figure

A Dual Aspect Theory of Shared Intention

In this article I propose an original view of the nature of shared intention. In contrast to psychological views (Bratman, Searle, Tuomela) and normative views (Gilbert), I argue that both functional roles played by attitudes of individual participants and interpersonal obligations are factors of central and independent significance for explaining what shared intention is. It is widely agreed that shared intention (I) normally motivates participants to act, and (II) normally creates obligations between them. I argue that the view I propose can explain why it is not a mere accident that both (I) and (II) are true of shared intention, while psychological and normative views cannot. The basic idea is that shared intention involves a structure of attitudes of individuals –including, most importantly, attitudes of reliance – which normally plays the relevant motivating roles and creates the relevant obligations

INNOVATION AND JOB CREATION AND DESTRUCTION: EVIDENCE FROM SPAIN

In this paper we examine the effect of innovation on job creation and job destruction in Spanish manufacturing. Our empirical analysis is based on firm-level longitudinal data from which we have information on employment and innovation activity. The estimation approach consists of a two-step procedure that takes into account the fact that firms endogenously choose positive, negative or zero growth in employment, in which the selection mechanism is an ordered probit. Our results point out the importance of innovation variables on employment growth: innovative firms create more jobs –and destroy fewer– than non-innovative, and the degree of technological effort has a strong positive effect on net employment creation.