Mean--field limit of a particle approximation of the one-dimensional parabolic--parabolic Keller-Segel model without smoothing

In this work, we prove the well--posedness of a singularly interacting stochastic particle system and we establish propagation of chaos result towards the one-dimensional parabolic-parabolic Keller-Segel model

Accruals, Cash-Flows and Tobin’s q : An Investment Perspective on Firm Accruals

Following Zhang (Accounting Review, 2007) we cast firm accruals in terms of short-term investment. Since many studies consider accruals as a smoothed measure of cash flows, we first adopt Zhang specification and augment the standard Jones model with a cash-flow variable. Second, if accruals are indeed a form of short-term investment they should also be influenced by firm’s performance as measured by Tobin’s q. Consequently we propose a new version of the accrual model including a proxy for Tobin’s q. Given that accounting data and Tobin’s q are generally measured with errors, we also introduce a new estimation method based on a modified version of the Hausman artificial regression, featuring an optimal weighting matrix composed of higher moments instrumental variable estimators. Our results suggest that all the key parameters of the accrual models are indeed systematically biased with measurement errors. More importantly, our findings largely qualify Zhang’s conjecture on accruals, as both cash-flows and Tobin’s q are found strongly significant regressors of firm accruals. Relatedly we find that the Tobin’s q augmented model better isolate discretionary accruals so that the residuals of the equation are particularly well-suited to forecast stock returns.Discretionary accruals; Earnings management; Investment; Measurement errors; Higher moments; Instrumental variable estimators.

Accruals, Investment and Errors-in-Variables

We formulate well-known discretionary accruals models in an investment setting. Given that accruals basically consist of short-term investment, we introduce, (i) cash-flows, as a proxy for financial constraints and other financial markets imperfections, and (ii) Tobin’s q as a measure of capital return. Accounting data and Tobin’s q being measured with errors, we propose an econometric method based on a modified version of the Hausman artificial regression which features an optimal weighting matrix of higher moments instrumental variable estimators. The empirical results suggest that all the key parameters of the discretionary accruals models studied are biased systematically with measurement errors.Discretionary accruals; Earnings management; Investment; Measurement errors; Higher moments; Instrumental variable estimators.

Assessment of the PCDD/F fate from MSWI residue used in road construction in France

MSWI fly ash is susceptible to contain high amount of polychlorinated dibenzo-dioxins and polychlorinated dibenzo-furans. However, the use of MSWI residue for road construction started in France at a period when MSWI Bottom Ash and MSWI fly ash were not separated. From four old road sites, MSWI residue, road soils, reference soils and geo-textiles were sampled and their PCDD/F contents were analyzed. MSWI residue show a great heterogeneity but also high amounts of PCDD/F (142960 ng ITEQ kg-1 dm). Soils underlying the road show less heterogeneity and PCDD/F contents between 0.57 and 7.23 ng I-TEQ kg-1 dm, lower than ordinary soils. Moreover, the specific analysis of the 17 toxic PCDD/F congeners (notably the 2,3,7,8-TetraCDD) indicates the very low harmfulness of road soils. The study also allows to assert the relation between the MSWI residue particle size and the PCDD/F content

Spectator 1951-03-08

xii, 611 hlm.; 21 c

A Numerical Scheme for Time-Domain FE Analysis of Viscoelastic Structures with Fractional Derivative Constitutive Equations

A numerical scheme is presented for time-domain simulations of structural dynamic problems with viscoelastic materials described by fractional derivative constitutive equations. The proposed approach combines a classical Newmark time-integration method used to solve second-order mechanical systems (obtained for example after finite element discretization), with a diffusive representation based on the transformation of the fractional operator into a system of linear differential equations. The focus is given on the general formulation of the problem, the algorithm implementation into a finite element framework, and the developpement of a closed-form solution for a fractionnally damped single degree-of-freedom equation

Some improvements of the spectral learning approach for probabilistic grammatical inference

International audienceSpectral methods propose new and elegant solutions in probabilistic grammatical inference. We propose two ways to improve them. We show how a linear representation, or equivalently a weighted automata, output by the spectral learning algorithm can be taken as an initial point for the Baum Welch algorithm, in order to increase the likelihood of the observation data. Secondly, we show how the inference problem can naturally be expressed in the framework of Structured Low-Rank Approximation. Both ideas are tested on a benchmark extracted from the PAutomaC challenge