On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation

In this paper, the theory of hidden Markov models (HMM) isapplied to the problem of blind (without training sequences) channel estimationand data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedureassumes the model (i.e., the channel response) to be static throughoutthe observation sequence. By means of introducing a parametric model fortime-varying channel responses, a version of the algorithm, which is moreappropriate for mobile channels [time-dependent Baum-Welch (TDBW)] isderived. Aiming to compare algorithm behavior, a set of computer simulationsfor a GSM scenario is provided. Results indicate that, in comparisonto other Baum–Welch (BW) versions of the algorithm, the TDBW approachattains a remarkable enhancement in performance. For that purpose, onlya moderate increase in computational complexity is needed.

Contextualizing the impact of work organization on employee satisfaction

The paper assesses the relationship between the use of alternative workplace practices (AWP) and job satisfaction. Using a unique employeremployee data set with rich information on both firm and employee characteristics we test whether there is a positive impact of AWPs on job satisfaction (motivation hypothesis) or it is negative (intensification hypothesis). We expand a growing empirical literature focusing on small and medium size firms from a southern European area. Our results show an overall positive effect, depending on the specific practice considered. We also obtain some sort of time-dependence with the effects turning from negative to positive once the practice has been implemented for some time. Keywords: Job satisfaction, work organization, unobserved heterogeneity.

Estrategies per la inversió tridimensional de dades magnetotel.lúriques:

Projecte de recerca elaborat a partir d’una estada a la Dublin Institute for Advanced Studies, Irlanda, entre setembre i desembre del 2009.En els últims anys s’ha realitzat un important avanç en la modelització tridimensional en magnetotel•lúrica (MT) gracies a l'augment d’algorismes d’inversió tridimensional disponibles. Aquests codis utilitzen diferents formulacions del problema (diferències finites, elements finits o equacions integrals), diverses orientacions del sistema de coordenades i, o bé en el conveni de signe, més o menys, en la dependència temporal. Tanmateix, les impedàncies resultants per a tots els valors d'aquests codis han de ser les mateixes una vegada que es converteixen a un conveni de signe comú i al mateix sistema de coordenades. Per comparar els resultats dels diferents codis hem dissenyat models diferents de resistivitats amb estructures tridimensional incrustades en un subsòl homogeni. Un requisit fonamental d’aquests models és que generin impedàncies amb valors importants en els elements de la diagonal, que no són menyspreables. A diferència dels casos del modelització de dades magnetotel.lúriques unidimensionals i bidimensionals, pel al cas tridimensional aquests elements de les diagonals del tensor d'impedància porten informació sobre l'estructura de la resistivitat. Un dels models de terreny s'utilitza per comparar els diferents algoritmes que és la base per posterior inversió dels diferents codis. Aquesta comparació va ser seguida de la inversió per recuperar el conjunt de dades d'una estructura coneguda.

Solving non-linear stochastic models by parameterizing expectations: An application to asset pricing with production

A new algorithm called the parameterized expectations approach(PEA) for solving dynamic stochastic models under rational expectationsis developed and its advantages and disadvantages are discussed. Thisalgorithm can, in principle, approximate the true equilibrium arbitrarilywell. Also, this algorithm works from the Euler equations, so that theequilibrium does not have to be cast in the form of a planner's problem.Monte--Carlo integration and the absence of grids on the state variables,cause the computation costs not to go up exponentially when the numberof state variables or the exogenous shocks in the economy increase. \\As an application we analyze an asset pricing model with endogenousproduction. We analyze its implications for time dependence of volatilityof stock returns and the term structure of interest rates. We argue thatthis model can generate hump--shaped term structures.

Non-stationary job search when jobs are not forever: A structural estimation

This paper considers a job search model where the environment is notstationary along the unemployment spell and where jobs do not lastforever. Under this circumstance, reservation wages can be lower thanwithout separations, as in a stationary environment, but they can alsobe initially higher because of the non-stationarity of the model. Moreover,the time-dependence of reservation wages is stronger than with noseparations. The model is estimated structurally using Spanish data forthe period 1985-1996. The main finding is that, although the decrease inreservation wages is the main determinant of the change in the exit ratefrom unemployment for the first four months, later on the only effect comesfrom the job offer arrival rate, given that acceptance probabilities areroughly equal to one.

Diffusion in spatially and temporarily inhomogeneous media

In this paper we consider diffusion of a passive substance C in a temporarily and spatially inhomogeneous two-dimensional medium. As a realization for the latter we choose a phase-separating medium consisting of two substances A and B, whose dynamics is determined by the Cahn-Hilliard equation. Assuming different diffusion coefficients of C in A and B, we find that the variance of the distribution function of the said substance grows less than linearly in time. We derive a simple identity for the variance using a probabilistic ansatz and are then able to identify the interface between A and B as the main cause for this nonlinear dependence. We argue that, finally, for very large times the here temporarily dependent diffusion "constant" goes like t-1/3 to a constant asymptotic value D¿. The latter is calculated approximately by employing the effective-medium approximation and by fitting the simulation data to the said time dependence.

Magnetic field scaling of relaxation curves in small particle systems

We study the effects of the magnetic field on the relaxation of the magnetization of smallmonodomain noninteracting particles with random orientations and distribution of anisotropyconstants. Starting from a master equation, we build up an expression for the time dependence of themagnetization which takes into account thermal activation only over barriers separating energyminima, which, in our model, can be computed exactly from analytical expressions. Numericalcalculations of the relaxation curves for different distribution widths, and under different magneticfields H and temperatures T, have been performed. We show how a T ln(t/t0) scaling of the curves,at different T and for a given H, can be carried out after proper normalization of the data to theequilibrium magnetization. The resulting master curves are shown to be closely related to what wecall effective energy barrier distributions, which, in our model, can be computed exactly fromanalytical expressions. The concept of effective distribution serves us as a basis for finding a scalingvariable to scale relaxation curves at different H and a given T, thus showing that the fielddependence of energy barriers can be also extracted from relaxation measurements.

Diffusion in spatially and temporarily inhomogeneous media

In this paper we consider diffusion of a passive substance C in a temporarily and spatially inhomogeneous two-dimensional medium. As a realization for the latter we choose a phase-separating medium consisting of two substances A and B, whose dynamics is determined by the Cahn-Hilliard equation. Assuming different diffusion coefficients of C in A and B, we find that the variance of the distribution function of the said substance grows less than linearly in time. We derive a simple identity for the variance using a probabilistic ansatz and are then able to identify the interface between A and B as the main cause for this nonlinear dependence. We argue that, finally, for very large times the here temporarily dependent diffusion "constant" goes like t-1/3 to a constant asymptotic value D¿. The latter is calculated approximately by employing the effective-medium approximation and by fitting the simulation data to the said time dependence.

Dynamics of transient pattern formation in nematic liquid crystals

We analyze the dynamics of a transient pattern formation in the Fréedericksz transition corresponding to a twist geometry. We present a calculation of the time-dependent structure factor based on a dynamical model which incorporates consistently the coupling of the director field with the velocity flow and also the effect of fluctuations. The appearance and development of a characteristic periodicity is described in terms of the time dependence of the maximum of the structure factor. We find a well-defined time for the appearance of the pattern and a subsequent stage of pattern development in which the characteristic periodicity tends to an asymptotic value.

Nonlinear effects in the dynamics of transient pattern formation in nematics

A nonlinear calculation of the dynamics of transient pattern formation in the Fréedericksz transition is presented. A Gaussian decoupling is used to calculate the time dependence of the structure factor. The calculation confirms the range of validity of linear calculations argued in earlier work. In addition, it describes the decay of the transient pattern.

A simple model to describe the thixotropic behavior of paints.

We propose a simple rheological model to describe the thixotropic behavior of paints, since the classical hysteresis area, which is usually used, is not enough to evaluate thixotropy. The model is based on the assumption that viscosity is a direct measure of the structural level of the paint. The model depends on two equations: the Cross-Carreau equation to describe the equilibrium viscosity and a second order kinetic equation to express the time dependence of viscosity. Two characteristic thixotropic times are differentiated: one for the net structure breakdown, which is defined as a power law function of shear rate, and an other for the net structure buildup, which is not dependent on the shear rate. The knowledge of both kinetic processes can be used to improve the quality and applicability of paints. Five representative commercial protective marine paints are tested. They are based on chlorinated rubber, acrylic, alkyd, vinyl, and epoxy resins. The temperature dependence of the rheological behavior is also studied with the temperature ranging from 5 ºC to 35 ºC. It is found that the paints exhibit both shear thinning and thixotropic behavior. The model fits satisfactorily the thixotropy of the studied paints. It is also able to predict the thixotropy dependence on temperature. Both viscosity and the degree of thixotropy increase as the temperature decreases.

Shifted loops and coercivity from field imprinted high energy barriers in ferritin and ferrihydrite nanoparticles

We show that the coercive field in ferritin and ferrihydrite depends on the maximum magnetic field in a hysteresis loop and that coercivity and loop shifts depend both on the maximum and cooling fields. In the case of ferritin, we show that the time dependence of the magnetization also depends on the maximum and previous cooling fields. This behavior is associated to changes in the intraparticle energy barriers imprinted by these fields. Accordingly, the dependence of the coercive and loop-shift fields with the maximum field in ferritin and ferrihydrite can be described within the frame of a uniform-rotation model considering a dependence of the energy barrier with the maximum and the cooling fields.

Speed limit laws in America: economics, politics and geography

The regulation of speed limits in the US had been centralized at the federal level since 1974, until decisions were devolved to the states in 1995. However, the centralization debate has reemerged in recent years. Here, we conduct the first econometric analysis of the determinants of speed limit laws. By using economic, geographic and political variables, our results suggest that geography -which affects private mobility needs and preferences- is the main factor influencing speed limit laws. We also highlight the role played by political ideology, with Republican constituencies being associated with higher speed limits. Furthermore, we identify the presence of regional and time dependence effects. By contrast, poor road safety outcomes do not impede the enactment of high speed limits. Overall, we present the first evidence of the role played by geographical, ideological and regional characteristics, which provide us with a better understanding of the formulation of speed limit policies.

A nonlinear threshold model for the dependence of extremes of stationary sequences

One of the main implications of the efficient market hypothesis (EMH) is that expected future returns on financial assets are not predictable if investors are risk neutral. In this paper we argue that financial time series offer more information than that this hypothesis seems to supply. In particular we postulate that runs of very large returns can be predictable for small time periods. In order to prove this we propose a TAR(3,1)-GARCH(1,1) model that is able to describe two different types of extreme events: a first type generated by large uncertainty regimes where runs of extremes are not predictable and a second type where extremes come from isolated dread/joy events. This model is new in the literature in nonlinear processes. Its novelty resides on two features of the model that make it different from previous TAR methodologies. The regimes are motivated by the occurrence of extreme values and the threshold variable is defined by the shock affecting the process in the preceding period. In this way this model is able to uncover dependence and clustering of extremes in high as well as in low volatility periods. This model is tested with data from General Motors stocks prices corresponding to two crises that had a substantial impact in financial markets worldwide; the Black Monday of October 1987 and September 11th, 2001. By analyzing the periods around these crises we find evidence of statistical significance of our model and thereby of predictability of extremes for September 11th but not for Black Monday. These findings support the hypotheses of a big negative event producing runs of negative returns in the first case, and of the burst of a worldwide stock market bubble in the second example. JEL classification: C12; C15; C22; C51 Keywords and Phrases: asymmetries, crises, extreme values, hypothesis testing, leverage effect, nonlinearities, threshold models

A Hull and White formula for a general stochastic volatility jump-diffusion model with applications to the study of the short-time behavior of the implied volatility

In this paper, generalizing results in Alòs, León and Vives (2007b), we see that the dependence of jumps in the volatility under a jump-diffusion stochastic volatility model, has no effect on the short-time behaviour of the at-the-money implied volatility skew, although the corresponding Hull and White formula depends on the jumps. Towards this end, we use Malliavin calculus techniques for Lévy processes based on Løkka (2004), Petrou (2006), and Solé, Utzet and Vives (2007).