Regional heterogeneity in wage distributions. Evidence from Spain.

Regional differences in real wages have been shown to be both large and persistent in the U.S. and the U.K., as well as in the economies of other countries. Empirical evidence suggests that wage differentials adjusted for the cost of living cannot only be explained by the unequal spatial distribution of characteristics determining earnings. Rather, average wage gap decomposition reveals the important contribution made by regional heterogeneity in the price assigned to these characteristics. This paper proposes a method for assessing regional disparities in the entire wage distribution and for decomposing the effect of differences across regions in the endowments and prices of the characteristics. The hypothesis forwarded is that the results from previous studies obtained by comparing average regional wages may be partial and nonrobust. Empirical evidence from a matched employer-employee dataset for Spain confirms marked differences in wage distributions between regions, which do not result from worker and firm characteristics but from the increasing role of regional differences in the return to human capital.

Statistical Inversion Theory in X-ray Tomography

In this thesis the X-ray tomography is discussed from the Bayesian statistical viewpoint. The unknown parameters are assumed random variables and as opposite to traditional methods the solution is obtained as a large sample of the distribution of all possible solutions. As an introduction to tomography an inversion formula for Radon transform is presented on a plane. The vastly used filtered backprojection algorithm is derived. The traditional regularization methods are presented sufficiently to ground the Bayesian approach. The measurements are foton counts at the detector pixels. Thus the assumption of a Poisson distributed measurement error is justified. Often the error is assumed Gaussian, altough the electronic noise caused by the measurement device can change the error structure. The assumption of Gaussian measurement error is discussed. In the thesis the use of different prior distributions in X-ray tomography is discussed. Especially in severely ill-posed problems the use of a suitable prior is the main part of the whole solution process. In the empirical part the presented prior distributions are tested using simulated measurements. The effect of different prior distributions produce are shown in the empirical part of the thesis. The use of prior is shown obligatory in case of severely ill-posed problem.

Labour segregation and immigrant and native-born wage distributions in Spain: an analysis using matched employer-employee data

This article carries out an empirical examination of the origin of the differences between immigrant and native-born wage structures in the Spanish labour market. Especial attention is given in the analysis to the role played by occupational and workplace segregation of immigrants. Legal immigrants from developing countries exhibit lower mean wages and a more compressed wage structure than native-born workers. By contrast, immigrants from developed countries display higher mean wages and a more dispersed wage structure. The main empirical finding is that the disparities in the wage distributions for the native-born and both groups of immigrants are largely explained by their different observed characteristics, with a particularly important influence in this context of workplace and, particularly, occupational segregation.

Speed of travelling fronts: Two-dimensional and ballistic dispersal probability distributions

The speed of traveling fronts for a two-dimensional model of a delayed reactiondispersal process is derived analytically and from simulations of molecular dynamics. We show that the one-dimensional (1D) and two-dimensional (2D) versions of a given kernel do not yield always the same speed. It is also shown that the speeds of time-delayed fronts may be higher than those predicted by the corresponding non-delayed models. This result is shown for systems with peaked dispersal kernels which lead to ballistic transport

Aerosol particle size distributions at a traffic exposed site and an urban background location in Oporto, Portugal

Aerosol size distributions from 6 to 700 nm were measured simultaneously at an urban background site and a roadside station in Oporto. The particle number concentration was higher at the traffic exposed site, where up to 90% of the size spectrum was dominated by the nucleation mode. Larger aerosol mode diameters were observed in the urban background site possibly due to the coagulation processes or uptake of gases during transport. Factor analysis has shown that road traffic and the neighbour stationary sources localised upwind affect the urban area thought intra-regional pollutant transport.

Regime Switching Models for Electricity Time Series that Capture Fat Tailed Distributions

In the power market, electricity prices play an important role at the economic level. The behavior of a price trend usually known as a structural break may change over time in terms of its mean value, its volatility, or it may change for a period of time before reverting back to its original behavior or switching to another style of behavior, and the latter is typically termed a regime shift or regime switch. Our task in this thesis is to develop an electricity price time series model that captures fat tailed distributions which can explain this behavior and analyze it for better understanding. For NordPool data used, the obtained Markov Regime-Switching model operates on two regimes: regular and non-regular. Three criteria have been considered price difference criterion, capacity/flow difference criterion and spikes in Finland criterion. The suitability of GARCH modeling to simulate multi-regime modeling is also studied.

Surface transformation hardening of carbon steel with high power fiber laser

This study investigated the surface hardening of steels via experimental tests using a multi-kilowatt fiber laser as the laser source. The influence of laser power and laser power density on the hardening effect was investigated. The microhardness analysis of various laser hardened steels was done. A thermodynamic model was developed to evaluate the thermal process of the surface treatment of a wide thin steel plate with a Gaussian laser beam. The effect of laser linear oscillation hardening (LLOS) of steel was examined. An as-rolled ferritic-pearlitic steel and a tempered martensitic steel with 0.37 wt% C content were hardened under various laser power levels and laser power densities. The optimum power density that produced the maximum hardness was found to be dependent on the laser power. The effect of laser power density on the produced hardness was revealed. The surface hardness, hardened depth and required laser power density were compared between the samples. Fiber laser was briefly compared with high power diode laser in hardening medium-carbon steel. Microhardness (HV0.01) test was done on seven different laser hardened steels, including rolled steel, quenched and tempered steel, soft annealed alloyed steel and conventionally through-hardened steel consisting of different carbon and alloy contents. The surface hardness and hardened depth were compared among the samples. The effect of grain size on surface hardness of ferritic-pearlitic steel and pearlitic-cementite steel was evaluated. In-grain indentation was done to measure the hardness of pearlitic and cementite structures. The macrohardness of the base material was found to be related to the microhardness of the softer phase structure. The measured microhardness values were compared with the conventional macrohardness (HV5) results. A thermodynamic model was developed to calculate the temperature cycle, Ac1 and Ac3 boundaries, homogenization time and cooling rate. The equations were numerically solved with an error of less than 10-8. The temperature distributions for various thicknesses were compared under different laser traverse speed. The lag of the was verified by experiments done on six different steels. The calculated thermal cycle and hardened depth were compared with measured data. Correction coefficients were applied to the model for AISI 4340 steel. AISI 4340 steel was hardened by laser linear oscillation hardening (LLOS). Equations were derived to calculate the overlapped width of adjacent tracks and the number of overlapped scans in the center of the scanned track. The effect of oscillation frequency on the hardened depth was investigated by microscopic evaluation and hardness measurement. The homogeneity of hardness and hardened depth with different processing parameters were investigated. The hardness profiles were compared with the results obtained with conventional single-track hardening. LLOS was proved to be well suitable for surface hardening in a relatively large rectangular area with considerable depth of hardening. Compared with conventional single-track scanning, LLOS produced notably smaller hardened depths while at 40 and 100 Hz LLOS resulted in higher hardness within a depth of about 0.6 mm.

Static pressure and wall shear stress distributions in air flow in a seven wire-wrapped rod bundle

An experimental investigation is performed in a turbulent flow in a seven wire-wrapped rod bundle, mounted in an open air facility. Static pressure distributions are measured on central and peripheral rods. By using a Preston tube, the wall shear stress profiles are experimentally obtained along the perimeter of the rods. The geometric parameters of the test section are P/D=1.20 and H/D=15. The measuring section is located at L/D=40 from the air inlet. It is observed that the dimensionless static pressure and wall shear stress profiles are nearly independent of the Reynolds number and strongly dependent of the wire-spacer position, with abrupt variations of the parameters in the neighborhood of the wires.

Diameter and height distributions in a gallery forest tree community and some of its main species in central Brazil over a six-year period (1985-1991)

(Diameter and height distributions in a gallery forest tree community and some of its main species in central Brazil over a six-year period (1985-1991)). The diameter and height structure were studied over six years in approximately 64 ha of the Gama gallery forest in Brasília, DF. Trees from 10 cm dbh were measured every three years from 1985 in 151 (10 x 20 m) permanent plots. Natural regeneration (individuals under 10 cm dbh) was measured in subplots within the 200 m² plots. Most individuals and species were under 45 cm diameter and 20 m high while the maximum diameter for individual species ranged from 30 to 95 cm. The diameter structure was typical of a mixed tropical forest with the number of individuals decreasing with increasing size classes and showing little change over the six years. The most abundant species occupy different positions in the canopy and have different size structures.

Spatial variations at different observational scales and the seasonal distributions of stream macroalgae in a Brazilian subtropical region

We examined the relationships between environmental variations in lotic ecosystems with the seasonal dynamics of macroalgae communities at different spatial scales: drainage basin of two rivers (Rio das Pedras and Rio Marrecas), shading (open and shaded stream segments), mesohabitat (riffles and pools), and microhabitats. Data collections were made on a monthly basis between January and December/2007. A total of 16 taxa were encountered (13 species and 3 vegetative groups). All of the biotic parameters (richness, abundance, diversity, equitability, and dominance) were found to be highly variable at all of the spatial scales evaluated. On the other hand, abiotic variables demonstrated differences only at mesohabitat (in terms of current velocity) and shaded habitat (in terms of irradiance) scales. The seasonality of the macroalgae community structure was strongly influenced by microhabitat variables (current velocity, substrate H', and irradiance), demonstrating their importance over time and at different scales. Regional variables (temperature, oxygen saturation, specific conductance, pH, and turbidity) were found to have little influence on the temporal dynamics of the macroalgae communities evaluated.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Statistique de la production et de la distribution de l'énergie électrique en France... : renseignements provisoires pour l'année... / Ministère des travaux publics, Service central des forces hydrauliques et des distributions d'énergie électrique

1929/01/01.

Statistique de la production et de la distribution de l'énergie électrique en France... : renseignements provisoires pour l'année... / Ministère des travaux publics, Service central des forces hydrauliques et des distributions d'énergie électrique

1927.