Assessing the labor supply and demand missmatch by skills in the Uruguay labor market

This article examines the mismatch between labor supply and demand for educational qualificationsin the Uruguayan labor market during 2000-2009. It attempts to measure the phenomenonof under-qualification and overqualification by occupation type based on educational requirementfor each occupation. Following the previous literature, the empirical work concentrates onthe determinants of over-education and its impact on wages.

Productivity, demand and the home market effect

The causality between international trade and industrialization is still ambiguous. We consider a model of international trade with the Home Market Effect - with differences in income and productivity between sectors and between countries - in order to identify additional channels for determining the effects of international trade on industrialization. Introducing non-homothetic preferences and differences in productivity aids in the interpretation of any apparent paradoxes within international trade, such as the commercial relations between more populated countries like China and India and large economies such as the U.S. Population size, demand composition and productivity levels constitute the three main channels for determining the effects of international trade. Interactions among these channels define the results obtained in terms of industrialization, while welfare levels are always higher in relation to autarky.

The determinants of non-compulsory education demand : an analysis from the students??? perspective

Resumen basado en el de la publicaci??n

Optimization of inverse reflector design

Aquesta tesi presenta un nou mètode pel disseny invers de reflectors. Ens hem centrat en tres temes principals: l’ús de fonts de llum reals i complexes, la definició d’un algoritme ràpid pel càlcul de la il•luminació del reflector, i la definició d’un algoritme d’optimització per trobar més eficientment el reflector desitjat. Les fonts de llum estan representades per models near-field, que es comprimeixen amb un error molt petit, fins i tot per fonts de llum amb milions de raigs i objectes a il•luminar molt propers. Llavors proposem un mètode ràpid per obtenir la distribució de la il•luminació d’un reflector i la seva comparació amb la il•luminació desitjada, i que treballa completament en la GPU. Finalment, proposem un nou mètode d’optimització global que permet trobar la solució en menys passos que molts altres mètodes d’optimització clàssics, i alhora evitant mínims locals.

Nature of Airline Demand

The Airline Industry • Big and Wide and Tall • Characteristics • Changes in Demand • Key Issues

Decadal predictability of the Atlantic Ocean in a coupled GCM: forecast skill and optimal perturbations using Linear Inverse Modelling

The decadal predictability of three-dimensional Atlantic Ocean anomalies is examined in a coupled global climate model (HadCM3) using a Linear Inverse Modelling (LIM) approach. It is found that the evolution of temperature and salinity in the Atlantic, and the strength of the meridional overturning circulation (MOC), can be effectively described by a linear dynamical system forced by white noise. The forecasts produced using this linear model are more skillful than other reference forecasts for several decades. Furthermore, significant non-normal amplification is found under several different norms. The regions from which this growth occurs are found to be fairly shallow and located in the far North Atlantic. Initially, anomalies in the Nordic Seas impact the MOC, and the anomalies then grow to fill the entire Atlantic basin, especially at depth, over one to three decades. It is found that the structure of the optimal initial condition for amplification is sensitive to the norm employed, but the initial growth seems to be dominated by MOC-related basin scale changes, irrespective of the choice of norm. The consistent identification of the far North Atlantic as the most sensitive region for small perturbations suggests that additional observations in this region would be optimal for constraining decadal climate predictions.

Evolving graphs: dynamical models, inverse problems and propagation

Applications such as neuroscience, telecommunication, online social networking, transport and retail trading give rise to connectivity patterns that change over time. In this work, we address the resulting need for network models and computational algorithms that deal with dynamic links. We introduce a new class of evolving range-dependent random graphs that gives a tractable framework for modelling and simulation. We develop a spectral algorithm for calibrating a set of edge ranges from a sequence of network snapshots and give a proof of principle illustration on some neuroscience data. We also show how the model can be used computationally and analytically to investigate the scenario where an evolutionary process, such as an epidemic, takes place on an evolving network. This allows us to study the cumulative effect of two distinct types of dynamics.