Two Essays On The Economics Of Education

In this dissertation I address different topics in education policy, taking advantage of utilizing both micro-data and economic theory. The dissertation consists of two chapters, both using Chilean data. In chapter 1, The Impact of College Admissions Policies on The Performance of High School Students, I empirically evaluate the effects of college admissions policies on high school students\u27 performance. In particular, I empirically demonstrate how increasing equality of opportunity may lead to a boost in average academic effort and shed light on the efficiency of alternative affirmative action policies. The results of this chapter suggest that affirmative action should not be seen only as a way to democratize the access to tertiary education, but also as a way to increase the motivation and performance of high school students. Methodologically speaking, this research contributes to the economic literature by estimating a rank-order tournament with heterogeneous-ability contestants. In Chapter 2, A Dynamic Model of Elementary School Choice, I study how parents choose a primary school for their child. The approach of this chapter has three main contributions to the previous literature. The empirical strategy allows me to distinguish between first among different sources of observed preferences for private vis-`a-vis public schools, and second among different causes of unequal access to high-quality schools. In the paper I model and empirically estimate how parents may have misperceptions about school quality, because test scores depend on school quality and on the socioeconomic status (SES) of the school\u27s population, parents can confound these two effects, confusing high quality schools with schools that have higher SES students. The paper contributes to the sparse literature on structural estimation with bounded rationality

Industrial Policy in Chile

This paper studies three horizontal policy instruments and two vertical ones in Chilean industrial policy, particularly regarding small and medium enterprises (SMEs). The horizontal instruments are (1) a guarantee program for borrowing by SMEs (FOGAPE), (2) a small subsidy to new exports that was applied from 1985 through 2003, and (3) the innovation subsidies provided by the Corporación de Fomento de la Producción (CORFO). The vertical policy instruments are the activities of Fundación Chile (FCh), a semi-public entrepreneur cum venture capitalist, and a CORFO program to attract foreign direct investment in information technology. Although most programs are well designed, they are numerous and insufficiently funded; Chile could benefit from a prioritization of needs and consolidation of these programs. Moreover, the instruments for making strategic bets on new sectors are particularly weak. In particular, FCh needs to refocus its activities on high-risk projects with long payoffs, something it cannot do with its small endowment.Industrial policy, Small and medium enterprises, Chile

QALC - the Question-Answering program of the Language and Cognition group at LIMSI-CNRS

International audienc

Détection automatique de structures fines de texte

National audienceDans ce papier, nous présentons un système de Détection de Structures fines de Texte (appelé DST). DST utilise un modèle prédictif obtenu par un algorithme d’apprentissage qui, pour une configuration d’indices discursifs donnés, prédit le type de relation de dépendance existant entre deux énoncés. Trois types d’indices discursifs ont été considérés (des relations lexicales, des connecteurs et un parallélisme syntaxico-sémantique) ; leur repérage repose sur des heuristiques. Nous montrons que notre système se classe parmi les plus performants

Biomass prediction in tropical forests : the canopy grain approach

18 pagesThe challenging task of biomass prediction in dense and heterogeneous tropical forest requires a multi-parameter and multi-scale characterization of forest canopies. Completely different forest structures may indeed present similar above ground biomass (AGB) values. This is probably one of the reasons explaining why tropical AGB still resists accurate mapping through remote sensing techniques. There is a clear need to combine optical and radar remote sensing to benefit from their complementary responses to forest characteristics. Radar and Lidar signals are rightly considered to provide adequate measurements of forest structure because of their capability of penetrating and interacting with all the vegetation strata. However, signal saturation at the lowest radar frequencies is observed at the midlevel of biomass range in tropical forests (Mougin et al. 1999; Imhoff, 1995). Polarimetric Interferometric (PolInsar) data could improve the inversion algorithm by injecting forest interferometric height into the inversion of P-band HV polarization signal. Within this framework, the TROPISAR mission, supported by the Centre National d'Etudes Spatiales (CNES) for the preparation of the European Space Agency (ESA) BIOMASS program is illustrative of both the importance of interdisciplinary research associating forest ecologists and physicists and the importance of combined measurements of forest properties. Lidar data is a useful technique to characterize the vertical profile of the vegetation cover (e.g. Zhao et al. 2009) which in combination with radar (Englhart et al. 2011) or optical (e.g. Baccini et al. 2008; Asner et al. 2011) and field plot data may allow vegetation carbon stocks to be mapped over large areas of tropical forest at different resolution scales ranging from 1 hectare to 1 km². However, small-footprint Lidar data are not yet accessible over sufficient extents and with sufficient revisiting time because its operational use for tropical studies remains expensive. At the opposite, very-high (VHR) resolution imagery, i.e. approximately 1-m resolution, provided by recent satellite like Geoeye, Ikonos, Orbview or Quickbird as well as the forthcoming Pleiades becomes widely available at affordable costs, or even for free in certain regions of the world through Google Earth®. Compared to coarser resolution imagery with pixel size greater than 4 meters, VHR imagery greatly improves thematic information on forest canopies. Indeed, the contrast between sunlit and shadowed trees crowns as visible on such images (Fig. 1) is potentially informative on the structure of the forest canopy while new promising methods now exist for analyzing these fine scale satellite observations (e.g. Bruniquel-Pinel & Gastellu-Etchegorry, 1998; Malhi & Roman-Cuesta, 2008; Rich et al. 2010). Besides, we believe that there is also a great potential in similarly using historical series of digitized aerial photographs that proved to be useful in the past for mapping large extents of unexplored forest (Le Touzey, 1968; Richards, 1996) for quantifying AGB changes through time. This book chapter presents the advancement of a research program undertaken by our team for estimating high biomass mangrove and terra firme forests of Amazonia using canopy grain from VHR images (Couteron et al. 2005; Proisy et al. 2007; Barbier et al., 2010; 2011). We present in a first section, the canopy grain notion and the fundamentals of the Fourier-based Textural Ordination (FOTO) method we developed. We then introduce a dual experimental-theoretical approach implemented to understand how canopy structure modifies the reflectance signal and produces a given texture. We discuss, for example, the influence of varying sun-view acquisition conditions on canopy grain characteristics. A second section assesses the potential and limits of the canopy grain approach to predict forest stand structure and more specifically above ground biomass. Perspectives for a better understanding of canopy grain-AGB relationships conclude this work

Medium-induced broadening and softening of a parton shower

The modifications of the angular and transverse momentum distributions of quarks and gluons inside a parton shower due to the presence of a medium are studied within an analytical description that reduces to the modified leading logarithmic approximation (MLLA) of QCD in the absence of medium.Comment: 5 pages, 4 figures. v2: published versio

Discrete anisotropic radiative transfer (DART 5) for modeling airborne and satellite spectroradiometer and LIDAR acquisitions of natural and urban landscapes

International audienceSatellite and airborne optical sensors are increasingly used by scientists, and policy makers, and managers for studying and managing forests, agriculture crops, and urban areas. Their data acquired with given instrumental specifications (spectral resolution, viewing direction, sensor field-of-view, etc.) and for a specific experimental configuration (surface and atmosphere conditions, sun direction, etc.) are commonly translated into qualitative and quantitative Earth surface parameters. However, atmosphere properties and Earth surface 3D architecture often confound their interpretation. Radiative transfer models capable of simulating the Earth and atmosphere complexity are, therefore, ideal tools for linking remotely sensed data to the surface parameters. Still, many existing models are oversimplifying the Earth-atmosphere system interactions and their parameterization of sensor specifications is often neglected or poorly considered. The Discrete Anisotropic Radiative Transfer (DART) model is one of the most comprehensive physically based 3D models simulating the Earth-atmosphere radiation interaction from visible to thermal infrared wavelengths. It has been developed since 1992. It models optical signals at the entrance of imaging radiometers and laser scanners on board of satellites and airplanes, as well as the 3D radiative budget, of urban and natural landscapes for any experimental configuration and instrumental specification. It is freely distributed for research and teaching activities. This paper presents DART physical bases and its latest functionality for simulating imaging spectroscopy of natural and urban landscapes with atmosphere, including the perspective projection of airborne acquisitions and LIght Detection And Ranging (LIDAR) waveform and photon counting signals

Evaluation of the performance of slaughterhouse surveillance for bovine tuberculosis detection in Castilla y Leon, Spain

Post-mortem inspection (PMI) of routinely slaughtered cattle in abattoirs is an extremely valuable tool for detecting bovine tuberculosis (bTB) infected herds that can supplement active surveillance activities. However, its true performance is difficult to assess due to the multiple factors that may affect it. Here, we determined relative efficiencies in the detection of bTB-compatible lesions and probabilities of subsequent laboratory confirmation of abattoirs located in Castilla y Leon, one of the regions with the largest cattle population in Spain, between 2010 and 2017. The slaughtered animal population was split based on the results of the ante-mortem tests (reactors or non-reactors), and two generalized linear multivariable mixed models were fitted to each subpopulation to calculate the risk of lesion detection and laboratory confirmation per abattoir while accounting for the effect of potential confounding variables. Throughout the 8-year period, ~30,000 reactors and >2.8 million non-reactor animals in the ante-mortem tests were culled in the abattoirs under study. Bovine TB compatible lesions were detected in 4,710 (16%) reactors and 828 (0.03%) non-reactor animals, of which >95% were confirmed as infected through bacteriology. The probability of disclosure of bTB-like lesions was associated with the animal subpopulation, type of source unit, the herd size, the year of slaughter, the breed and age of the animal, and/or the season of slaughter. The probabilities of detection of bTB-like lesions varied largely depending on the abattoir in both subpopulations, ranging from 603 to 3,070 per 10,000 animals for the reactors and 0.2–16.1 per 10,000 animals for the nonreactor animals. Results obtained here will help to quantify the performance of PMI in abattoirs in Castilla y Leon and the between-abattoir variability, and to identify animals at increased risk of having bTB-like lesions detected during PMI based on animal- and farm-related factors

Expression of CD20 after viral reactivation renders HIV-reservoir cells susceptible to Rituximab

Rituximab; Viral reactivation; CD20Rituximab; Reactivació viral; CD20Rituximab; Reactivación viral; CD20The identification of exclusive markers to target HIV-reservoir cells will represent a significant advance in the search for therapies to cure HIV. Here, we identify the B lymphocyte antigen CD20 as a marker for HIV-infected cells in vitro and in vivo. The CD20 molecule is dimly expressed in a subpopulation of CD4-positive (CD4+) T lymphocytes from blood, with high levels of cell activation and heterogeneous memory phenotypes. In lymph node samples from infected patients, CD20 is present in productively HIV-infected cells, and ex vivo viral infection selectively upregulates the expression of CD20 during early infection. In samples from patients on antiretroviral therapy (ART) this subpopulation is significantly enriched in HIV transcripts, and the anti-CD20 monoclonal antibody Rituximab induces cell killing, which reduces the pool of HIV-expressing cells when combined with latency reversal agents. We provide a tool for targeting this active HIV-reservoir after viral reactivation in patients while on ART.This study was supported by the American National Institutes of Health (grant R21AI118411 to M.B.), the Spanish Secretariat of Science and Innovation and FEDER funds (grant SAF2015-67334-R [MINECO/FEDER]), the Spanish "Ministerio de Economia y Competitividad, Instituto de Salud Carlos III" (ISCIII, PI17/01470), GeSIDA and the Spanish AIDS network Red Tematica Cooperativa de Investigacion en SIDA (RD16/0025/0007). M.B. is supported by the Miguel Servet program funded by the Spanish Health Institute Carlos III (CP17/00179). M.G. is supported by the "Pla estrategic de recerca i innovacio en salut" (PERIS), from the Catalan Government

Statistical shape modeling of the left ventricle: myocardial infarct classification challenge

Statistical shape modeling is a powerful tool for visualizing and quantifying geometric and functional patterns of the heart. After myocardial infarction (MI), the left ventricle typically remodels in response to physiological challenges. Several methods have been proposed in the literature to describe statistical shape changes. Which method best characterizes left ventricular remodeling after MI is an open research question. A better descriptor of remodeling is expected to provide a more accurate evaluation of disease status in MI patients. We therefore designed a challenge to test shape characterization in MI given a set of three-dimensional left ventricular surface points. The training set comprised 100 MI patients, and 100 asymptomatic volunteers (AV). The challenge was initiated in 2015 at the Statistical Atlases and Computational Models of the Heart workshop, in conjunction with the MICCAI conference. The training set with labels was provided to participants, who were asked to submit the likelihood of MI from a different (validation) set of 200 cases (100 AV and 100 MI). Sensitivity, specificity, accuracy and area under the receiver operating characteristic curve were used as the outcome measures. The goals of this challenge were to (1) establish a common dataset for evaluating statistical shape modeling algorithms in MI, and (2) test whether statistical shape modeling provides additional information characterizing MI patients over standard clinical measures. Eleven groups with a wide variety of classification and feature extraction approaches participated in this challenge. All methods achieved excellent classification results with accuracy ranges from 0.83 to 0.98. The areas under the receiver operating characteristic curves were all above 0.90. Four methods showed significantly higher performance than standard clinical measures. The dataset and software for evaluation are available from the Cardiac Atlas Project website1