1 resultado para ESTs, genomics, invasive species, maternal effects, rapid adaptation, selection, Senecio madagascariensis
em Repositório digital da Fundação Getúlio Vargas - FGV
Filtro por publicador
- Abertay Research Collections - Abertay University’s repository (1)
- Academic Research Repository at Institute of Developing Economies (1)
- Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España (1)
- Adam Mickiewicz University Repository (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (2)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (1)
- Applied Math and Science Education Repository - Washington - USA (1)
- Aquatic Commons (34)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (1)
- Archimer: Archive de l'Institut francais de recherche pour l'exploitation de la mer (2)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (4)
- Aston University Research Archive (3)
- Biblioteca de Teses e Dissertações da USP (1)
- Biblioteca Digital | Sistema Integrado de Documentación | UNCuyo - UNCUYO. UNIVERSIDAD NACIONAL DE CUYO. (2)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (13)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (4)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (11)
- Bioline International (1)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (52)
- Brock University, Canada (2)
- Bucknell University Digital Commons - Pensilvania - USA (4)
- CaltechTHESIS (3)
- Cambridge University Engineering Department Publications Database (10)
- CentAUR: Central Archive University of Reading - UK (17)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (69)
- Coffee Science - Universidade Federal de Lavras (1)
- CORA - Cork Open Research Archive - University College Cork - Ireland (5)
- Deakin Research Online - Australia (82)
- Digital Commons - Michigan Tech (8)
- Digital Commons - Montana Tech (1)
- Digital Commons @ DU | University of Denver Research (3)
- Digital Commons at Florida International University (12)
- DigitalCommons@The Texas Medical Center (2)
- DigitalCommons@University of Nebraska - Lincoln (7)
- DRUM (Digital Repository at the University of Maryland) (1)
- Duke University (9)
- Ecology and Society (2)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (57)
- Glasgow Theses Service (1)
- Helda - Digital Repository of University of Helsinki (22)
- Illinois Digital Environment for Access to Learning and Scholarship Repository (2)
- Indian Institute of Science - Bangalore - Índia (16)
- Instituto Gulbenkian de Ciência (2)
- Instituto Politécnico do Porto, Portugal (2)
- Memorial University Research Repository (1)
- National Center for Biotechnology Information - NCBI (8)
- Nottingham eTheses (1)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (25)
- Portal de Revistas Científicas Complutenses - Espanha (2)
- Publishing Network for Geoscientific & Environmental Data (29)
- QSpace: Queen's University - Canada (1)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (92)
- Queensland University of Technology - ePrints Archive (91)
- RDBU - Repositório Digital da Biblioteca da Unisinos (1)
- Repositório Alice (Acesso Livre à Informação Científica da Embrapa / Repository Open Access to Scientific Information from Embrapa) (2)
- Repositório Científico da Universidade de Évora - Portugal (9)
- Repositorio de la Universidad de Cuenca (1)
- Repositório digital da Fundação Getúlio Vargas - FGV (1)
- Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal (1)
- REPOSITORIO DIGITAL IMARPE - INSTITUTO DEL MAR DEL PERÚ, Peru (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (3)
- Repositório Institucional da Universidade de Brasília (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (92)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (1)
- SAPIENTIA - Universidade do Algarve - Portugal (4)
- South Carolina State Documents Depository (1)
- Universidad de Alicante (4)
- Universidad del Rosario, Colombia (1)
- Universidad Politécnica de Madrid (5)
- Universidade de Lisboa - Repositório Aberto (1)
- Universidade dos Açores - Portugal (1)
- Universidade Estadual Paulista "Júlio de Mesquita Filho" (UNESP) (1)
- Universidade Federal do Pará (4)
- Universidade Técnica de Lisboa (1)
- Universita di Parma (2)
- Universitat de Girona, Spain (5)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (1)
- Université de Lausanne, Switzerland (2)
- Université de Montréal, Canada (11)
- University of Canberra Research Repository - Australia (4)
- University of Connecticut - USA (6)
- University of Michigan (3)
- University of Queensland eSpace - Australia (21)
- University of Washington (3)
- Worcester Research and Publications - Worcester Research and Publications - UK (2)
Resumo:
This paper presents semiparametric estimators for treatment effects parameters when selection to treatment is based on observable characteristics. The parameters of interest in this paper are those that capture summarized distributional effects of the treatment. In particular, the focus is on the impact of the treatment calculated by differences in inequality measures of the potential outcomes of receiving and not receiving the treatment. These differences are called here inequality treatment effects. The estimation procedure involves a first non-parametric step in which the probability of receiving treatment given covariates, the propensity-score, is estimated. Using the reweighting method to estimate parameters of the marginal distribution of potential outcomes, in the second step weighted sample versions of inequality measures are.computed. Calculations of semiparametric effciency bounds for inequality treatment effects parameters are presented. Root-N consistency, asymptotic normality, and the achievement of the semiparametric efficiency bound are shown for the semiparametric estimators proposed. A Monte Carlo exercise is performed to investigate the behavior in finite samples of the estimator derived in the paper.