Quatro ensaios em Economia da Educa ção
Notice bibliographique
Résumé
This thesis comprises four essays in economics of education. The first two essays are focused on the returns of accumulated human capital, in which the Quadros de Pessoal dataset is used. The first essay examines the evolution of returns to education for Portuguese workers during the period 1986{2009. In order to address the possible estimate bias due to the endogeneity, the education is instrumented by the quarter of birth and by the changes in the Portuguese compulsory schooling laws. In addition, a new instrumental variable is proposed: average education by region in the year in which individual entered school. Also in the context of the returns to education, in the second essay, the existence and size of human capital spillovers at different levels of analysis (firm, regional and inter-regional) is investigated, allowing to understand how the interactions among Portuguese workers can be determinant of differences in individual wages. Furthermore, the aggregated human capital is measured in three different ways: average education, share of high qualified workers and an adjusted multi-dimensional skill index. To control to the imperfect substitutability across workers, two qualification groups of workers are considered. Using a matched employer-employee dataset for the period 2002-2009 complemented by variables at county level from other sources, augmented Mincerian wage equations are estimated using different estimation methodologies. The third and fourth essays focus on the human capital accumulation process and the MISI and JNE Statistics datasets are used. The third essay analyses the determinants that influence the students' achievement of secondary education and, in addition, estimates the school value-added. It is given greater emphasis to the analysis of the class size e effect on students' achievement. For these purposes, a multilevel variance component model, with 3 levels: student, class and school, in a value added perspective, is applied. Additionally, the results obtained from the methodologies that are commonly used in academic work on performance assessment schools, Data Envelopment Analysis (DEA) and multilevel modelling, are compared. Finally, the fourth essay examines which observable teachers' characteristics, who teach Mathematics and Portuguese in the secondary education, influence the achievement gains of their students, taking into account a whole set of other factors that influence its progression, such as student's characteristics and class size. A value-added approach that adjusts for teacher fixed-effects is applied.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».