Attention, les informations que vous consultez actuellement ne sont pas celles de l'année universitaire en cours. Consulter l'année universitaire 2023-2024.
UE788 - Econometric Methods
Lieu et planning
-
48 bd Jourdan
48 bd Jourdan 75014 Paris
2nd semestre / hebdomadaire, vendredi 08:00-11:00
du 8 janvier 2021 au 25 juin 2021
Description
Dernière modification : 28 mai 2020 10:39
- Type d'UE
- Enseignements fondamentaux de master
- Disciplines
- Économie
- Page web
- https://www.parisschoolofeconomics.eu/en/teaching/masters-program/ppd-public-policy-and-development/being-ppd-student-resources-internship/
- Langues
- anglais
- Mots-clés
- Économie
- Aires culturelles
- -
Intervenant·e·s
- Philipp Ketz [référent·e] assistant professor/maître assistant, Paris-Jourdan sciences économiques
This course builds on and is complementary to the first-year econometrics series. While the treatment is somewhat theoretical, the focus lies with the applicability and usefulness of econometric methods. Throughout the course the theory is motivated and illustrated by means of examples.
The first part of this course treats classic asymptotic theory, including consistency and asymptotic normality results for extremum estimators. While extremum estimators include e.g., OLS, 2SLS, and Generalized Method of Moments (GMM) estimators, the exposition focuses on Maximum Likelihood (ML) estimation. Besides covering textbook examples, such as the Probit model, the course aims at providing students with the ability to model and estimate (simple) structural models using ML. In addition to standard inference methods, the course discusses bootstrap based inference.
The second part of the course treats clustering (clustered standard errors), which plays an important role in applied econometrics. After taking this course, students will be familiar with the different techniques currently available and should be able to appropriately choose among them in applications.
As part of the course, students learn to understand and use Monte Carlo simulations as a useful tool in assessing empirical/econometric methods. Homework assignments and a final project help achieving this learning goal.
Le programme détaillé n'est pas disponible.
Master
-
Initiation/introduction
– Analyse et politique économiques
– M2/S4
Suivi et validation – semestriel hebdomadaire = 3 ECTS
MCC – examen -
Initiation/introduction
– Politiques publiques et développement
– M2/S4
Suivi et validation – semestriel hebdomadaire = 3 ECTS
MCC – examen
Renseignements
- Contacts additionnels
- -
- Informations pratiques
Mentions APE et PPD, secrétariat pédagogique, 48 bd Jourdan 75014 Paris, tél. : 01 80 52 19 43/44. Pour tout renseignement, veuillez écrire à master-ppd@psemail.eu
48 Boulevard Jourdan, 75014 Paris
du lundi au mardi de 15h30h à 17h30 et du jeudi au vendredi de 10h à 12h30.
Le syllabus et le planning du cours seront disponibles sur le site Internet :
- Direction de travaux des étudiants
- -
- Réception des candidats
- -
- Pré-requis
- -
Dernière modification : 28 mai 2020 10:39
- Type d'UE
- Enseignements fondamentaux de master
- Disciplines
- Économie
- Page web
- https://www.parisschoolofeconomics.eu/en/teaching/masters-program/ppd-public-policy-and-development/being-ppd-student-resources-internship/
- Langues
- anglais
- Mots-clés
- Économie
- Aires culturelles
- -
Intervenant·e·s
- Philipp Ketz [référent·e] assistant professor/maître assistant, Paris-Jourdan sciences économiques
This course builds on and is complementary to the first-year econometrics series. While the treatment is somewhat theoretical, the focus lies with the applicability and usefulness of econometric methods. Throughout the course the theory is motivated and illustrated by means of examples.
The first part of this course treats classic asymptotic theory, including consistency and asymptotic normality results for extremum estimators. While extremum estimators include e.g., OLS, 2SLS, and Generalized Method of Moments (GMM) estimators, the exposition focuses on Maximum Likelihood (ML) estimation. Besides covering textbook examples, such as the Probit model, the course aims at providing students with the ability to model and estimate (simple) structural models using ML. In addition to standard inference methods, the course discusses bootstrap based inference.
The second part of the course treats clustering (clustered standard errors), which plays an important role in applied econometrics. After taking this course, students will be familiar with the different techniques currently available and should be able to appropriately choose among them in applications.
As part of the course, students learn to understand and use Monte Carlo simulations as a useful tool in assessing empirical/econometric methods. Homework assignments and a final project help achieving this learning goal.
Le programme détaillé n'est pas disponible.
-
Initiation/introduction
– Analyse et politique économiques
– M2/S4
Suivi et validation – semestriel hebdomadaire = 3 ECTS
MCC – examen -
Initiation/introduction
– Politiques publiques et développement
– M2/S4
Suivi et validation – semestriel hebdomadaire = 3 ECTS
MCC – examen
- Contacts additionnels
- -
- Informations pratiques
Mentions APE et PPD, secrétariat pédagogique, 48 bd Jourdan 75014 Paris, tél. : 01 80 52 19 43/44. Pour tout renseignement, veuillez écrire à master-ppd@psemail.eu
48 Boulevard Jourdan, 75014 Paris
du lundi au mardi de 15h30h à 17h30 et du jeudi au vendredi de 10h à 12h30.
Le syllabus et le planning du cours seront disponibles sur le site Internet :
- Direction de travaux des étudiants
- -
- Réception des candidats
- -
- Pré-requis
- -
-
48 bd Jourdan
48 bd Jourdan 75014 Paris
2nd semestre / hebdomadaire, vendredi 08:00-11:00
du 8 janvier 2021 au 25 juin 2021