LMD academic program

Master’s degree (1st year) Econometrics and Statistics

Master’s degree (1st year) Econometrics and Statistics

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Details

General information

Available to
  • Initial course
  • Resumption of training

International

*
* English

Introduction

Objectives

The 1st  year of the Master 1 in Econometrics and statistics provides rigorous training in the major fields of economics. 100% of courses of this program are taught in English. The objectives of this 1st year is to enhance the students’ general economics culture and to prepare them for more quantitatively oriented classes.

The program also includes: 

  • Individual tutoring hours in «  econometrics », « Applied econometrics » and « Intro to SAS, R and Python »
  • Employment coaching sessions in English

Specificities

For further information, refer to the TSE website.

Institution

Person in charge of the academic program


Toulouse School of Economics
Bureau des Masters TSE
Bâtiment A -1er étage - MA 106
Manufacture des Tabacs
31015 Toulouse Cedex 6
France
Phone : + (33) (0)5 67 73 27 87
E-mail : TSE-studentsrecruitment@ut-capitole.fr
Site : http://tse-fr.eu/en


Admission

Prerequisite

Prerequisites for enrolment

Bac + 4

Application

Conditions of admission / Conditions of successful application

  • Aimed at non French speaking international students
  • Students should hold a BA or BSc in Economics, Applied Mathematics within a recognized curriculum considered as consistent with the program and approved by the TSE selection committee.
  • For more details about application process, click here
Admission :TSE recruitment
Director of the program: Christine Thomas

Program

1. Decisions Mathematics Path

SEMESTER 1

Compulsory courses:
  • Macroeconomics
  • Intermediate econometrics 
  • Mathematical Statistics 1 
  • Strategic Optimization
  • Advanced Analysis 
  • Markov chains and applications
  • Optimization
  • Professional Development
Optional:
  • Algebra refresher *
  • Probability refresher *
  • Static Optimization refresher *
* Maths Camp for M1 and M2 ( end of august)

SEMESTRE 2

Compulsory courses :
  • Program Evaluation 
  • Games and Equilibria
  • Mathematical Statistics 2 
  • Optimization for big data
  • Martingales theory and applications
  • Advanced Macroeconomics
  • Advanced Microeconomics
  • Data bases

Internship or master thesis


2. Statistics and Applied econometrics Path

SEMESTER 1

Compulsory courses:
  • Applied econometrics 
  • Intermediate econometrics 
  • Statistical Softwares (SAS, R, Python) OR Macroeconomics
  • Mathematical Statistic 1 
  • Game Theory 
  • Professional Development
2 electives from:
  • Environmental economics
  • Development economics
  • Markov chain and applications
  • Probability Modelling
  • Evolution of economic behaviour
  • Understanding real world Organizations
  • Project management

Optional:
  • Algebra refresher *
  • Probability refresher *
  • Optimization refresher *

SEMESTER 2

Compulsory courses:
  • Program Evaluation
  • Applied econometrics
  • Mathematical Statistic 2
4 electives from:
  • Industrial Organization ** 
  • Corporate finance ** 
  • North-South Economic Relations ** 
  • Environmental & Resource Economics **
  • Market finance** 
  • Dynamic Optimization
  • Time series ** 
  • Introduction to big data ** (limited numbers of students)
  • Martingales theory and application ***
  • Data Bases **
  • Advanced Macroeconomics ** 
  • Advanced Microeconomics **
  • Optimization for big data ** (limited numbers of students)

Internship or master thesis

* Maths Camp for M1 and M2 (end of august)
** Highly suggested by a M2 director (see M1 brochure for more details)
*** Student must have followed the course "Markov chains"

What's next ?

Level of education obtained after completion

Year of highschool graduation

Unknown label

Submission

Tuition

5 500 euros/year (these fees can be paid in three installments) + registration fees (256€) and social security (215€) Finacial aids: Some Master scholarships and fee waivers will be awarded to Master students according to academic, geographical or individual criteria.