Teaching

This course offers an introduction to current economic issues and to the fundamental principles and methods of macroeconomics. As macroeconomics is the study of the economy as a whole, we begin with three key macroeconomic variables: GDP, inflation, and unemployment. We then explore topics such as economic growth, financial markets, business cycles, and the role of government through monetary and fiscal policy. Along the way, we also discuss interest rates, investment, exchange rates, and international trade.

I am a Teaching Fellow for this course. My role is to lead discussion sections, review and clarify material presented in lectures, work through example problems, and help students prepare effectively for exams.

1. Algebra [Syllabus]

The aim of this course is to provide students with a solid grounding in algebra and to introduce them, where appropriate, to its applications in the field of economics. Themes covered include the foundations of set theory; the basic objects of algebra; vector spaces; linear applications; the matrix and Hermitian forms in particular. The course emphasizes on analytical rigor in the understanding, presentation and writing of mathematical concepts.

2. Analysis [Syllabus]

This course provides an introduction to real analysis and its applications in economics. The course covers the following topics: limits and continuity in topological spaces; functions and differential calculus; construction of the Riemann-Stieltjes integral; measure theory and Lebesgue integration. Emphasis is placed on careful training in proof writing and a deep understanding of the mathematical objects used in analysis.

• Chapter 1 : Introduction [Slides ]

• Chapter 2 : Policy coordination[Slides ]

• Chapter3a : Expectations and policy [Slides ]

• Chapter3b : Rational expectations and Lucas' Critique [Slides ]

• Chapter 4 :Time inconsistency [Slides ]

• Chapter 5 : Market, Price and Equilibrium[Slides]

• Chapter 6 : Introduction to RBC model[Slides][Matlab/Dynare codes]

• Chapter 1 : Logic and proofs [Slides ]

• Chapter 2 : Set theory[Slides] and Algebra structures [Slides]

• Chapter 3 : Optimization without constraint [Slides]

• Chapter 4 : Optimization with constraints [Slides]

• Chapter 5 : Introduction to dynamic optimization[Slides]

[Syllabus] [Lecture notes ]

• Chapitre 1 : Modèle de régression linéaire classique  

• Chapitre 2 : Propriété sur échantillons finis 

• Chapitre 3 : Distribution sur grands échantillons

• Chapitre 4 : Économétrie des anticipations rationnelles

• Chapitre 5 : Méthodes des moments généralisés

• Chapter 1 : Set theory

• Chapter 2 : Introduction to measure theory

• Chapter 3 : Measurable function 

• Chapter 4 :  Random variables and random vectors

• Chapter 5 : Characteristic function

• Chapter 6 : Convergence 

• Chapter 7 : Conditional Expectation and stochastic process

1. Les mathématiques du leadership : théorème d'exemplarité [slides , based on Hermalin(1998)]

2. Mathematics of leadership : Why vision matters   [Slides ]