**Aims of the course: **

The course focuses on supplying students with more advanced tools of economic analysis, while aiming at practical usefulness rather than theoretical robustness.

**Language: **English

**Course contents: **

Lesson 1: Linear programming (objective function, constraints, feasible region, optimal solution)

Lesson 2: Matrix algebra I (vectors, matrices, transpose matrix, addition and multiplication of matrices, determinant, Cramer’s rule)

Lesson 3: Matrix algebra II (SSR, OLS)

Lesson 4: Matrix algebra III (quadratic forms, eigenvalues and eigenvectors, definiteness of matrices)

Lesson 5: Differentiation (partial derivative, Taylor series, Jacobian matrix, Hessian matrix)

Lesson 6: Unconstrained optimization (first order conditions, second order conditions)

Lesson 7: Constrained optimization (Lagrange function, nonlinear programming, Kuhn-Tucker first order conditions)

Lesson 8: Linear difference equations (characteristic equation, stability, cobweb model, Markov system)

Lesson 9: Differential equations (separable differential equations, homogeneous and non-homogeneous linear differential equations)

Lesson 10: Dynamic analysis – continuous time (proper and improper integrals, Euler equation, Hamiltonian, necessary and sufficient conditions

**Class times: **

- October 11, 16:15-19:30 – classroom NB 472
- October 18, 16:15-19:30 – classroom NB 472
- October 25, 16:15-19:30 – classroom SB 327
- November 1, 16:15-19:30 – classroom NB 472
- November 8, 16:15-19:30 – classroom NB 472
- November 15, 16:15-19:30 – classroom NB 472

**Date of Exam**: to be agreed upon.

**Instructor**: Taghi Ghadiri Abkenar, MSc.