Numerical Methods

2018-2019
This course is offered in Dutch. Some of the descriptions may therefore only be available in Dutch.

Course Objective

Acquainting the student with numerical methods and applications to
econometric problems.

Course Content

Several methods will be discussed for solving numerical problems in
econometrics. Topics include:
- floating point representation of numbers on computers
- numerical differentiation
- numerical integration: quadrature and Monte Carlo integration
- interpolation methods
- finding zeros of functions: bisection, Newton(-Raphson), Secant
methods
- univariate optimization: golden section search.
- multivariate optimization: Newton(-Raphson) and BFGS with linesearch,
Nelder-Mead. Differential Evolution.
- optimization under restrictions using transformations.
- using optimization methods to compute Maximum Likelihood estimators in
non-Gaussian/non-linear econometric models
- Power method for computing eigenvalues and eigenvectors.
- Monte Carlo simulation methods

Teaching Methods

Classes and computer practicals.

Method of Assessment

Intermediate exam – Individual assessment
Final exam – Individual assessment
Individual assignment - Groups of 1 or 2 students

Literature

Cheney & Kincaid (2012), Numerical Mathematics and Computing. 7th
edition.

Recommended background knowledge

Programming, Linear Algebra, Analysis II.

General Information

Course Code E_EOR2_NUME
Credits 6 EC
Period P1+2
Course Level 200
Language of Tuition Dutch
Faculty School of Business and Economics
Course Coordinator dr. L.F. Hoogerheide
Examiner dr. L.F. Hoogerheide
Teaching Staff dr. L.F. Hoogerheide
dr. A.A.N. Ridder

Practical Information

You need to register for this course yourself

Teaching Methods Study Group, Lecture, Computer lab
Target audiences

This course is also available as: