Numerical Methods


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
- 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

Assignment - Groups of 3-4 students


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

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 English
Faculty School of Business and Economics
Course Coordinator dr. C.S. Bos
Examiner dr. C.S. Bos
Teaching Staff dr. A.A.N. Ridder

Practical Information

You need to register for this course yourself

Teaching Methods Study Group, Lecture, Computer lab
Target audiences

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