Monte Carlo Simulation:
Methods and Design
The purpose of this course is to provide students with an introduction to Monte Carlo methods as used in econometrics. Most research papers use Monte Carlo, and we aim to understand its use and limitations. We use the Oxlanguage to understand and create Monte Carlo experiments. Ox is an object-oriented matrix programming language with a mathematical and statistical function library, developed by Dr Jurgen Doornik and widely used in different econometrics specialisations.
This module can be taken on its own for a PG Certificate of achievement as part of a PG Certificate, PG Diploma or Full Masters Program.
By the end of this course, participants should have knowledge and ability to:
Basic pseudo random number generation, and how to sample from statistical distributions.
Basic principles of numerical computation.
Uses, limitations and statistical properties of Monte Carlo experiments.
Using PcNaive to design experiments for Econometrics, and understanding the output from PcNaive.
By the end of this course, students should be able to:
Interpret Monte Carlo results.
Implement basic experiments in the Ox language, and use parallelization effectively.
Understand basic principles and limitationsof the bootstrap.
Present, interpret and analyse information in numerical form.
Understand some of the basic principles of Monte Carlo estimation.
Monte Carlo Simulation: Methods and Design is an elective 10 credit course and therefore students are expected to input approximately 100 hours of study into the course.
The total number of contact hours is 15 hours. This leaves 85 hours for private study.
This module consists of 2- hour lectures per day for 5 days, plus a 1 - hour tutorial per day.
There will be optional clinics on the last day of the course.
The dates of each lecture are confirmed closer to the start of each term. If you have any questions about dates, please contact email@example.com.