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Unit of study_

Computational Econometrics - ECMT3170

Year - 2020

This unit provides an introduction to modern computationally intensive algorithms, their implementation and application for carrying out statistical inference on econometric models. Students will learn modern programming techniques such as Monte Carlo simulation and parallel computing to solve econometric problems. The computational methods of inference include Bayesian approach, bootstrapping and other iterative algorithms for estimation of parameters in complex econometric models. Meanwhile, students will be able to acquire at least one statistical programming language.

1x2hr lecture/week, 1x1hr computer laboratory/week

1x2hr Final Exam (50%), 1x1500wd Computer Project (30%), 2x500wd Computer Assignment (20%)


ECMT2160 or ECMT2110


Faculty: Arts and Social Sciences

Semester 1

24 Feb 2020

Department/School: Economics
Study Mode: Normal (lecture/lab/tutorial) day
Census Date: 31 Mar 2020
Unit of study level: Senior
Credit points: 6.0
EFTSL: 0.125
Available for study abroad and exchange: Yes
Faculty/department permission required? No
Courses that offer this unit

Non-award/non-degree study If you wish to undertake one or more units of study (subjects) for your own interest but not towards a degree, you may enrol in single units as a non-award student. Cross-institutional study If you are from another Australian tertiary institution you may be permitted to undertake cross-institutional study in one or more units of study at the University of Sydney.

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