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.
Unit details and rules
Academic unit | Economics |
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Credit points | 6 |
Prerequisites
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ECMT2160 or ECMT2110 |
Corequisites
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None |
Prohibitions
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None |
Assumed knowledge
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None |
Available to study abroad and exchange students | Yes |
Teaching staff
Coordinator | Peter Exterkate, peter.exterkate@sydney.edu.au |
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