Bayesian Econometrics (ECOM40002)

HonoursPoints: 12.5On Campus (Parkville)

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Overview

Availability
Semester 2
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The overall aim of this subject is to introduce students to the essential concepts and techniques/tools used in Bayesian inference and to apply Bayesian inference to a number of econometric models. Basic concepts and tools introduced include joint, conditional and marginal probability distributions, prior, posterior and predictive distributions, marginal likelihood and Bayes theorem. Key tools and techniques introduced include Markov chain Monte Carlo (MCMC) techniques, such as the Gibbs and Metropolis Hastings algorithms, for model estimation and model comparison and the estimation of integrals via simulation methods. Throughout the course we will implement Bayesian estimation for various models such as the traditional regression model, panel models and limited dependent variable models using the Matlab programming environment.

Intended learning outcomes

On successful completion of this subject, students should be able to:

  • Explain the concepts of joint, conditional and marginal probability density functions and their relevance for Bayesian inference;
  • Derive posterior density functions for common econometric models including the traditional regression model, discrete outcome models and panel models;
  • Explain the relevance of Markov chain Monte Carlo techniques for Bayesian inference;
  • Program Gibbs samplers and Metropolis-Hastings algorithms for a number of models including the traditional regression model, discrete outcome and panel models;
  • Interpret results from Bayesian inference;
  • Estimate marginal likelihoods for model comparison.

Generic skills

On successful completion of this subject, students should have improved the following generic skills:

  • High level of development: evaluation of data and other information; synthesis of data and other information; critical thinking; interpretation and analysis; use of computer software; statistical reasoning; problem solving; collaborative learning; written communication; oral communication.
  • Moderate level of development: receptiveness to alternative ideas; application of theory to practice.
  • Some level of development: accessing data and other information from a range of sources.

Last updated: 8 November 2024

Eligibility and requirements

Prerequisites

Admission into or selection of one of the following:

  • BH-COM Bachelor of Commerce (Degree with Honours)
  • Economics specialisation (formal) in the BH-ARTS Bachelor of Arts (Degree with Honours)

AND

Code Name Teaching period Credit Points
ECOM40006 Econometrics 3
Semester 1 (On Campus - Parkville)
 12.5

Corequisites

None

Non-allowed subjects

Code Name Teaching period Credit Points
ECOM90010 Bayesian Econometrics
Semester 2 (On Campus - Parkville)
 12.5

Recommended background knowledge

Please refer to Prerequisites and Corequisites.

Inherent requirements (core participation requirements)

The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.

Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home

Last updated: 8 November 2024

Assessment

DescriptionTimingPercentage

Assignment 1 (computer exercises and problem set)

  • 1000 words (total)
Week 620%

Assignment 2 (computer exercises and problem set)

  • 1000 words (total)
Week 1220%

End-of-semester Examination

  • 2 hours
During the examination period60%

Last updated: 8 November 2024

Dates & times

  • Semester 2
    Principal coordinatorLiana Jacobi
    Mode of deliveryOn Campus (Parkville)
    Contact hoursTwo 1.5-hour lectures per week
    Total time commitment170 hours
    Teaching period22 July 2024 to 20 October 2024
    Last self-enrol date 2 August 2024
    Census date 2 September 2024
    Last date to withdraw without fail20 September 2024
    Assessment period ends15 November 2024

    Semester 2 contact information

    Liana Jacobi: ljacobi@unimelb.edu.au

Time commitment details

170 Hours

What do these dates mean

Visit this webpage to find out about these key dates, including how they impact on:

  • Your tuition fees, academic transcript and statements.
  • And for Commonwealth Supported students, your:
       -  Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
     

    Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.

Last updated: 8 November 2024

Further information

  • Texts

    Prescribed texts

    You will be advised of prescribed texts by your lecturer.

  • Available to Study Abroad and/or Study Exchange Students

    This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.

Last updated: 8 November 2024