Modelling the Australian Macroeconomy (ECOM90012)

Graduate courseworkPoints: 12.5Not available in 2025

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Overview

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The aim of this subject is to provide students with a solid grounding in modern applied macroeconomic modelling. There are two components to the course. The first is theoretically orientated and builds on New Keynesian Dynamic Stochastic General Equilibrium (DSGE) models used to analyse the business cycle effects of macroeconomic policies. The second component is empirical. It will focus on the estimation of DSGE and the estimation and identification of Structural Vector Auto-Regressions (SVARs). Attention will be devoted to core components of a closed-economy frameworks as well as small-open economy models. Applications to Australia will be discussed. This subject also provides students with the experience of carrying out a research-based project on a specific topic in applied econometrics.

Intended learning outcomes

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

  • Specify and estimate VAR/SVAR models
  • Generate and understand impulse response functions and forecast error variance decompositions
  • Understand alternative identification strategies and apply them to identify monetary policy shocks, fiscal shocks, and technology shocks
  • Specify a basic New Keynesian model; generalise it for a small open economy as well as other commonly included extensions in empirical applications
  • Apply econometrics methods (Generalized Method of Moments and the Kalman filter) commonly used to estimate DSGE models
  • Analyse policies by simulating DSGE models
  • Understand the relevance of optimal and unconventional policies
  • Evaluate recent central bank and academic research using VAR/SVAR and small-open economy DSGE models
  • Orally present the results of an independent piece of research
  • Complete a written research report

Generic skills

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

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

Last updated: 4 March 2025