ADVANCED MACROECONOMICS - 2022/3
Module code: ECOM047
This module builds on the techniques for dynamic optimization developed in ECOM021 and taken together, the two courses provide a rigorous introduction to modern macroeconomic modelling. ECOM047 focuses on model construction, simulation and policy analysis. The general approach to macro-economic modelling is to derive all decisions of economic agents from micro-foundations in a rational expectations, dynamic and stochastic setting. Taken together with market clearing, the models studied are then of the DSGE (dynamic stochastic general equilibrium) genre that form the basis of macroeconomic modelling that is common in central banks and finance ministries.
The Course will study the construction of a rich New Keynesian model in steps, progressing in stages from simpler set-ups. The use of Software packages Matlab and Dynare will be taught to carry out the numerical solution and simulation of the models. The ultimate aim is to use such models to first, understand the volatility, co-movement and persistence seen in macroeconomic data and second, understand their implications for monetary and fiscal policy
Other parts of the Course will include a surveys of systems estimation methods and 'behavioural' alternatives to rational expectations where agents learn about the model, in an otherwise DSGE framework.
LEVINE Paul (Economics)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
JACs code: L130
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 79
Lecture Hours: 22
Tutorial Hours: 5
Guided Learning: 22
Captured Content: 22
Prerequisites / Co-requisites
Indicative content includes:
- Overview of recent developments in macroeconomic modelling
- Foundations of dynamic stochastic general equilibrium models (DSGE) models
- The Basics of Matlab and Dynare
- Construction of the Real Business Cycle (RBC) model
- Construction of The New Keynesian (NK) model with an RBC Core
- Calibration of DSGE Models
- A tractable three-equation linearized NK model.
- A survey of systems estimation methods for DSGE models
- A survey of alternatives to, and current developments of DSGE models
|Assessment type||Unit of assessment||Weighting|
|Coursework||COURSEWORK (COMPUTATIONS AND ESSAY)||30|
|Examination Online||FINAL EXAMINATION||70|
The assessment strategy is designed to provide students with the opportunity to demonstrate that they have achieved the module’s learning outcomes and, by association, developed their digital capabilities and employability, among other module attributes.
Thus, the summative assessment for this module consists of:
- A take-home coursework project consisting of an essay and modelling exercise connected to learning outcomes 1, 2 and 4
- A final exam, which is connected to all learning outcomes
Formative Assessment and Feedback
Students receive verbal feedback on their answers to questions during the lectures. They are also encouraged to attend the designated student consultation hours so that they can receive further verbal feedback on their understanding and progress.
- Apply key microeconomic mathematical techniques in a macroeconomic context
- Explain and discuss the construction and estimation of DSGE models
- Apply these models to macroeconomics problems
- Introduce some of the strengths and weaknesses of DSGE modelling
- Enable the students to follow the relevant literature
|001||Achieve a systematic understanding of the mathematical techniques used to construct and estimate DSGE models||KCPT|
|002||Demonstrate originality in the use of DSGE models to address macroeconomic policy problems||KCPT|
|003||Show critical awareness of the strengths and weaknesses of DSGE modelling, and the direction in which they are developing||KCPT|
|004||Show conceptual understanding of the literature in macroeconomics using DSGE models||KCPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The learning and teaching strategy is designed to combine lectures on theory with practical hand-on lab sessions running the models in Dynare.
The learning and teaching methods are as follows:
- Lectures, which are recorded and disseminated as captured content
- Guided learning
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: ECOM047
In line with the University's curriculum framework, the School of Economics is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities in the following areas:
Students in this module will learn how to use software packages Matlab and Dynare to carry out numerical solution and simulation of DSGE models.
This module will provide students with skills for placement at Central Banks, Investment Banks and Academia. The material covers research methods at the frontier of macroeconomic policy. Lecture and class sessions are designed to go over practical exercises and provide students with the opportunity to apply their knowledge to real-life examples used in the sector.
Programmes this module appears in
|Economics MSc||2||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
|Economics (International Economics) MSc||2||Optional||A weighted aggregate mark of 50% is required to pass the module|
|Economics (Macroeconomics and Financial Markets) MSc||2||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.