ADVANCED MACROECONOMICS - 2019/0
Module code: ECOM047
Module Overview
The module approaches macro-economic modelling from micro-foundations. It aims to introduce dynamic stochastic general equilibrium (DSGE) modelling along with related numerical applications. At every stage, the theories will be illustrated in the context of some macroeconomic application.
Module provider
Economics
Module Leader
LEVINE Paul (Economics)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 128
Lecture Hours: 17
Laboratory Hours: 5
Module Availability
Semester 2
Prerequisites / Co-requisites
None
Module content
Indicative content includes:
- Overview of modern macroeconomic theory
- Foundations of dynamic stochastic general equilibrium (DSGE) models
- Applications of dynamic optimisation
- Basics of Dynare and Matlab
- The Real Business Cycle model
- New Keynesian theory
- Bayesian Estimation
- Monetary policy
- Alternatives to and developments of DSGE models
Assessment pattern
| Assessment type | Unit of assessment | Weighting |
|---|---|---|
| Coursework | COURSEWORK - WRITTEN ASSIGNMENT COMBINING COMPUTATION AND 1500 WORD ESSAY | 30 |
| Examination | EXAMINATION - 2 HOURS | 70 |
Alternative Assessment
Not applicable.
Assessment Strategy
The assessment strategy is designed to provide students with the opportunity to demonstrate
Learning outcomes above
Thus, the summative assessment for this module consists of:
- A practical computing and essay assignment due typically in Week 8
2 hour examination with essay-style exam questions, scheduled in Weeks 13-15.
Formative assessment and feedback
Individual comments on scripts together with a common set of solutions and general comments
Module aims
- 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
Learning outcomes
| Attributes Developed | ||
| 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 |
Attributes Developed
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 include:
- 2 hour lectures/lab sessions combined per week x 11 weeks
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.
Reading list
https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: ECOM047
Programmes this module appears in
| Programme | Semester | Classification | Qualifying conditions |
|---|---|---|---|
| Economics 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 2019/0 academic year.