Module code: ECOD001

Module Overview

This course gives the students a systematic way of thinking about macroeconomic issues. The course will present the methodology and tools to study dynamic macroeconomic problems and will cover a broad range of macroeconomic theories of business cycle.

Module provider


Module Leader

CANTORE Cristiano (Economics)

Number of Credits: 0

ECTS Credits: 0

Framework: FHEQ Level 8

JACs code: L130

Module cap (Maximum number of students): N/A

Module Availability

Semester 1

Prerequisites / Co-requisites


Module content

Indicative content includes:

  • Deterministic Difference Equations

  • Stochastic Difference Equations

  • Introduction to Matlab and programming in Dynare

  • Neoclassical Growth Models and different market structures

  • Real Business Cycle theory

  • Fiscal Policy

  • The New Keynerian Model: Sticky Prices and Sticky Wages

  • Medium Scale DSGE Models

  • Dynamic Programming

  • LQ model and Optimal Policy

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework COURSEWORK 30

Alternative Assessment


Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate their technical skills relating to, and understanding of, economic problems involving game theory.


Thus, the summative assessment for this module consists of:

  • A three-hour exam worth 70% of the final mark.

  • Problem sets worth 30% of the final mark typically submitted in week 5, 6, 9 and 11.


Formative assessment

Due to the limited size of the cohort and the level of study, formal formative assessment is being replaced with informal discussions during and outside of lectures.


Students will receive verbal feedback during the lectures through direct interaction. Moreover, they will receive their problems sets back with written comments.

Module aims

  • Provide students with a thorough understanding of key macroeconomics models, concepts and results.
  • Enable students to prepare for research in this field
  • Enable students to develop the skills to work independently.

Learning outcomes

Attributes Developed
001 Understand and apply linear state-space time series analysis to macroeconomics data. KC
002 Understand and apply basic dynamic programming KCT
003 Understand how to build up economic models based on rational inter-temporal optimizing behaviour of all agents KCPT
004 Solve and simulate DSGE models, and use them for policy analysis KCPT
005 Read, interpret and critically discuss the advanced, state-of-the-art papers and books related to the material covered KT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Overall student workload

Independent Study Hours: 123

Lecture Hours: 27

Methods of Teaching / Learning

The learning and teaching strategy is designed to: develop students’ independent research skills, by training them to do critical analysis of papers in scientific journals and do many problem sets, making sure concepts and methods are mastered.


The learning and teaching methods include:

Interactive lectures and discussion of cases within these.

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


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.