TOPICS IN MACROECONOMETRICS - 2020/1

Module code: ECOD025

Module Overview

The module covers a range of econometric tools that are typically employed in empirical work in macroeconomics.

Module provider

Economics

Module Leader

GABRIEL Vasco (Economics)

Number of Credits: 0

ECTS Credits: 0

Framework: FHEQ Level 8

JACs code: L100

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

Module Availability

Semester 1

Prerequisites / Co-requisites

None

Module content

Indicative content includes:

- State Space Models and Kalman Filtering
- (Dynamic) Factor models
- VAR models and extensions
- Nonlinear methods for IRFs
- GMM
- Simulated Methods of Moments
- Bayesian Methods
- Macro Panels

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Problem sets 30
Coursework Take-home assignment 70

Alternative Assessment

N/A

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate their technical skills relating to the use of the relevant econometrics techniques to carry out innovative empirical work.

Thus, the summative assessment for this module consists of:
• 2 Problem sets worth 30% of the final mark.
• A take-home assignment involving the implementation of one of the methods covered in the module, worth 70% of the final mark.

Formative assessment
Students will be supported formatively through interactive teaching, informal discussion, mini coding workshops and office hours.

Feedback
Written and oral feedback will be provided on the pieces of assessment. Office hours are devoted to more targeted, individually based feedback on specific problems.

Module aims

  • to provide students with a strong foundation on theoretical macroeconometrics and its applications
  • to enable students to conduct independent research in macroeconometrics/empirical macroeconomics

Learning outcomes

Attributes Developed Ref
001 To demonstrate advanced understanding and be able to critically evaluate of the main methods used in empirical macroeconomics CKPT
002 To engage in innovative research in macroeconometrics CKPT
003 To be able to independently implement, using appropriate software (e.g. Matlab), and apply the techniques learned to real data, and intepret the results CPT
004 To be able to present critical analysis at the appropriate level CPT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Overall student workload

Independent Study Hours: 117

Lecture Hours: 22

Tutorial Hours: 11

Methods of Teaching / Learning

The learning and teaching strategy is designed to:
• Provide research-led teaching that gives students a deep understanding of the theoretical econometric issues, enables them to implement the techniques and allows students to consider possible methodological contributions.

The learning and teaching methods include:
• 11 taught lectures, which will include the presentation of technical material and interaction with students

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

Reading list for TOPICS IN MACROECONOMETRICS : http://aspire.surrey.ac.uk/modules/ecod025

Other information

N/A

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Economics PHD 1 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 2020/1 academic year.