TOPICS IN MACROECONOMETRICS - 2023/4

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

VOLPICELLA Alessio (Economics)

Number of Credits: 0

ECTS Credits: 0

Framework: FHEQ Level 8

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

Overall student workload

Workshop Hours: 8

Independent Learning Hours: 133

Guided Learning: 6

Captured Content: 3

Module Availability

Semester 1

Prerequisites / Co-requisites

None

Module content

Indicative content includes: -Maximum Likelihood and State-Space Models -Bayesian Econometrics -GMM, Simulated Method of Moments, Indirect Inference -Structural Vector Autoregressions: Identification, Estimation and Inference -Local Projections -Nonlinear Methods

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Take-Home Assignment 100

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 a mix of problem sets, presentations, papers replication, and referee reports.
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.

Extracts from the coursework may eventually be used in the students’ PhD dissertation, and that will not constitute self-plagiarism.

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
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

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

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: 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 2023/4 academic year.