This module aims to:

Equip students with the tools necessary for state-of-the-art empirical research with economic time series data (macro-economics, finance, marketing, accounting etc.)

Lay out the econometric theory of time series analysis.

Inspire and motivate students by discussing recent research in this field.

(LO1) Students will be able to build theoretical models to approach research questions.

(LO2) Students will be able to numerically compute simple models.

(LO3) Students will be able to demonstrate advanced understanding of the links between economic theory and macroeconometric models.

(LO4) Students will be able to demonstrate a critical awareness of the latest approaches to macroeconometrics modelling.

(LO5) Students will be able to establish a suitable macroeconometric model for a specific question.

(LO6) Students will be able to critically evaluate research papers in macroeconometrics.

(LO7) Students will be able to demonstrate a critical awareness of recent empirical approaches in macroeconometrics.

(S1) Organisation skills
This applies to all modules of the programme and is relevant for planning scheduled work and meeting assessment deadlines. This will be evident in the students’ independent management of their assignments and coursework and by meeting coursework deadlines.

(S2) Problem solving and decision making skills
Students will be challenged to think critically about macroeconomic models. They will do this by gathering and synthesising information, analysing alternative perspectives and options and presenting a considered opinion or course of action in their course assessment.

(S3) Digital skills
Students will develop IT skills through learning programming of macroeconometrics techniques such as estimation, inference, etc.

(S4) Numeracy
Students will develop numeracy through computation in the project.

(S5) Communication skills
Students will develop written and oral skills through the assessment aspect of the module.

(S6) Ethical awareness
Students will enhance their ethical awareness by reflecting how research including their own is consistent with the principles of research ethics, integrity and open science and learning how to resolve issues and navigate challenges through in class work.

(S7) International awareness
International issues will be covered in class work.

Lectures x 18 hours (90 minutes per week)

During the lectures, the instructor will cover some of the topics listed in the syllabus. But students will also be required to read published papers and working papers and will present a paper of their choice. This will form part of the module's assessment.

Self-directed learning x 182 hours
Students should make use of their self-directed learning time to read the module textbooks and journal articles, and reflect about the implications for their own research.

Indicative Syllabus:

Univariate time series models;

Non-stationary linear models;

Stationary multivariate time series models;

Non-Stationary multivariate models;

A selection of further topics (this will be specified at the start of the module), which might include some recent development on Granger causality analysis and quantile regression analysis.