ECM607CNU-Macroeconometrics

Module Provider: School of Politics, Economics and International Relations
Number of credits: 10 [5 ECTS credits]
Level:7
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2021/2

Module Convenor: Dr Shixuan Wang
Email: shixuan.wang@reading.ac.uk

Type of module:

Summary module description:

NUIST Module Lead:ÌýÌýDr.ÌýWuÌýZhenyong, Email: wuzhy1983@163.com

This module is intended to teach students more advanced macroeconometrics, which focuses time series econometrics with macroeconomic applications. The module considers how to select and apply the most appropriate time series econometrics for a given economic dataset. In addition students will develop their econometric software skills using R.

Aims:

The aim of this module is to provide students with a more extensive knowledge and understanding of macroeconometrics, especially applying the techniques for research. Additionally, the module will teach students how to implement these econometric techniques, using R.

Assessable learning outcomes:

By the end of the course students should be able to:

• Understand the need and the nature of time series econometrics.


• Implement time series econometric methods using R.


• Read academic papers in macroeconometrics and understand the suitability of the methods employed.

Additional outcomes:

Students will develop their research and data handling skills, and be able to critically evaluate methods and approaches chosen by research papers.

Outline content:

Topics may include autoregressive moving-average models, unit root/stationarity tests, model selection and diagnostics, forecasting, and cointegration.

Brief description of teaching and learning methods:

Teaching will be a combination of lectures and computer classes.

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

There will be one course project in which students will implement a set of econometric tasks by using R and produce a report.

Formative assessment methods:

There will be computer exercises for each topic, which will be discussed during the lectures and workshops.

Penalties for late submission:

The below information applies to students on taught programmes except those on Postgraduate Flexible programmes. Penalties for late submission, and the associated procedures, which apply to Postgraduate Flexible programmes are specified in the policy 􀀓Penalties for late submission for Postgraduate Flexible programmes􀀔, which can be found here: