Gwybodaeth Modiwlau

Module Identifier
AB33720
Module Title
Advanced Econometrics
Academic Year
2025/2026
Co-ordinator
Semester
Semester 1
Pre-Requisite
Reading List

Course Delivery

 

Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment 2 Hours   Exam  50%
Semester Assessment Project  2000 Words  50%
Supplementary Assessment 2 Hours   Supplementary Exam  50%
Supplementary Assessment Supplementary project  2000 Words  50%

Learning Outcomes

On successful completion of this module students should be able to:

Complete small scale empirical projects independently, using econometrics software such as Stata

Understand how econometric analysis is used in data science and economics

Apply appropriate econometric techniques to provide evidence for evaluation

Demonstrate knowledge of econometric approaches used in data science and economic studies

Brief description

An introduction to approaches used in advanced econometric modelling, with focus on methods and techniques when the data to be analysed are either time series, cross-sectional or a combination of both. The module builds on students’ knowledge gained in AB23420 Econometrics. Instruction in using the computer software STATA will be provided. Students will gain valuable quantitative skills useful in a broad range of careers across business and economics.

Aims

This module aims to introduce students to advanced approaches used in econometric modelling for applied research in economics and business. A secondary aim is to introduce students to using STATA as a computational package for data science analyses.

Content

Time series modelling: including ARMA, ARIMA, ARMAX
Microeconometric modelling: including limited dependent and counted variables
Repeated measures panel data modelling

Module Skills

Skills Type Skills details
Critical and analytical thinking Developed through working on individual research project
Professional communication Developed through writing project report
Subject Specific Skills Econometric methods and techniques

Notes

This module is at CQFW Level 6