Module description
What is the module about?
This module introduces students to the main techniques that economists use for estimating economic relationships, testing economic theories and evaluating government and business policies. It builds on material covered in first year core modules: 4SSMN901 Mathematics for Economists and 4SSMN902 Statistics for Economists, though only the latter is required (or 4QQMN503 Mathematics and Statistics for Accounting and Finance).
We cover the fundamentals of linear regression analysis as well as more advanced topics related to estimation and inference for probability models, panel and time series data. Throughout the module, we study examples based on real data and published research. In class, we do some number crunching ourselves using Stata, a fast and versatile software for quantitative research and we will have 5 workshops throughout the Semester in addition to tutorials and lectures.
Our ultimate goal in this module is to learn how to use data to answer causal if-then questions, i.e. to make predictions under plausible assumptions, consistent with the available evidence.
Who should do this module?
This module is available to students in the Business School and students on the BSc Economics programme. It should be of interest to students who want a deeper understanding of quantitative methods.
Provisional Lecture Outline
Lecture 1: Introduction to linear regression
Lecture 2: Simple linear regression I: Assumptions and Estimation
Lecture 3: Simple linear regression II: Interpretation and Inference
Lecture 4: Multiple regression I: Omitted variable bias, inference, interpretation.
Lecture 5: Multiple regression II: Non-linear functions
Lecture 6: Multiple regression III: further topics
Lecture 7: Instrumental Variables
Lecture 8: Models for panel data
Lecture 9: Probability models
Lecture 10: Applications: prediction with many regressors and Big Data
Assessment details
80% Examination
20% Individual Coursework
The format of the examination has not yet been confirmed. All students will be expected to sit any remote exams in January, but semester 1 only students will be set an alternative assessment or sit the exam remotely in lieu of any in-person exams.
Teaching pattern
Fortnightly Workshops
Weekly Tutorial
Suggested reading list
Key text or background reading
J.H. Stock and M.W. Watson, Introduction to Econometrics, 4th edition, Pearson 2020