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Module

ECO3008 : Advanced Econometric Analysis

  • Offered for Year: 2021/22
  • Module Leader(s): Professor Nils Braakmann
  • Owning School: Newcastle University Business School
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 10
ECTS Credits: 5.0

Aims

This module is a further investigation into econometric methods and techniques with a particular focus on techniques commonly used with micro data. It is a particularly useful module for students intending to undertake empirical analysis in their dissertations, intending to take a Masters course or for those who are considering entering into employment involving data or policy analysis.

The module deals with questions around causal inference. OLS always identifies some form of partial correlation. However, if people can self-select or if not all relevant variables are observable, these partial correlations might not have a causal interpretation. To frame our thinking, we will consider two useful frameworks to think about causality - the first is a definition of causality based on the potential outcomes framework (also called the Rubin causal model) that enables us to define the effect of a treatment on an outcome as the difference between an observed outcome and a hypothetical “counterfactual” outcome that would have prevailed had a different treatment state been realised. We will also consider a more recent approach based on graphical methods pioneered by Judea Pearl. We will then talk about estimators and research designs that allow us to infer causal relationships from observational data.

Outline Of Syllabus

(0) A brief revision of OLS (this is not formally part of the course but might be a useful refresher for the material covered in stage 2)
(1) Intuition of causal inference – why is this hard?; potential outcome framework, directed acyclical graphs
(2) Regression as a causal inference tool
(3) Fixed effects
(4) Difference-in-differences
(5) Instrumental variables
(6) Regression discontinuity designs

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Structured Guided LearningLecture materials61:006:00Recorded lecture material
Guided Independent StudyAssessment preparation and completion120:0020:00N/A
Scheduled Learning And Teaching ActivitiesLecture81:008:00Present-in-person lectures
Guided Independent StudyDirected research and reading120:0020:00N/A
Scheduled Learning And Teaching ActivitiesSmall group teaching41:004:00Seminars. PiP
Guided Independent StudyIndependent study142:0042:00N/A
Total100:00
Jointly Taught With
Code Title
ECO3019Dissertation Part 1
Teaching Rationale And Relationship

The module will run in a hybrid format as follows: We will start with a present-in-person lecture that will cover the basics of causal inference and two important frameworks – potential outcomes and directed acyclical graphs. For each further topic, there will be recorded videos going through the econometric theory. These will be broken up into chunks, i.e., you won’t have many 4-hour lecture videos to watch in one go. For each topic, there will also be a present-in-person lecture – this will usually be an application that demonstrates how to use the respective theory to answer an economic question – during these parts we will also go back to the theory. These applications are usually based on my work – not because I think these are the best papers ever written using a specific method, but because I know exactly why I did what I did for my own paper
We will also have seminars for some topics. In these, we will usually discuss two applied papers.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Essay1M1002000 word essay
Assessment Rationale And Relationship

The essay will tests students' ability to critically assess and explain the application of econometrics techniques in an applied setting.

Reading Lists

Timetable