ECM703-Advances in Causal Inference

Module Provider: School of Politics, Economics and International Relations
Number of credits: 20 [10 ECTS credits]
Level:7
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites: only registered PhD candidates in Economics or related disciplines
Co-requisites:
Modules excluded:
Current from: 2021/2

Module Convenor: Dr Sarah Jewell
Email: s.l.jewell@reading.ac.uk

Type of module:

Summary module description:

This module introduces research students to advanced microeconometrics techniques, focusing on methods for causal inference. Students will be expected to have a good knowledge of level 7 econometries (MSc level). The module considers how to select and apply modern and widely used microeconometric techniques for applied research. In addition, students will develop their econometric software skills using Stata – a beginner’s working knowledge of Stata will be assumed, or students will have to attain this on their own in advance (e.g., see topics 1-4 here as a public example. Other materials will be provided.

Aims:

The aim of this module is to provide students with a knowledge and understanding of microeconometrics, which will allow them to engage with the latest applied and theoretical literature. The module will teach students how to apply microeconometric techniques, using the statistical software Stata.

Assessable learning outcomes:

By the end of the module students should:

1. have the knowledge and understanding required to select and use appropriate microeconometric techniques for research;


2. have a good understanding and knowledge of causal inference;


3. be able to devise an identification strategy;


4. be able to perform their own data analysis using the statistical package Stata;


5. be able to critically evaluate methods and approaches chosen by research papers.

Additional outcomes:

Knowledge of statistical and econometric software commensurate with beginning PhD-level research.

Outline content:

Topics may include but not be exclusive to: difference-in-differences and panel data, regression discontinuity design, matching, synthetic controls, instrumental variables, quantile regression.

Global context:

Economics is global. Research students can use these methods to study any question they like.

Brief description of teaching and learning methods:

Teaching will via be a combination of pre-recorded lectures, required readings and weekly exercises before online live applied sessions

Each week there will be pre-recorded lectures to be watched in advance of online live seminars on, 90 mins, followed by a “reading group” on, 60 mins, to discuss a recent research paper.

Contact hours:

	Autumn	Spring	Summer
Lectures		20
Seminars		15
Tutorials		10
Guided independent study:
Wider reading (independent)		30
Wider reading (directed)		20
Preparation for tutorials		10
Preparation for presentations		5
Preparation for seminars		10
Preparation of practical report		5
Carry-out research project		75
Total hours by term	0	200	0
Total hours for module	200

Summative Assessment Methods:

Method	Percentage
Written assignment including essay	30
Project output other than dissertation	70

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

• Group presentation and critical review task: small groups will lead the weekly discussions on a paper applying methods related to the week’s lectures. After the discussion, the group will submit a mock referee-style report on the paper, to be graded. [weight: 30%]


• Collaborative research project: in pairs, find data and demonstrate application and understanding of the methods from the course by writing a “letter” type paper on any applied economics question (e.g., in the style of the peer-reviewed journals Economics Letters, Applied Economics Letters or Finance Research letters, i.e., around 2,000 words). [weight: 70% - submitted in May]

Formative assessment methods:

Feedback on group presentations and critical analysis of a recent contribution to causal inference.

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: http://www.reading.ac.uk/web/files/qualitysupport/penaltiesforlatesubmissionPGflexible.pdf
The Support Centres will apply the following penalties for work submitted late:

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
• where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

The University policy statement on penalties for late submission can be found at: http://www.reading.ac.uk/web/FILES/qualitysupport/penaltiesforlatesubmission.pdf
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:

50% overall, though PhD programme training normally requires 60% average over all credits to be deemed a pass before confirmation of registration.

Reassessment arrangements:

None – PhD students can retake in the following year if their learning needs analysis requires it.

Additional Costs (specified where applicable):

1) Required text books:  None

2) Specialist equipment or materials:  Access to Stata 16 through University licence

3) Specialist clothing, footwear or headgear:  None

4) Printing and binding:  None

5) Computers and devices with a particular specification:  None

6) Travel, accommodation and subsistence:  None

Last updated: 30 July 2021