EC205-Intermediate Econometrics

Module Provider: School of Politics, Economics and International Relations
Number of credits: 20 [10 ECTS credits]
Terms in which taught: Spring term module
Non-modular pre-requisites:
Co-requisites: EC204 Introductory Econometrics or EC204NU Introductory Econometrics
Modules excluded: EC207 Empirical Methods for Economics and Social Sciences
Current from: 2023/4

Module Convenor: Dr Shixuan Wang

Type of module:

Summary module description:

This module complements EC204 Introductory Econometrics and will provide foundations for econometrics and other modules at part three. It will explore more deeply the ordinary least squares (OLS) estimator and its properties, hypothesis testing, study departures from the standard assumptions, aspects of model specification, and will further develop data analytical skills in R.


To provide a deeper understanding of the OLS regression and the underlying assumptions, including proofs and derivations of the estimator’s statistical properties; to develop an understanding of how to go about making model specification choices as an applied econometrician; to understand some alternative estimators and when these could be appropriate to model relationships between variables; to further develop statistical software, programming, and data handling skills.

Assessable learning outcomes:

At the end of the module students should be able to:

  • Derive the OLS estimator and prove its statistical properties.

  • Understand departures form the OLS assumptions and the consequences when data and models are not consistent with them.

  • Understand more deeply hypothesis testing, estimation methods, and aspects of model specification.

  • Understand some alternatives to OLS.

  • Undertake econometric tasks using computer software. 

Additional outcomes:

Greater familiarity with econometric software, programming, and the processes involved in handling data and preparing them for analysis.

Outline content:

The module may cover the following topics: simple linear regression, multiple linear regression with matrix algebra, and the Gauss Markov Theorem, statistical inference with OLS, heteroskedasticity, model specification testing, endogeneity and instrumental variables, qualitative independent variables, and limited dependent variables.

Brief description of teaching and learning methods:

Lectures, seminars, and computer classes; supported by independent study.

Contact hours:
  Autumn Spring Summer
Lectures 20 2
Practicals classes and workshops 8
Guided independent study: 131 39
Total hours by term 0 159 41
Total hours for module 200

Summative Assessment Methods:
Method Percentage
Written exam 60
Set exercise 40

Summative assessment- Examinations:

One 3-hour unseen written paper.

Part 2 examinations are held in the Summer term.

The examination for this module will require a narrowly defined time window and is likely to be held in a dedicated exam venue.

Summative assessment- Coursework and in-class tests:

There will be one course project, which will test applications of the econometric theory, as well as data handling and statistical software skills.

Formative assessment methods:

Econometric applications in R during the computer workshops.

Penalties for late submission:

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:
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:
A minimum overall mark of 40%.

Reassessment arrangements:

Re-assessment for all modules takes place in August/September of the same year.

Re-assessment is by examination only; coursework is not included at the second attempt.

Additional Costs (specified where applicable):

7th Edition, ISBN-13: 9781337558860, ISBN: 1337558869, Authors: Jeffrey M. Wooldridge

2) Specialist equipment or materials:  Students will need to use Stata (statistical software), available under licence from the University’s applications catalogue.

3) Specialist clothing, footwear or headgear:  None

4) Printing and binding:  There may be optional costs associated with photocopying or printing sources listed on the reading list relating to this module. Please note that the Library charges approximately 5p per photocopy.

5) Computers and devices with a particular specification:  None

6) Travel, accommodation and subsistence:  None

Last updated: 30 March 2023


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