SOAS University of London

Department of Economics

Applied Econometrics

Module Code:
Year of study:
Year 3
Taught in:
Full Year

This course builds technically on the second year econometrics course (15 340 0103), the prerequisite for this course. It also builds conceptually on the core courses: Macroeconomic Analysis and Microeconomic Analysis. The course is designed to provide students with a "hands-on" environment in which they learn how to apply economic theories to real economic data by means of empirical modelling search. It aims at helping students deepen and broaden their knowledge and understanding of econometric techniques needed for empirical analyses of micro and macro as well as financial data. Various topics in economics and finance are used as case studies to show students how to apply econometrics appropriately to the topics of concern. Examples of the topics are: CAPM (Capital Asset Pricing Model), production function, elasticity of demand, the Phillips curve, labour supply and hedonic price index construction. Students are expected to build up their abilities in synthesizing what they have learnt from various economics courses with data knowledge by means of statistical model learning. In addition, the course also aims to develop students' abilities in critical evaluation of what is taught in econometrics textbooks.

The course is taught in a computer lab with a two-hour interactive lecture and a one-hour tutorial per week.

Main software – PcGive, an econometrics programme in OxMetrix mainly for time-series data based modelling and STATA for cross-section data based modelling

More detailed course information is provided in the course website, which is accessible for all the registered students.

Objectives and learning outcomes of the module

The course objectives are:

  • To deepen and broaden students' knowledge and understanding of material needed for empirical quantitative analysis of micro and macro data relevant to development issues, building on the material covered in the second year intermediate econometrics course
  • To cover the theory and practice of modern econometrics at a level appropriate for an economics graduate, emphasising application
  • To teach the students the habit of thought, knowledge and understanding to be able to carry out good quality applied economic research with confidence
  • To develop the critical insight to appraise econometric results obtained by other researchers
  • The course is application oriented. Accordingly, the emphasis will be on application of techniques for policy analysis and will not be overly concerned with mathematical proofs. The course also aims to provide students with the ability to use econometric software in an effective manner
Learning Outcomes:
  • By the end of the course the students will have developed the necessary skills needed for empirical research using econometrics techniques. Through their computer based assignments they will be also trained in conducting research using secondary data. The students will also deepen their other transferable skills such as written communication, teamwork, numeracy, computer literacy, problem solving and analytical skills.

Method of assessment

Assessment weighting: (a) Course work 30% (2 essays each of 15%); (b) Tutorial participation (10%) - for weekly assigned homework tasks (5% for each term); (c) One research project with a mini viva attached (60%). All Course work is resubmittable.

Suggested reading

There are no core textbooks. Students may use their econometrics textbooks from Econometrics as the main technical manuals.

Textbook Used for Case Studies
  • E.R. Berndt, The Practice of Econometrics, Addison-Wesley, 1990
Recommended Reading
  • Peter Kennedy, A guide to Econometrics, 6E, 2008
  • Peter Swann, Putting Econometrics in Its Place, 2006
  • T. Hastie, R. Tibshirani and J Friedman, The Elements of Statistical Learning:  Datat Mining, Inference, and Prediction, 2009
  •  S.M. Stigler, The seven pillars of statistical wisdom, 2016


Important notice regarding changes to programmes and modules