Econometrics 2: Multiple Regression and Applications

Econometrics 2: Multiple Regression and Applications

Year: 2018-19
Course code: ECON4004
Course credits: 15
Taught: Semester 2
Course co-ordinator: Dr Souvik Datta
Entry requirements: Normally admission to an honours programme in Economics. Econometrics 1: Introduction to Econometrics
Available to visiting students: Yes, subject to completing Econometrics 1 or a broadly equivalent course at home institution
Contact for more information: Gillian Weir

Course description

The main aim of this course is to help students develop a clear and complete understanding of various econometric techniques that should be used to analyze different economic, financial, political and social datasets. The emphasis throughout this course is on empowering the student to thoroughly understand the most fundamental econometric ideas and tools, and how this knowledge is of practical relevance to professionals in business, industry, government, and academia.  By the end of this course, students should be able to analyse actual economic data so as to produce a statistically adequate model; check the validity of the statistical assumptions underlying the model, using the sample data and revising the model specification as needed; use the model to obtain reasonably valid statistical test of economic theory – i.e. of our understanding of the economic reality generating the sample data; use the model to obtain reasonably valid confidence intervals for the key coefficients, so that the estimates can be sensibly used for policy analysis and identify, estimate and diagnostically check practical panel data and time-series forecasting models

Learning and teaching methods

20 hours of lectures (10 x 2 hours), Tuesday 14:00-16:00; 10 hours tutor-led computing sessions (5 x 2 hours).

Course texts

Stock and Watson. (2015). Introduction to Econometrics, updated 3rd Edition, Addison-Wesley (Pearson)

Assessment

A group project (30%)
A 2-hour degree exam (April/May) (70%)