ME307 Intermediate Econometrics

The 2016 Methods Summer Programme is now closed. 
Details for 2017 programme will be available soon.

The typical introductory econometrics course is mostly confined to the Classical Linear Regression Model. It may also cover a few advanced topics, but with eclectic choice and superficial treatment. This course aims to build a solid, comprehensive understanding of the use of the regression model when one progresses from the CLRM, with its strong and unrealistic assumptions, and addresses the issues that researchers encounter in practice.

This course is designed for those who have already taken an introductory course covering the CLRM and need to develop their skills to the next level. The course is not suitable for those whose only exposure to econometrics has been as part of a statistics course.

Course benefits
Students will have an advanced understanding of the use of the regression model beyond the CLRM. They should then be able to apply econometric techniques to real-world issues. The course also serves as preparation for an MSc level econometrics course.

Prerequisites
At least one semester of mathematical statistics with a serious analytical treatment of estimation and inference, and at least one semester of multivariate calculus, both passed at a respectable standard. The CLRM foundation is a mandatory prerequisite and applicants should be careful to provide evidence of meeting it.

The course assumes that participants will already have a sound understanding of the CLRM. After a brief review of the latter, it will cover the following topics:
•    stochastic regressors
•    measurement error
•    instrumental variables
•    simultaneous equations estimation

Next, it will cover binary choice models:
•    linear probability model and its shortcomings
•    logit model
•    probit model
•    tobit model
•    sample selection bias

The course will then treat issues related to regressions with time series data:
•    regressions with lagged variables
•    autoregressive distributed lag - ADL(p,q) - models
•    detailed treatment of issues relating to the ADL(1,0) model
•    consequences of the violation of the assumption of noncontemporaneous independence of regressors and disturbance term
•    autocorrelation: consequences, tests, and remedies
•    properties of nonstationary time series
•    tests for nonstationarity
•    cointegration
•    error correction models

The course will conclude with a brief treatment of panel data regressions.
The course will not use linear (matrix) algebra. 

This course will consist of three hours of lectures each morning and a small-group class lasting one hour and a half each afternoon. A written problem set will be due for each class.

A 2-hour examination will take place on the afternoon of Friday 26th August 2016.

Main text
Dougherty, Christopher, (2016) Introduction to Econometrics (fifth edition), Oxford University Press. Chapters 8 to 14

Software used
Stata and EViews will be used for the problem sets. These applications are provided on the public LSE network. No previous experience with either is expected.

"Chris and Clement did a fantastic job. They are both really passionate and knowledgeable about the topics covered in class. The course definitely improved my working knowledge in econometrics and I know it will be really beneficial in practice."
2014 participant on Intermediate Econometrics

"Chris was by a wide margin the best econometrics lecturer I have had. He taught with energy, enthusiasm and a fluency rarely encountered in highly technical disciplines."
2013 participant on Intermediate Econometrics

"The programme has provided me with a solid foundation from which to continue to advance my knowledge in econometrics. It has been a privilege to attend."
2013 participant on Intermediate Econometrics

Please note: A full timetable will be provided at registration on Monday 15 August. The below timetables contain approximate hours only

Week One (hours)
M	Tu	W	Th	F
Morning session	1.5	1.5	1.5	3	3
Afternoon session	3	3	3	1.5	1.5

Week Two (hours)
M	Tu	W	Th	F
Morning session	3	3	3	3	/
Afternoon session	1.5	1.5	1.5	1.5	Exam