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.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: %E2%80%A2%09stochastic regressors%E2%80%A2%09measurement error%E2%80%A2%09instrumental variables%E2%80%A2%09simultaneous equations estimationNext, it will cover binary choice models:%E2%80%A2%09linear probability model and its shortcomings%E2%80%A2%09logit model%E2%80%A2%09probit model%E2%80%A2%09tobit model%E2%80%A2%09sample selection biasThe course will then treat issues related to regressions with time series data:%E2%80%A2%09regressions with lagged variables%E2%80%A2%09autoregressive distributed lag - ADL(p,q) - models%E2%80%A2%09detailed treatment of issues relating to the ADL(1,0) model%E2%80%A2%09consequences of the violation of the assumption of noncontemporaneous independence of regressors and disturbance term%E2%80%A2%09autocorrelation: consequences, tests, and remedies%E2%80%A2%09properties of nonstationary time series%E2%80%A2%09tests for nonstationarity%E2%80%A2%09cointegration%E2%80%A2%09error correction modelsThe 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.

Course leader
Dr Christopher Dougherty

Target group
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 financial statistics course.

Course aim
This course aims to build a solid, comprehensive understanding of the use of the regression model when one progresses from the Classical Linear Regression Model, with its strong and unrealistic assumptions, and addresses the issues that researchers encounter in practice.

Credits info
5 ECTS The decision to award credits is at the discretion of the student's home institution. Students should always check with their home institution to confirm the number of credits that can be awarded.

Fee info
GBP 1435: Student rate - available to current university (including PhD) students.Academic staff and staff of UK charities are eligible for a reduced rate of 1,930. GBP 2425: Standard rate

Scholarships
Previous students of LSE may be eligible for a 15% discount on their tuition fees.

London School of Economics
Address: Houghton Street
Postal code: WC2A 2AE
City: London
Country: United Kingdom
Website: http://www.lse.ac.uk/study/summerSchools/Methods/home.aspx
E-mail: summer.methods@lse.ac.uk
Phone: +44 (0)20 7955 6422