Microeconometrics and Panel Data Econometrics
The purpose of this course is to provide students with an in-depth understanding of panel data econometrics presented from a microeconometrics perspective. The course will cover linear panel data models with unobserved heterogeneity, including discussions of the strengths and weakness of the various estimation methods
This module can be taken alone, or as part of a PG Certificate, PG Diploma or Full Masters Program.
Static panel models, random effects, fixed effects, first differencing estimators.
Instrumental variables estimation of models without strictly exogenous explanatory variables will also be covered
Dynamic panel models, Arellano Bond and Arellano Blundell Bond estimators.
Estimation of linear models with heterogeneous trends and heterogeneous slopes. Unbalanced panels, how to test for sample selection and attrition bias.
By the end of this course, participants should have knowledge and ability to:
Engage in abstract thinking by extracting the essential features of complex systems to facilitate problem solving and decision-making.
Communicate and present complex arguments in oral and written form with clarity and succinctness.
Use statistical and other packages effectively, presenting, interpreting and analysing information in numerical form.
Apply basic statistical techniques to analyse economic and financial datasets. Utilise effectively statistical and other packages
By the end of this course, students should be able to:
Microeconometrics and Panel Data Econometrics is a core 20 credit course and therefore students are expected to input approximately 200 hours of study into the course.
The total number of contact hours is 25 hours. This leaves 175 hours for private study.
This module consists of 4 - hour lectures per day for 5 days, plus a 1 - hour tutorial per day.
There will be optional clinics on the last day of the course.
The dates of each lecture are confirmed closer to the start of each term. If you have any questions about dates, please contact email@example.com.