What is the module about?
This course provides students with a practical understanding of econometrics. The course covers the key statistical methods that economists use to disentangle cause and effect: regression, instrumental variables, regression discontinuity designs and difference-in-differences. These methods are illustrated with interesting and relevant real-world examples.
Who should do this module?
It provides students with an understanding of econometric methods and how they are applied to economic problems. Students will gain good command of Stata.
You must have already covered the following at your home university to be able to be registered on this module:
Regression analysis, simple regression model; multiple regression analysis, estimation and inference; data scaling, beta coefficients, logarithmic functional forms, quadratics, interactions; multiple regressions with binary (or dummy) variables; probability models, panel data.
20% tutorial assessment (one short assignment)
1 x 1-hour weekly lecture
1 x 1-hour weekly tutorial
Suggested reading list
The module textbook is:
Angrist and Pischke (2015), Mastering ‘Metrics, Princeton University Press
This will be complemented by the following textbook:
Wooldridge (2016), Introductory Econometrics: a Modern Approach, Cengage Learning, 6th edition
We will also be covering some academic papers. The focus will be on the empirical techniques used in those papers.