- Module Code:
- Module Not Running 2021/2022
- FHEQ Level:
- Taught in:
- Term 2
The course is built on Econometrics (15PECC008) and complementary to Advanced Macroeconometrics (15PECC045). It caters to the need of both MSc students with an empirical bent and PhD students whose research involves empirical modelling. This course runs in parallel with Advanced Macroeconometrics (15PECC045).
The course covers basic econometric methods commonly used for analysing microeconomic cross-section and panel survey data. These include methods for analysing limited dependent variables as well as for estimating the impacts of policy-driven social programmes. It also discusses fundamental methodological issues in empirical modelling research to help students deepen their understanding of econometrics and enhance their critical appreciation of empirical works. The course is strongly applied-econometrics oriented with minimum emphasis on mathematical proofs and derivations. It is taught in a computer room with most examples based on real data samples.
More detailed course information is provided in the course website, which is accessible for all the registered students.
Students pursuing a degree external to the Department of Economics should contact the convenor for approval to take this module.
Objectives and learning outcomes of the module
The objective of the course is to enable students to use and apply appropriately basic micro-econometric methods currently being employed in development economics and economics in general. It also aims at raising students’ critical appreciation of applied econometric practice and broadening their understanding of major methodological issues in econometrics.
On successful completion of the course, you should be able to:
- explain core concepts in micro-econometrics
- apply various econometric methods, such as probit/logit, Tobit and Heckman selection procedure, propensity score matching, fixed effects versus random effects to modelling micro-econometric data
- conduct research with secondary data using econometric software and critically evaluate your own and other's applied results
Method of assessment
Assessment weighting: Coursework 100%
- Cameron and Trivedi (2005). Microeconomics: Methods and Applications
- Wooldridge J (2010). Econometric Methods for Cross Section and Panel Data. MIT Press
- Greene W (2006, 6th Edition). Econometric Analysis. Pearson-Prentice Hall.
Other useful readings:
- Peter Kennedy, A guide to Econometrics, 6E, 2008
- Peter Swann, Putting Econometrics in Its Place, 2006
- David Cox and Nancy Wermuth, Multivariate dependencies: Models, analysis and interpretation, 1996
- T. Hastie, R. Tibshirani and J Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2009
- S.M. Stigler, The seven pillars of statistical wisdom, 2016