Course unit details:
Microeconometrics
| Unit code | ECON60052 |
|---|---|
| Credit rating | 15 |
| Unit level | FHEQ level 7 – master's degree or fourth year of an integrated master's degree |
| Teaching period(s) | Semester 2 |
| Available as a free choice unit? | Yes |
Overview
The aims of this course unit are to:
(i) introduce students to modelling and estimation techniques in the analysis of microeconometric data;
(ii) develop an understanding on how and when to use the different techniques
(iii) provide sufficient background to enable students to read the applied literature which applies these techniques;
(iv) prepare students for a dissertation topic that analyses microeconometric data.
Pre/co-requisites
| Unit title | Unit code | Requirement type | Description |
|---|---|---|---|
| Econometric Methods | ECON61001 | Pre-Requisite | Compulsory |
Pre requisite ECON61001
Aims
The aims of this course unit are to:
(i) introduce students to modelling and estimation techniques in the analysis of microeconometric data;
(ii) develop an understanding on how and when to use the different techniques
(iii) provide sufficient background to enable students to read the applied literature which applies these techniques;
(iv) prepare students for a dissertation topic that analyses microeconometric data.
Learning outcomes
On completion of this unit successful students will be able to:
(i) demonstrate an understanding of some of the problems associated with microeconometric data such as endogenous regressors, selection bias and causal effects;
(ii) understand and apply some standard techniques to address these problems, such as instrumental variable estimation, randomized experiments, using panel data, using Differences-in-Differences approaches or using Regression Discontinuity Designs;
(iv) apply these techniques using the computer software R;
(v) interpret R output correctly.
Syllabus
Provisional
1) Regression
(2) Standard Errors
(3) Instrumental Variables
(4) Randomized Experiments
(5) Panel Data Methods
(6) Differences-in-Differences
(7) Regression Discontinuity Designs)
Teaching and learning methods
Lectures and tutorials
Assessment methods
| Method | Weight |
|---|---|
| Other | 25% |
| Written exam | 75% |
75% Final Exam
25% Group MIdterm Assessment
Recommended reading
There is no one course text. Material will be delivered primarily though the lecture unless specified otherwise.
The main texts are: -
Wooldridge, J.M. (2020): Introductory Econometrics: A Modern Approach, 7th ed., Cengage. -
Angrist, J. D. and J.- S. Pischke (2009). Mostly Harmless Econometrics, Princeton University Press.
For some parts, the course also follows: -
Wooldridge, J.M. (2010): Econometric Analysis of Cross Section and Panel Data, Second Edition. MIT Press. -
Duflo, E., Glennester, R. and M. Kremer (2007): Chapter 61 Using Randomization in Development Economics research: A Toolkit, Elsevier, vol. 4 of Handbook of Development Economics, 3895 – 3962. -
Fröhlich, M. and S. Sperlich (2019): Impact Evaluation: Treatment Effects and Causal Analysis. Cambridge University Press.
Students may note that the following cover the same or related topics. -
Cameron, C. and P. Trivedi (2012): Microeconometrics: Methods and Applications, Cambridge University Press. -
Verbeek, M. (2012): A Guide to Modern Econometrics, 4th edition, Wiley. -
Angrist, J.D. and J.-S. Pischke (2014): Mastering metrics: The path from cause to effect. Princeton, New Jersey: Princeton University Press.
The specific references relevant for each topic are given in the lectures
Study hours
| Scheduled activity hours | |
|---|---|
| Lectures | 18 |
| Tutorials | 7 |
| Independent study hours | |
|---|---|
| Independent study | 125 |
Teaching staff
| Staff member | Role |
|---|---|
| Jasmin Fliegner | Unit coordinator |
Additional notes