Applied Microeconometrics - ECO00092M

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Module summary

The module will cover econometric methods that are essential for empirical analysis in microeconomics: e.g. linear and non-linear models, endogeneity issues, panel data, missing data and causal inference methods. Applied empirical examples will be provided.

Module will run

Occurrence	Teaching period
A	Semester 2 2023-24

Module aims

The module is designed to teach students econometric techniques that are essential for empirical analysis in microeconomics. The focus is on building basic research skills, including learning how to apply these techniques in practice, and on reading, interpreting and understanding empirical research. The module will cover key microeconometric estimation methods, such as panel data methods and models for limited dependent variables, as well as quasi-experimental econometric methods such as instrumental variables and differences in difference approaches. It will provide a broad range of empirical examples from labour economics, education, health economics and industrial organisation. Students will learn to use Stata to estimate different types of models, test assumptions, choose between different models and interpret results. The module will provide basic coding skills in Stata that are applicable to a broad set of coding platforms and statistical software. This will be invaluable for any empirical MSc dissertation topic and also for any job which involves the use of data for economic analysis.

Module learning outcomes

Given the extensive use of individual/household data sources in applied microeconomic analysis, it has become increasingly important to understand the techniques available to the microeconometrician in applied research. Moreover, it is just as important to be aware of the limitations and pitfalls associated with each microeconometric technique. The purpose of this module is to provide the applied economist with sufficient background of modern microeconometrics to choose techniques suited both to the data and to the economic model. Also, the lectures provide the opportunity to gain experience of empirical analysis using Stata software.

Module content

Outline syllabus (TBC)

1. Interpretation of linear and nonlinear regressions

2. Randomized Experiments

3. Regression and causality

4. Propensity score methods

5. Instrumental Variable Estimation and Natural Experiment

6. Extension of instrumental variable

7. Differences-in-Differences

8. Panel data analysis

9. Missing data and sample selection

10. How to start a research project

11. How to write up the results of a project

Indicative assessment

Task	% of module mark
Essay/coursework	100

Special assessment rules

None

Indicative reassessment

Task	% of module mark
Essay/coursework	100

Module feedback

Feedback will be provided in line with University policy

Indicative reading

Angrist, J. D., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist's companion. Princeton University Press.

Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data. MIT press.

Cameron, A. C., & Trivedi, P. K. (2010). Microeconometrics using stata (Vol. 2). College Station, TX: Stata press.