This microeconometrics module covers the time series models and statistical techniques used to analyse cross-sectional and panel data in social sciences, with a focus on the identification of causal effects. This module’s main objective is to equip students with the tools necessary to conduct their empirical research precisely and confidently.
In terms of improving data skills, the module develops the ways students handle data, conduct descriptive analysis and visualise their results. A large emphasis is put on operationalising research questions and identifying the methods capable of answering these questions, given the data limitations. The module covers a set of state-of-the-art methods of identifying causal effects, including matching, instrumental variables and panel data methods. By the end of the module students will be able to apply these methods confidently and understand the strengths and limitations of each of these methods.
In terms of applications, the module covers many recent studies and students will be expected to conduct their own project.