Causality in Statistics (MT)

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The module introduces causal inference methods that are commonly used in quantitative research, in particularly social policy evaluations. It covers the contexts and principles as well as applications of several specific methods - instrumental variable approach, regression discontinuity design, and difference-in-differences analysis. Key aspects of the module include investigations of the theoretical basis, statistical process, and illustrative examples drawn from research papers published on leading academic journals. The module incorporates both formal lecturing and lab practice to facilitate understanding and applications of the specific methods covered. The module is suitable for those who are interested in quantitative research and analysis of causality across a range of topics in social sciences.

Basic knowledge of Stata is recommended to maximise the learning experience. If you are not familiar with Stata then taking the CaRM module 'Introduction to Stata' is recommended.

Number of sessions: 4

The module consists of four lectures (two-hour per session) including:

• Lecture 1: Introduction into causal inference methods

• Lecture 2: Instrumental variable approach

• Lecture 3: Regression discontinuity design

• Lecture 4: Difference-in-differences analysis

Lecture 1 will give a brief introduction of causal inference methods, focusing on the contexts, principles, and general applications of several of the commonly used methods. Lectures 2 to 4 will introduce three specific causal inference methods that widely used in academic research and social policy evaluations. These include instrumental variable approach, regression discontinuity design, and difference-in-differences analysis. We will investigate the theoretical basis, statistical process, and applications of these methods in research papers published on leading academic journals. The sessions will consist of formal lecturing followed by lab practice to enhance outcomes of learning.

By the end of the module, students will be able to:

• Understand the contexts and principles of causal inference methods

• Grasp the theoretical and statistical basis for several common causal inference methods

• Analyse and interpret research papers drawn on causal inference methods

Teaching will take place in person, with each session lasting for 2 hours. The sessions will consist of formal lecturing and lab practice, with each part lasting for approximately an hour.

The module uses Stata software for practical examples. You are required to arrive at each session with a fully charged laptop with a copy of Stata already uploaded. Participants with a valid CRSID who have booked on this module will be entitled to download a free copy of Stata MP4.

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This module runs once in Michaelmas Term and once in Lent. You only need to book on ONE of these iterations, either in Michaelmas OR in Lent.