2024 Faculty Courses School of Environment and Society Department of Architecture and Building Engineering Graduate major in Urban Design and Built Environment
Empirical Analysis: Theory and Practice
- Academic unit or major
- Graduate major in Urban Design and Built Environment
- Instructor(s)
- Hitomu Kotani
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 5-6 Fri
- Class
- -
- Course Code
- UDE.P501
- Number of credits
- 100
- Course offered
- 2024
- Offered quarter
- 4Q
- Syllabus updated
- Mar 14, 2025
- Language
- English
Syllabus
Course overview and goals
In studies on urban design and built environment, we should analyze data obtained through observations and questionnaires. In this lecture, we will focus on empirical analysis and learn the theory and practice, with an emphasis on causal inference. In order to deepen the understanding of the lecture, students will present the results of their empirical analysis on a topic of their own interest and discuss the results.
Course description and aims
By the end of this course, students will be able to
- understand the basic theory of causal inference
- implement it
Keywords
empirical analysis; statistics; causal inference
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
The class will be taught mainly through lectures.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Introduction, selection bias, and RCT | Understand selection bias and RCT (Randomized Controlled Trial). |
| Class 2 | Causal inference: Regression analysis | Understand regression analysis for measuring the effect of interventions. |
| Class 3 | Causal inference: Propensity score analysis | Understand analysis using propensity scores. |
| Class 4 | Causal inference: DID | Understand DID (Difference-in-Difference). |
| Class 5 | R programming | Implement the causal inference using R. |
| Class 6 | Group work/presentation 1 | Each group will introduce an applied paper that uses causal inference. |
| Class 7 | Group work/presentation 2 | Each group will present and discuss the results of their analysis of a topic of their own interest. |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
NAN
Reference books, course materials, etc.
Angrist, J. D., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist's companion. Princeton University Press.
Other materials will be introduced during class as needed.
Evaluation methods and criteria
Group work/presentation (70%) and attendance/feedback for every lecture (30%)
Related courses
- UDE.D417 ： Introduction to Methodology of Social studies
Prerequisites
Basic statistics at undergraduate level