| Academic Year |
2024Year |
School/Graduate School |
Graduate School of Innovation and Practice for Smart Society (Master's Course) |
| Lecture Code |
WTCA0002 |
Subject Classification |
Specialized Education |
| Subject Name |
Arts & Science for Evidence-Based Decision Making |
Subject Name
（Katakana） |
|
Subject Name in
English |
Arts & Science for Evidence-Based Decision Making |
| Instructor |
MITCHELL AUSTIN MICHAEL,CARO-BURNETT JOHANN |
Instructor
(Katakana) |
ミッチェル オースティン マイケル,カロ バーネット ヨハン |
| Campus |
Higashi-Hiroshima |
Semester/Term |
1st-Year, Second Semester, 3Term |
| Days, Periods, and Classrooms |
(3T) Weds1-4：IDEC Large Conference Rm |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
|
| |
| Credits |
2.0 |
Class Hours/Week |
|
Language of Instruction |
E
:
English |
| Course Level |
5
:
Graduate Basic
|
| Course Area（Area） |
24
:
Social Sciences |
| Course Area（Discipline） |
03
:
Economics |
| Eligible Students |
|
| Keywords |
|
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Class Objectives
/Class Outline |
The art and science of decision making is entering into a new era. The paradigm shift is upgrading the process of decision making and its impact evaluation from an experience-based subjective approach to a more objective, evidence-based one. Evidence-based decision making does not merely mean the utilization of data. Rather, it explicitly prohibits doing so, by acknowledging the wisdom that what our data shows in front of our eyes is just the correlation, and not the causation that we need to base our decision on. Throughout the course, all concepts are delivered without using technical expressions. Students will acquire the intuition directly from the lectures and presentations, and are expected to learn the fundamentals of evidence-based decision making and its impact evaluations. The course consists of lectures, weekly assignments, and a final examination. |
| Class Schedule |
Unit 1: Introduction to causal inference
Unit 2: Random control trials
Unit 3: Matching
Unit 4: Difference in differences
Unit 5: Research discontinuity design
Unit 6: Instrumental variables
Unit 7: Advanced topics in data analysis
Final exam |
Text/Reference
Books,etc. |
• Angrist, Joshua D. , and Jörn-Steffen Pischke. Mastering 'metrics: The path from cause to effect. Princeton university press, 2014.
• Angrist, Joshua D. , and Jörn-Steffen Pischke. Mostly harmless econometrics: An empiricist's companion. Princeton university press, 2009.
• Cunningham, Scott. Causal Inference: The Mixtape. Yale University Press, 2021. |
PC or AV used in
Class,etc. |
|
| (More Details) |
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| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Please watch the following YouTube videos for more about the causal inference:
Mod•U: Powerful Concepts in Social Science
(1) Causal Inference Bootcamp: Introduction to Causality
https://www.youtube.com/watch? v=FNpcwiOme1g&list=PL1M5TsfDV6Vufqfs_h5fDR3pBhIj4QOW7
(2) Causal Inference Bootcamp: Your Guide to Experiments
https://www.youtube.com/watch?v=S5TVIPknDI4&list=PL1M5TsfDV6Vui- q_q1Bq5kF2Y77udGwWx
(3) Causal Inference Bootcamp: Your Guide to Instrumental Variables
https://www.youtube.com/watch? v=4xF_DMbL14w&list=PL1M5TsfDV6VsE11CCeMuBL0owBpwp4xru |
| Requirements |
|
| Grading Method |
Weekly assignments and final examination |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |