Hiroshima University Syllabus

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Academic Year 2024Year School/Graduate School Graduate School of Innovation and Practice for Smart Society (Master's Course)
Lecture Code WTCA0001 Subject Classification Specialized Education
Subject Name Arts & Science for Evidence-Based Decision Making
Subject Name
Subject Name in
Arts & Science for Evidence-Based Decision Making
ゴトウ ダイサク,ヨシダ ユウイチロウ,ハーン グラム ダスタギール,サイジョウ ハルノブ,カロ バーネット ヨハン
Campus Higashi-Hiroshima Semester/Term 1st-Year,  First Semester,  1Term
Days, Periods, and Classrooms (1T) Mon1-4: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
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
(Applicable only to targeted subjects for undergraduate students)
Criterion referenced
(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.
Class Schedule lesson1 Correlation vs. Causation

lesson2 Counterfactuals & Unit Level Treatment Effects

lesson3 Average Treatment Effects & Conditional Average Treatment Effects

lesson4 Confounders and Directed Acyclic Graphs (DAGs)

lesson5 Statistical vs. Causal Inference

lesson6 Controlled Experiments & Randomized Experiments

lesson7 Difficulties in Performing Randomized Experiments

lesson8 The Two Kinds of Natural Experiments

lesson9 Justifying As-If Randomization

lesson10 Noncompliance in Experiments & Survey Noncompliance

lesson11 4 Ways of Dealing with Noncompliance: Bounds Analysis for Missing Data

lesson12 Visual Logic of Instrumental Variables

lesson13 The 3 Assumptions of Instrumental Variables

lesson14 The "No Defiers" Assumption & The Local Average Treatment Effect (LATE)

lesson15 Regression Discontinuity Design as a Relevant Variation of IV Analysis

• 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.

• Huntington-Klein, N. (2022). The effect: An introduction to research design and causality. Chapman and Hall/CRC.
PC or AV used in
(More Details) a computer & a projector 
Learning techniques to be incorporated  
Suggestions on
Preparation and
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 
Grading Method class participation and performances in quizzes 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
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. 
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