Causal Inference and Public Policy
Official course title: Special Topics in Economics I (Course ID: 2952413)
Tentative Syllabus | Summer 2023 | Page last updated on: 4 June 2023
EBA Program | Faculty of Economics | Chulalongkorn University | Bangkok, Thailand
Instructors: Prof. Shikha Silwal, Ph.D. [Ajarn Shikha] & Prof. Jurgen Brauer, Ph.D. [Ajarn Jurgen]
Level: Intended for 2nd year students.
Description: This special topics course deals with the translation of economic theory to causal empirical analysis in a hands-on and mostly non-technical manner. While students are expected to take formal mathematics, statistics, and econometrics courses in their normal course of study, this course studies selected material at a level that is primarily conceptual (rather than formally theoretical) and practical (“click-here, click-there”, all coding provided), focusing on questions of empirical test design and the interpretation (causal inference) of the numerical results. The main objective is to learn how best to think about public policy issues and, especially, how to test statistically for any hypothesized claim of causality. For example, what is the effect of text messaging bans while driving on motor vehicle accidents (public health policy)? What is the effect of a 3rd child on employment and earnings (labor market policy)? Does foreign aid cause conflict (foreign aid policy)?
First things first: Welcome to class. We hope that you will have an enjoyable and formative learning experience in this class on causal inference and public policy.
Class level: Intended for 2nd year students.
Class type: Recorded and in-class lectures and hands-on computer lab sessions.
Class day/time: For the class days & times, see the class schedule below.
Class room: [To be announced.]
Class size: Limited to a maximum of 20 students.
Professors: Shikha Silwal, Ph.D. & Jurgen Brauer, Ph.D.
Professor emails: silwals@wlu.edu or jbrauer@duck.com.
Office room/hours: Email us to set up an appointment.
Course websites: https://www.jbrauer.info and links found there.
Grading and grades: The Chulalongkorn grading schedule applies. It is as follows: 90+% = A (Excellent; 4.0 points); 85-89% = B+ (Very Good; 3.5 points); 80-84% = B (Good; 3.0 points); 75-79% = C+ (Fairly Good; 2.5 points); 70-74% = C (Fair; 2.0 points); 65-69% = D+ (Poor; 1.5 points); 60-64% = D (Very poor; 1.0 point); <60% = F (Fail; zero points). It takes extra devotion and diligence to advance to the Very Good or Excellent levels of which the majority of Chula students are quite capable. The average Chulalongkorn economics student can expect to earn a grade of Good, which implies that I do not hesitate to record earned scores of less than that.
Academic honesty, class attendance, and expected classroom behavior: Please refer to the relevant university policies. Academic dishonesty is not tolerated and results in expulsion from class, a failing grade for the entire course, and reporting to the university authorities. Sadly, this has happened in the past, with students suspended from or altogether expelled from Chulalongkorn University. Academic dishonesty is embarrassing, painful, and costly to both students and faculty. Academic dishonesty includes cheating, ghostwriting, plagiarism, or other forms of dishonesty on any assigned work. Enrolling in this course means that you promise and agree not to engage in any form of academic misconduct. You also promise and agree to report other students to your professor and to the EBA Program Director if you know or suspect that a classmate is violating the honesty rule. Classroom behavior that permits unimpeded exchange of academically relevant ideas and views is expected. Unless required for class, turn off cell phones or other electronic devices and put them out of sight.
Textbook: No textbook. Lectures and materials we provide will serve the purpose.
Assignments:
1. Eight (8) computer lab write-ups (1 page each). The lab write-ups will be graded on a 4-3-2-1-0 (or "A", "B", "C", "D", "F") basis for up to 40% of your course grade. Instructions [here], which will be explained in class.
2. Class attendance, preparation, & participation (up to 10%).
3. A data replication & extension project, for a maximum of up to 50% of your course grade.
TENTATIVE SCHEDULE
Prof. Shikha Silwal is the primary professor for this course. Her course website is [here].
WEEK 1: Introduction and regression analysis (RA)
Tue 6 June (9a-12p) [Room: Mahit 612]
- Overview: course objective, syllabus, process, and assignments
- Lecture: Motivating statistical analysis: from description to causal inference
- Lecture: Causal modeling; directed acyclic graphs (DAGs); potential outcomes model; why causal analysis?
Thu 8 June (9a-12p) [Room: Econ 212 (computer lab)]
- Topic: Global dataset on miitary expenditure
- Lab #1 (descriptive): time charts, scatter plots, summary statistics, etc.
- Lab #2 (analytic): simple & multiple regression analysis
- Discussion: how to do a lab write-up: (a) state the research question; (b) describe the data; (c) discuss the method used & why; (d) present the technical results; (e) spell out the results' implications; and (f) contextualize & critically discuss (a) to (e)
- Prepare & do your lab #1 and lab #2 write-ups in class (45 min.)
WEEK 2: Difference-in-differences (DiD)
Tue 13 June (9a-12p) [Room: Econ 412]
- Lecture: Panel data & difference-in-differences (DiD) method
- Exercise: DiD problem (students work with paper & pencil to design a hypothetical study)
Thu 15 June (9a-12p) [Room: Econ 212 (computer lab)]
- Topic: The impact of the Americans with Disabilities Act on U.S. employment and earnings
- Reading: Acemoglu and Angrist 2001
- Lab #3 (analytic): replication study
- Prepare & do your lab #3 write-up in class (30 min.)
Fri 16 June (9a-12p) [Room: Econ 212 (computer lab)]
- Topic: Texting ban and road accidents
- Reading: Abouk and Adams 2013
- Lab #4 (analytic): replication study
- Prepare & do your lab #4 write-up in class (30 min.)
WEEK 3: Matching & propensity scores (MPS) / domestic public health issues
Tue 20 June (9a-12p) [Room: Econ 412]
- Lecture: Matching & propensity score (MPS) / Note: the lecture may be pre-recorded.
- Exercise: MPS problem (students work with paper & pencil to design a hypothetical study)
Thu 22 June (9a-12p) [Room: Econ 212 (computer lab)]
- Topic: Smoking ban and public health
- Reading: Evans, Farelly, and Montgomery 1999
- Lab #5 (analytic): replication study
- Prepare & do your lab #5 write-up in class (30 min.)
WEEK 4: Instrumental variables (IV) / (re)formation of cultural norms
Tue 27 June (9a-12p)
Midterm; no class
Thu 29 June (9a-12p) [Room: Econ 212 (computer lab)]
- Lecture: Instrumental variables (IV)
- Exercise: IV problem (students work with paper & pencil to design a hypothetical study)
- Topic: The effect of a 3rd child on parents' labor supply
- Reading: Angrist and Evans 1996
- Lab #6 (analytic): replication study
- Prepare & do your lab #6 write-up in class (30 min.)
WEEK 5: Regression discontinuity design (RDD) / [climate change, migration, pol. economy]
Tue 4 July (9a-12p) [Room: Econ 412]
- Lecture: Regression discontinuity design (RDD)
- Exercise: RDD problem (students work with paper & pencil to design a hypothetical study)
Thu 6 July (9a-12p) [Room: Econ 212 (computer lab)]
- Topic: The impact of (nearly) universal health care coverage on health care utilization and health outcomes
- Reading: Card, Dobkin, and Maestas 2004
- Lab #7 (analytic): replication study
- Prepare & do your lab #7 write-up in class (30 min.)
Fri 7 July (9a-12p) [Room: Econ 409]
- Informal project ideas presentations & discussion (project assignment is to work with prior data sets)
WEEK 6: Randomized controlled trials (RCT) / human & economic development
Tue 11 July (9a-12p) [Room: Econ 412]
- Lecture: Randomized controlled trials (RCT)
- Exercise: RCT problem (students work with paper & pencil to design a hypothetical study)
Thu 13 July (9a-12p) [Room: Econ 212 (computer lab)]
- Topic: Market access, farm product quality, and rural incomes
- Reading: Bold, Ghisolfi, Nsonzi, and Svensson 2022
- Lab #8 (analytic): replication study
- Prepare & do your lab #8 write-up in class (30 min.)
WEEK 7: Student projects
Tue 18 July (9a-12p) [Room: Econ 412]
- Informal student project discussion (in preparation for formal project write-up)
Thu 20 July (9a-12p)
- Final exam; no class; formal class project due
- Please complete the Chulalongkorn/EBA course evaluation form which will be sent to you separately by email.