Program & Materials
All lectures will be delivered in Korean and uploaded on the YouTube Channel. For learning materials, click each section to expand below.
All PPT files can be used for educational purposes.
Boot Camp for Beginners (6/13~6/17)
* The Boot Camp aims to introduce basic concepts and methods for causal inference to beginners.
[6/13, 9:30 am - 12:00 pm] What is Causal Inference?
[6/14, 9:30 am - 12:00 pm] Potential Outcome Framework, Regression, and Matching
[6/15, 9:30 am - 12:00 pm] Quasi-Experiments
[6/16, 9:30 am - 12:00 pm] Instrumental Variable and Regression Discontinuity
[6/17, 9:30 am - 10:45 am] Causal Graph and Structural Causal Model
[6/17, 10:45 am - 12:00 pm] Transporting Causal Effects Across Populations Using Structural Causal Modeling: The Example of Work-From-Home Productivity
Speaker: Sujin Park (PhD Candidate in Management Information Systems, Department of Information and Decision Sciences, University of Illinois at Chicago)
Slide (PDF)
Reading List
Park, S., Tafti, A.R. and Shmueli, G., 2021. Transporting Causal Effects Across Populations Using Structural Causal Modeling: The Example of Work-From-Home Productivity. Available at SSRN.
재미한인과학기술자협회 NC지부 특별세션
[6/21] Health Informatics & Marketing
[9:30 am - 10:45 am] The Unintended Consequences from Repealing a Green Nudge: Evidence from Single-Use Bag Policies
Speaker: Sungjin Kim (Assistant Professor of Marketing, Shidler College of Business, University of Hawaii at Manoa)
Slide (PDF)
Reading List
Kim, S., Lee, C. and Gupta, S., 2020. Bayesian synthetic control methods. Journal of Marketing Research, 57(5), pp.831-852.
[10:45 am - 12:00 pm] Heterogeneous Treatment Effect Estimation Using Machine Learning - Application to Healthcare Data
Speaker: Yejin Kim (Assistant Professor, School of Biomedical Informatics, University of Texas Health Science Center)
Slide (PDF)
Reading List
Ling, Y., Upadhyaya, P., Chen, L., Jiang, X. and Kim, Y., 2021. Heterogeneous treatment effect estimation using machine learning for healthcare application: tutorial and benchmark. arXiv preprint arXiv:2109.12769.
[6/23] Biostatistics & Policy Evaluation
[9:30 am - 10:45 am] A Bayesian Approach for Handling Covariate Measurement Error When Estimating Population Treatment Effect
Speaker: Hwanhee Hong (Assistant Professor, Department of Biostatistics & Bioinformatics, Duke University)
Slide (PDF)
[10:45 am - 12:00 pm] Policy Effect Evaluation under Counterfactual Neighborhood Intervention in the Presence of Spillover
Speaker: Youjin Lee (Manning Assistant Professor, Department of Biostatistics, Brown University)
Slide (PDF)
한국경영학회 콜로키움
[6/28] Marketing & Accounting
[9:30 am - 10:45 am] In the Company of Strangers: Social Influence from Anonymous Peers and its Underlying Mechanisms in Video Games
Speaker: Wooyong Jo (Assistant Professor of Marketing, Krannert School of Management, Purdue University)
Slide (PDF)
[10:45 am - 12:00 pm] An Analyst by Any Other Surname: Surname Favorability and Market Reaction to Analyst Forecasts
Speaker: Jay H. Jung (Senior Lecturer in Accounting, Bayes Business School, City, University of London)
Slide (PDF)
Reading List
Jung, J.H., Kumar, A., Lim, S.S. and Yoo, C.Y., 2019. An analyst by any other surname: Surname favorability and market reaction to analyst forecasts. Journal of Accounting and Economics, 67(2-3), pp.306-335.
[6/30] Organization & Entrepreneurship
[9:30 am - 10:45 am] Using Natural Experiments in Organizational Settings for Management Research
Speaker: Sunkee Lee (Assistant Professor of Organizational Theory and Strategy, Tepper School of Business, Carnegie Mellon University)
Slide (PDF)
Reading List
Lee, S., 2019. Learning-by-moving: can reconfiguring spatial proximity between organizational members promote individual-level exploration?. Organization Science, 30(3), pp.467-488.
Lee, S. and Meyer-Doyle, P., 2017. How performance incentives shape individual exploration and exploitation: Evidence from microdata. Organization Science, 28(1), pp.19-38.
[10:45 am - 12:00 pm] Thinking about Endogeneity in Entrepreneurship Research
Speaker: Sukhun Kang (PhD Candidate in Strategy & Entrepreneurship, London Business School)
Slide (PDF)
Reading List
Required:
Howell, Sabrina T. "Financing innovation: Evidence from R&D grants." American Economic Review 107.4 (2017): 1136-64.
Conti, Annamaria. "Entrepreneurial finance and the effects of restrictions on government R&D subsidies." Organization Science 29.1 (2018): 134-153.
Jaffe, Adam B. "Building programme evaluation into the design of public research‐support programmes." Oxford Review of Economic Policy 18.1 (2002): 22-34.
Optional:
Chen, Jin, et al. "The distinct signaling effects of R&D subsidy and non-R&D subsidy on IPO performance of IT entrepreneurial firms in China." Research Policy 47.1 (2018): 108-120.
Audretsch, David B., Isabel Grilo, and A. Roy Thurik. "Explaining entrepreneurship and the role of policy: a framework." The Handbook of Research on Entrepreneurship Policy (2007): 1-17.
Becker, Bettina. "Public R&D policies and private R&D investment: A survey of the empirical evidence." Journal of Economic Surveys 29.5 (2015): 917-942.
[7/2] Industry & International Organization
[9:30 am - 10:45 am] The Dynamic Effects of Cash Transfers: Evidence from Rural Liberia and Malawi
Speaker: Dahyeon Jeong (Economist, Development Impact Evaluation (DIME), World Bank)
Slide (PDF)
[10:45 am - 12:00 pm] 톰슨샘플링을 써보자
한국경영정보학회 특별세션
[7/5] Operations Management & Economics
[9:30 am - 10:45 am] Managing the Impact of Fitting-Room Traffic on Retail Sales: Using Labor to Reduce Phantom Stockouts
Speaker: Hyun Seok (“Huck”) Lee (Assistant Professor of Logistics, Service and Operations Management, Korea University Business School, Korea University)
Slide (PDF)
Reading List
Lee H, Kesavan S, Deshpande V (2021) Managing the Impact of Fitting-Room Traffic on Retail Sales: Using Labor to Reduce Phantom Stockouts. Manufacturing & Service Operations Management, 23(6): 1580-1596.
[10:45 am - 12:00 pm] Agency Frictions and Procurement: New Evidence from U.S. Electricity Restructuring
Speaker: Jin Soo Han (Assistant Professor, College of Business, Korea Advanced Institute of Science and Technology)
Slide (PDF)
[7/7] Information Systems
[9:30 am - 10:45 am] Randomized Field Experiments for (Health) Behavior Change: Intervention, Incentive, and Targeting
Speaker: Nakyung Kyung (Assistant Professor of Information Systems, School of Computing, National University of Singapore)
Slide (PDF)
Reading List
Kyung, N. and Kwon, H.E., 2022. Rationally trust, but emotionally? The roles of cognitive and affective trust in Laypeople's acceptance of AI for preventive care operations. Production and Operations Management. forthcoming.
[10:45 am - 12:00 pm] A Nudge to Credible Information as a Countermeasure to Misinformation: Evidence from Twitter
Speaker: Elina H. Hwang (Assistant Professor of Information Systems, Foster School of Business, University of Washington in Seattle)
Slide (PDF)
Reading List
Hwang, E.H. and Lee, S., 2021. A Nudge to Credible Information as a Countermeasure to Misinformation: Evidence from Twitter. Available at SSRN.
Hwang, E.H., Nageswaran, L. and Cho, S.H., 2022. Value of online–off-line return partnership to off-line retailers. Manufacturing & Service Operations Management, 24(3), pp.1630-1649.
[7/9] Industry
[9:30 am - 10:45 am] Applications of Causal Inference in Product Analytics
Speaker: Bokyung Choi (Data Scientist, QANDA)
Slide (PDF)
[10:45 am - 12:00 pm] 게임 업계 인과 추론 분석 사례 및 향후 과제
Speaker: Eun Jo Lee (Head of Intelligence and Insight Division, NCSOFT)
Slide (PDF)
한국인공지능학회 특별세션
[7/12] Artificial Intelligence & Machine Learning I
[9:00 am - 11:00 am] Introduction to Causal Model for AI
Speaker: Chang D. Yoo (Professor, School of Electrical Engineering, KAIST)
Slide (PDF)
[11:00 am - 12:00 pm] Applications of Causal Model in AI
Speaker: Gwangsu Kim (Research Associate Professor, School of Electrical Engineering, KAIST)
Slide (PDF)
[12:00 pm - 1:15 pm] Causal Model and Vision
Speaker: Junyeong Kim (Assistant Professor, Department of Artificial Intelligence, Chung-Ang University)
Slide (PDF)
[7/14] Artificial Intelligence & Machine Learning II
[9:30 am - 10:45 am] Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder
Speaker: Il-Chul Moon (Associate Professor, Department of Industrial and Systems Engineering, KAIST)
Slide (PDF)
Reading List
Kim, H., Shin, S., Jang, J., Song, K., Joo, W., Kang, W. and Moon, I.C., 2021, May. Counterfactual fairness with disentangled causal effect variational autoencoder. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 9, pp. 8128-8136).
[10:45 am - 12:00 pm] On Nested Counterfactual Identification
Speaker: Sanghack Lee (Assistant Professor, Graduate School of Data Science, Seoul National University)
Slide (PDF)
Reading List
Correa, J., Lee, S. and Bareinboim, E., 2021. Nested counterfactual identification from arbitrary surrogate experiments. Advances in Neural Information Processing Systems, 34, pp.6856-6867.
[12:00 pm - 1:15 pm] Estimating Identifiable Causal Effects and its Application toward Interpretable ML/AI
Speaker: Yonghan Jung (PhD Candidate, Department of Computer Science, Purdue University)
Slide (PDF)
Reading List
[Estimating Identifiable Causal Effects through Double Machine Learning] Y.Jung, J. Tian, E. Bareinboim. AAAI-21.
[Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine Learning] Y.Jung, J. Tian, E. Bareinboim. ICML-21.
[On Measuring Causal Contribution via do-intervention] Y. Jung, S. asiviswanathan, J. Tian, D. Janzing, P. Blöbaum, E. Bareinboim. ICML-22.
[7/16] Artificial Intelligence & Machine Learning III
[10:30 am - 11:45 am] Language Models for Commonsense & Causal Reasoning
Speaker: Sungbin Lim (Assistant Professor, Artificial Intelligence Graduate School & Department of Industrial Engineering, UNIST)
Slide (PDF)