November 16, 2021

Every conference day consists of three presentation blocks, followed by a keynote talk in the evening. Times are Central European Time (CET). Registered participants will receive a link to Zoom to join the Meeting.

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Time	Presentation
10:30	Welcome Paul Hünermund, Jermain Kaminski, Carla Schmitt, Beyers Louw Copenhagen Business School / Maastricht University
	Session 1
10:40	The impact of the #MeToo movement on language at court: A text-based causal inference approach Henrika Langen University of Fribourg
10:55	Firm incentives and consumer adaption in a multi unit auction Simon Schulten Düsseldorf Institute for Competition Economics (DICE)
11:10	Drawing (causal) conclusions from data – some evidence Karsten Lübke FOM University of Applied Sciences
11:25	End-to-end causal analysis in Python with cause2e Daniel Gruenbaum Osram
11:40	Q & A
12:00	60 min break (Timer)
	Session 2
13:00	The role of the propensity score in fixed effect models Dmitry Arkhangelsky Center for Monetary and Financial Studies (CEMFI)
13:15	The challenges of measuring the impact of interventions in brick-and-mortar stores Patrick de Oude Albert Heijn
13:30	Longitudinal symptomatic interactions in long-standing schizophrenia: a novel five-point analysis based on directed acyclic graphs Giusi Moffa University of Basel
13:45	Causal inference with proxy variables in Booking.com Christina Katsimerou Booking.com
14:00	Q & A
14:20	30 min break (Timer)
	Session 3
14:50	Treatment effects in strategic management: with an application to choosing early stage venture capital Jorge Guzman Columbia Business School
15:05	Deep learning for individual heterogeneity: An automatic inference framework Max Farrell The University of Chicago Booth School of Business
15:20	Causal knowledge graph: A demonstration Victor Chen University of North Carolina at Charlotte
15:35	An empirical analysis of intra-firm product substitutability in fashion retailing Nathan Yang Cornell University
15:50	Q & A
16:10	30 min break (Timer)
	Session 4
16:40	The importance of being causal Iavor Bojinov Harvard Business School
16:55	Desiderata for representation learning: A causal perspective Yixin Wang University of Michigan
17:10	What experimental designs justify two-way-fixed-effects regression estimators Lihua Lei Stanford University
17:25	CausalML: A Python package for uplift modeling and causal inference with machine learning Zhenyu Zhao, Totte Harinen Tencent, Toyota Research
17:40	Q & A
18:00	30 min break (Timer)
	Keynote
18:30	Keynote A Design Approach to Synthetic Controls Guido Imbens Stanford University

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Authors denote presenters. Full author list will be visible in published papers.