{"id":195053,"date":"2026-11-09T15:30:29","date_gmt":"2026-11-09T14:30:29","guid":{"rendered":"https:\/\/www.ieseg.fr\/?post_type=events&p=195053"},"modified":"2026-11-09T15:35:22","modified_gmt":"2026-11-09T14:35:22","slug":"workshop-causal-inference-workshop-2","status":"publish","type":"events","link":"https:\/\/www.ieseg.fr\/en\/events\/workshop-causal-inference-workshop-2\/","title":{"rendered":"[Workshop] Causal Inference Workshop"},"content":{"rendered":"\n
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From Financial Event Studies to Causal Inference<\/em><\/strong>
May 20th,<\/sup> 2027 <\/strong><\/em>on I\u00c9SEG Lille Campus<\/em><\/strong><\/p>\n\n\n\n

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Preamble<\/strong><\/h2>\n\n\n\n

Many research questions in the social sciences aim to establish a causal relationship between a particular element and its expected effects. In recent years, the quality of empirical studies designed to address these questions has significantly improved, particularly through more systematic use of identification strategies previously developed in economics. These strategies stem from economists’ growing awareness of the limitations of certain methods and were recognized with the Nobel Prize in Economics in 2021[1]<\/a>. Consequently, this “credibility revolution” in causal inference has naturally led to the recent and rapid adoption of the most sophisticated identification techniques, particularly in the field of corporate finance[2]<\/a>.<\/p>\n\n\n\n

workshop topic<\/h2>\n\n\n\n

Financial event studies are among the most widely used empirical methods in finance and accounting. They measure stock price reactions to corporate events, such as mergers and acquisitions, earnings announcements, and regulatory decisions. But do abnormal returns necessarily identify causal effects? What assumptions are needed to interpret them causally? And how can modern causal inference methods help researchers construct more credible counterfactuals? The AIC 2027 workshop will address these questions by connecting traditional financial event studies with recent developments in causal inference.<\/p>\n\n\n\n

The workshop will be organized around two main references: Goldsmith-Pinkham and Lyu, Causal Inference in Financial Event Studies<\/em><\/strong>, which provides the central framework, and Abadie (2021), Using Synthetic Controls<\/em><\/strong>, which offers a comprehensive introduction to synthetic control methods, their assumptions, and practical implementation. The day will combine theoretical foundations, identification issues, methodological extensions, and a hands-on application to mergers and acquisitions (M&A) announcements.<\/p>\n\n\n\n

Targeted audience<\/h2>\n\n\n\n

The workshop is intended for academic researchers interested in empirical work, primarily in causal inference. Although the empirical framework presented is mainly based on examples from economics, finance, and accounting, the fields of application are broad and encompass all areas of management and social sciences (accounting, marketing, strategy, human resources, organization, political science, etc.).<\/p>\n\n\n\n

Practicalities & Registration<\/h2>\n\n\n\n