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Fabian Lange on Seminar Series: Causal Inference and Data Science for Improved Policy

On April 22, 2024, DSI hosted the presentation titled “Labour Force Transitions,” marking the second talk of our seminar series that encourages research collaboration among data scientists, causal inference experts, and applied researchers. This series is funded through the DSI Emergent Data Sciences Program competition, and co-led by Professors Linbo Wang (Departments of Statistical Sciences and Computer Science), Gustavo J. Bobonis, Raji Jayaraman, and Ismael Mourifié (Department of Economics) at the University of Toronto.

Speaker

Fabian Lange, Professor, Department of Economics, McGill University

 

 

 

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Prof. Lange delved into latent-state and type models utilized in the labor force transitions literature, offering insights into the heterogeneity observed in transitions between employment and non-employment states. The seminar compared results obtained from methods relying on short panels such as the Current Population Survey and approaches reliant on long administrative and survey datasets.

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