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Teaser image to From Couch to Poll: Media Content and the Value of Local Information

 

From Couch to Poll: Media Content and the Value of Local Information

Mathias Bühler, Volkswirtschaftliche Fakultät, LMU Munich

   10.01.2024

   4:15 pm - 5:45 pm

   LMU Department of Statistics and via zoom

Analyzing Canada's media landscape, the study reveals that TV introduction reduced voter turnout, primarily in public markets. Private broadcasters emphasize local information, prompting politicians in private districts to engage more locally and defy party lines. This underscores the impact of local TV on political engagement.

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Link to Privacy, Data Privacy, and Differential Privacy

 

Colloquium  •  16.07.2024  •  LMU Department of Statistics and via zoom

Privacy, Data Privacy, and Differential Privacy

Colloquium at the LMU Department of Statistics with James Bailie from Harvard University.

Link to Variational Learning for Large Deep Networks

 

Colloquium  •  10.07.2024  •  LMU Department of Statistics and via zoom

Variational Learning for Large Deep Networks

Colloquium at the LMU Department of Statistics with Thomas Möllenhoff from RIKEN, Tokyo.

Link to Can today’s intention to treat have a causal effect on tomorrow’s hazard function?

 

Colloquium  •  03.07.2024  •  LMU Department of Statistics and via zoom

Can today’s intention to treat have a causal effect on tomorrow’s hazard function?

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Link to The Complexities of Differential Privacy for Survey Data

 

Colloquium  •  26.06.2024  •  LMU Department of Statistics and via zoom

The Complexities of Differential Privacy for Survey Data

Link to Resampling-based inference for the average treatment effect in observational studies with competing risks

 

Colloquium  •  19.06.2024  •  LMU Department of Statistics and via zoom

Resampling-based inference for the average treatment effect in observational studies with competing risks

This talk explores three resampling methods to construct valid confidence intervals and bands for treatment effect estimation in competing risks studies.