4 papers · 1 filter
Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact
Masahiro Kato, Daiki Honma, Taka Kato
Generative artificial intelligence changes how firms reach customers, but standard marketing data do not record how often users see and notice a firm's name in generated answers. W…
genriesz: A Python Package for Automatic Debiased Machine Learning with Generalized Riesz Regression
Masahiro Kato
Efficient estimation of causal and structural parameters can be automated using the Riesz representation theorem and debiased machine learning (DML). We present genriesz, an open-s…
Riesz Regression As Direct Density Ratio Estimation
Masahiro Kato
This study clarifies the relationship between Riesz regression [Chernozhukov et al., 2021] and density ratio estimation (DRE) in causal inference problems, such as average treatmen…
A Unified Theory for Causal Inference: Direct Debiased Machine Learning via Bregman-Riesz Regression
Masahiro Kato
This note introduces a unified theory for causal inference that integrates Riesz regression, covariate balancing, density-ratio estimation (DRE), targeted maximum likelihood estima…