Masahiro Kato

This work develops Generative Marketing Mix Modeling (GMMM) to estimate the causal effects of Generative Engine Optimization and Generative Engine Marketing and investigates the empirical performance of the proposed method using simulated answers to product recommendation in English and Japanese.

RAG-based policy learning can significantly enhance causal inference by effectively integrating nearest-neighbor matching for action selection.

Grounding economic narratives in real-world data and theory transforms LLM-generated reports from mere text into coherent, traceable economic analyses.

Uncover your LLM's hidden worldviews: this pipeline extracts and visualizes the causal relationships a language model believes to be true.

Forget hand-tuning causal inference pipelines: `genriesz` automates debiased machine learning by intelligently balancing regressors, offering a unified framework for estimating causal effects with statistical guarantees.