A new paper by Takahide Yanagi introduces methods for estimating treatment effects in dyadic data, even when confounding factors are unknown. The approach leverages graphon estimation from network analysis and proposes a neighborhood kernel smoothing method for estimating average treatment effects. The research also includes conformal inference techniques for outcome prediction and is applied to international trade data to analyze the impact of free trade agreements. AI
RANK_REASON Academic paper on statistical methods. [lever_c_demoted from research: ic=1 ai=0.4]
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
