4 citations · 4 across the 1 of their papers we have counts for
3 papers
econ.EM2026
Efficient difference-in-differences estimation under partial interference with incremental propensity score policies
Junjie Li, Yukitoshi Matsushita
This paper develops efficient difference-in-differences (DID) estimation under partial interference with a cluster incremental propensity score (CIPS) policy. We define direct and…
econ.EM2025
A difference-in-differences estimator by covariate balancing propensity score
Junjie Li, Yukitoshi Matsushita
This article develops a covariate balancing approach for the estimation of treatment effects on the treated (ATT) in a difference-in-differences (DID) research design when panel da…
cs.IR2024★ 4 cited
A Unified Search and Recommendation Framework Based on Multi-Scenario Learning for Ranking in E-commerce
Jinhan Liu, Qiyu Chen, Junjie Xu +3
Search and recommendation (S&R) are the two most important scenarios in e-commerce. The majority of users typically interact with products in S&R scenarios, indicating the need and…