10 citations · 28 across the 20 of their papers we have counts for
7 papers · 1 filter
Single-Network Finite-Sample Inference in Strategic Network Formation Models
Wayne Yuan Gao, Ming Li
We develop a finite-sample valid inference procedure for strategic network formation models with endogenous network statistics, using only a single observed network. We impose no r…
Variance or Standard Deviation? Shell Geometry and Global-Scale Priors in High-Dimensional Shrinkage
Wayne Yuan Gao, Zhiheng You
We study how the choice of default prior for a common Gaussian scale affects high-dimensional shrinkage risk, highlighting the role played by high-dimensional geometry. Formally, w…
Identification in Dynamic Dyadic Network Formation Models with Fixed Effects
Wayne Yuan Gao, Yi Niu
This paper establishes (set) identification results in a dynamic dyadic network formation model with time-varying observed covariates, lagged local network statistics, and unobserv…
When "Normalization Without Loss of Generality" Loses Generality
Wayne Gao
Normalization is ubiquitous in economics, and a growing literature shows that ``normalizations'' can matter for interpretation, counterfactual analysis, misspecification, and infer…
Tractable Identification of Strategic Network Formation Models with Unobserved Heterogeneity
Wayne Yuan Gao, Ming Li, Zhengyan Xu
We develop a tractable identification approach for strategic network formation models with both strategic link interdependence and individual unobserved heterogeneity (fixed effect…
Model Restrictiveness in Functional and Structural Settings
Drew Fudenberg, Wayne Yuan Gao, Zhiheng You
We extend the restrictiveness measure of Fudenberg, Gao & Liang (2026) to functional and structural econometric settings using Gaussian process priors. We find that models evaluate…
How Well Do LLMs Predict Human Behavior? A Measure of their Pretrained Knowledge
Wayne Gao, Sukjin Han, Annie Liang
Large language models (LLMs) are increasingly used to predict human behavior. We propose a measure for evaluating how much knowledge a pretrained LLM brings to such a prediction: i…