2019/04/17 by Kyungchul Song, Song, Kyungchul
Mathematics · Physics and Astronomy · Social Sciences · #62F99 #62G99 #62P20 #62P25 #Electoral Systems and Political Participation #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Inference #Theoretical and Computational Physics #msc:62F99 #msc:62G99 #msc:62P20 #msc:62P25 #stat.ME
paper · pdf · doi:10.48550/arxiv.1904.08538
openalex publication_date 2019/04/17 · arxiv created 2022/05/16 · arxiv updated 2022/05/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Diffusion over a network refers to the phenomenon of a change of state of a cross-sectional unit in one period leading to a change of state of its neighbors in the network in the next period. One may estimate or test for diffusion by estimating a cross-sectionally aggregated correlation between neighbors over time from data. However, the estimated diffusion can be misleading if the diffusion is confounded by omitted covariates. This paper focuses on the measure of diffusion proposed by He and Song (2022), provides a method of decomposition analysis to measure the role of the covariates on the estimated diffusion, and develops an asymptotic inference procedure for the decomposition analysis in such a situation. This paper also presents results from a Monte Carlo study on the small sample performance of the inference procedure.