Fixed-Effect Regressions on Network Data

• 成果类型: Article
• 署名作者: Jochmans, Koen; Weidner, Martin
• 署名单位: University of Cambridge; University of London; University College London
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA14605
• 发表日期: 2019
• 页码: 1543-1560
• 关键词: high wage workers; teacher quality; FIRMS

摘要

This paper considers inference on fixed effects in a linear regression model estimated from network data. An important special case of our setup is the two-way regression model. This is a workhorse technique in the analysis of matched data sets, such as employer-employee or student-teacher panel data. We formalize how the structure of the network affects the accuracy with which the fixed effects can be estimated. This allows us to derive sufficient conditions on the network for consistent estimation and asymptotically valid inference to be possible. Estimation of moments is also considered. We allow for general networks and our setup covers both the dense and the sparse case. We provide numerical results for the estimation of teacher value-added models and regressions with occupational dummies.