Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/211109 
Erscheinungsjahr: 
2019
Schriftenreihe/Nr.: 
cemmap working paper No. CWP16/19
Verlag: 
Centre for Microdata Methods and Practice (cemmap), London
Zusammenfassung: 
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 sparse case. We provide numerical results for the estimation of teacher value-added models and regressions with occupational dummies.
Schlagwörter: 
connectivity
fixed effects
graph
Laplacian
limited mobility
teacher value-added
two-way regression model
JEL: 
C23
C55
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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