Description/Abstract
This paper considers a spatial lag model with a complete bipartite network weighting matrix which is important in network theory. We show that two-stage least squares is equivalent to ordinary least squares and both estimators are inconsistent for the cross-section data case. This result has also been derived for the spatial lag model with an equal weight matrix by Kelejian and Prucha (2002). We also show that the fixed effects two-stage least squares estimator is consistent in case we have panel data and the spatial lag model includes time fixed effects. This is different from the result for an equal weight matrix derived by Kelejian, Prucha and Yuzefovich (2006).
Document Type
Working Paper
Date
4-22-2025
Keywords
Spatial Lag Model, Two-Stage Least Squares, Ordinary Least Squares, Panel Data, Complete Bipartite Network
Language
English
Series
Working Papers Series
Acknowledgements
We dedicate this paper to the memory of Harry H. Kelejian and his many contributions to econometrics and especially spatial econometrics.
Disciplines
Econometrics | Economics
ISSN
1525-3066
Recommended Citation
Baltagi, Badi H. and Liu, Long, "Two-Stage Least Squares Estimation in a Spatial Lag Model under a Complete Bipartite Network" (2025). Center for Policy Research. 497.
https://surface.syr.edu/cpr/497
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
