A simple feasible procedure to fit models with high-dimensional fixed effects
In this article, we describe an iterative approach for the estimation of linear regression models with high-dimensional fixed effects. This approach is computationally intensive but imposes minimum memory requirements. We also show that the approach can be extended to nonlinear models and to more than two high-dimensional fixed effects. Copyright 2010 by StataCorp LP.
Volume (Year): 10 (2010)
Issue (Month): 4 (December)
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References listed on IDEAS
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