A Simple Feasible Alternative Procedure to Estimate Models with High-Dimensional Fixed Effects
In this paper we describe an alternative iterative approach for the estimation of linear regression models with high-dimensional fixed-effects such as large employer-employee data sets. This approach is computationally intensive but imposes minimum memory requirements. We also show that the approach can be extended to non-linear models and potentially to more than two high dimensional fixed effects.
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