Feasible fitting of linear models with N fixed effects
Fernando Rios-Avila
Levy Economics Institute of Bard College
Blithewood-Bard College
Annandale-on-Hudson, NY
[email protected]
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Abstract. In this article, I describe an alternative approach for fitting linear models
with multiple high-order fixed effects. The strategy relies on transforming
the data before fitting the model. While the approach is computationally
intensive, the hardware requirements for the fitting are minimal, allowing for
estimation in models with multiple high-order fixed effects for large
datasets. I illustrate implementing this approach using the U.S. Census Bureau
Current Population Survey data with four fixed effects. I also present a new
Stata command, regxfe, for implementing this strategy.
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Fernando Rios-Avila
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regxfe, itercenter, nredound, fixed-effects models, two-step estimation
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