Estimating high-dimensional fixed-effects models
AbstractIn this presentation, I describe an alternative iterative approach for the estimation of linear regression models with high-dimensional fixed-effects, such as large employer–employee datasets. This approach is computationally intensive but imposes minimum memory requirements. I also show that the approach can be extended to nonlinear models and potentially to more than two high-dimensional fixed effects. Note: The presentation is based on a paper that is currently under review at the Stata Journal.
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Bibliographic InfoPaper provided by Stata Users Group in its series DC09 Stata Conference with number 2.
Date of creation: 11 Aug 2009
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-08-16 (All new papers)
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- González de San Román, Ainara & Rebollo-Sanz, Yolanda F., 2014. "An estimation of worker and firm effects with censored data," Economics Discussion Papers 2014-28, Kiel Institute for the World Economy.
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