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Fast Poisson estimation with high-dimensional fixed effects

Sergio Correia (), Paulo Guimaraes () and Thomas Zylkin ()

Stata Journal, 2020, vol. 20, issue 1, 95-115

Abstract: In this article, we present ppmlhdfe, a new command for estimation of (pseudo-)Poisson regression models with multiple high-dimensional fixed effects (HDFE). Estimation is implemented using a modified version of the iteratively reweighted least-squares algorithm that allows for fast estimation in the presence of HDFE. Because the code is built around the reghdfe package (Correia, 2014, Statistical Software Components S457874, Department of Economics, Boston Col- lege), it has similar syntax, supports many of the same functionalities, and benefits from reghdfe’s fast convergence properties for computing high-dimensional least- squares problems. Performance is further enhanced by some new techniques we introduce for accelerating HDFE iteratively reweighted least-squares estimation specifically. ppmlhdfe also implements a novel and more robust approach to check for the existence of (pseudo)maximum likelihood estimates.

Keywords: ppmlhdfe; reghdfe; Poisson regression; high-dimensional fixed effects (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1177/1536867X20909691

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Handle: RePEc:tsj:stataj:v:20:y:2020:i:1:p:95-115