Fast Estimation of Linear and Poisson Models with High-Dimensional Fixed Effects in Python : The FastHDFE package

DOI zum Zitieren der Version auf EPub Bayreuth: https://doi.org/10.15495/EPub_UBT_00009520
URN to cite this document: urn:nbn:de:bvb:703-epub-9520-3

Title data

Larch, Mario ; Schoenfeld, Mirco ; Shikher, Serge:
Fast Estimation of Linear and Poisson Models with High-Dimensional Fixed Effects in Python : The FastHDFE package.
Bayreuth, Germany , 2026 . - 70 P.

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Abstract

We present FastHDFE, an easy-to-install Python package providing the commands reghdfe and ppmlhdfe for estimating linear and multiplicative (Poisson pseudo-maximum-likelihood, PPML) models with high-dimensional fixed effects. They rest on the method of alternating projections and, for PPML, iteratively reweighted least squares, and provide homoskedastic, heteroskedasticity-robust, and multi-way cluster-robust standard errors, detection and removal of separated observations via the iterative rectifier, and singleton handling, with the demeaning step implemented in compiled C code. The commands closely replicate the Stata packages of the same name, reproducing their point estimates to at least six decimal places and the standard errors to at least five decimal places. On the ITPD-E gravity dataset, with roughly 83 million observations and more than four million fixed effects, they run about six to forty-four times faster than Stata while integrating naturally into the Python ecosystem.

Further data

Item Type:	Project report, research report, survey
Additional notes (visible to public):	This is a technical report corresponding to the Python package https://pypi.org/project/fasthdfe
Keywords:	high-dimensional fixed effects, Poisson pseudo-maximum-likelihood, gravity models, method of alternating projections, multi-way clustering, Python, econometric software
Subject classification:	JEL Classification: C13 , C23 , C55 , C87 , F14
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics 500 Science > 510 Mathematics
Institutions of the University:	Faculties > Faculty of Law, Business and Economics > Department of Economics > Chair Economics VI - Empirical Economic Research > Chair Economics VI - Empirical Economic Research - Univ.-Prof. Dr. Mario Larch Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung - Juniorprof. Dr. Mirco Schönfeld Faculties Faculties > Faculty of Law, Business and Economics Faculties > Faculty of Law, Business and Economics > Department of Economics Faculties > Faculty of Law, Business and Economics > Department of Economics > Chair Economics VI - Empirical Economic Research Faculties > Faculty of Languages and Literature Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung
Language:	English
Originates at UBT:	Yes
URN:	urn:nbn:de:bvb:703-epub-9520-3
Date Deposited:	28 Jul 2026 08:20
Last Modified:	29 Jul 2026 05:40
URI:	https://epub.uni-bayreuth.de/id/eprint/9520

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