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 College), it has similar syntax, supports many of the same functionalities, and benefits from reghdfe‘s fast convergence properties for computing high-dimensional leastsquares 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.

在本文中，我们介绍了ppmlhdfe，这是一种用于估计具有多个高维固定效应（HDFE）的（伪）泊松回归模型的新命令。使用迭代重加权最小二乘算法的修改版本实现估算，该算法允许在存在HDFE的情况下进行快速估算。因为该代码是围绕reghdfe软件包构建的（Correia，2014年，波士顿学院经济系，统计软件组件S457874），所以它具有相似的语法，支持许多相同的功能，并受益于reghdfe的快速收敛特性，用于计算高维最小二乘问题。我们引入了一些新技术来进一步提高性能，这些新技术专门用于加速HDFE迭代式重加权最小二乘估计。ppmlhdfe还实现了一种新颖且更强大的方法来检查（伪）最大似然估计的存在。