Everything about Fixed-effect Poisson model
Statistical models used for static panel data
In statistics, a fixed-effect Poisson model is a Poisson regression model used for static panel data when the outcome variable is count data. Hausman, Hall, and Griliches pioneered the method in the mid-1980s. Their outcome of interest was the number of patents filed by firms, where they wanted to develop methods to control for the firm fixed effects. Linear panel data models use the linear additivity of the fixed effects to difference them out and circumvent the incidental parameter problem. Even though Poisson models are inherently nonlinear, the use of the linear index and the exponential link function lead to multiplicative separability, more specificallyE[yit ∨ xi1... xiT, ci ] = m(xit, ci, b0 ) = exp(ci + xit b0 ) = ai exp(xit b0 ) = μti (1) Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Fixed-effect Poisson modelA 5-minute orientation
- Skim a recent paper: On robust M, S and MM estimations for the Poisson fixed effects panel model with outliers: simulation and applicationsInfluential work since 2022
- Pick up a classic book: Introduction to Probability and StatisticsThe most-reprinted book on the subject
- Read the landmark paper: Gravity model estimation: fixed effects vs. random intercept Poisson pseudo-maximum likelihoodCited 25 times
- Go sideways: Partial likelihood methods for panel dataA closely related topic
- Go sideways: First-difference estimatorA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
No outline available.
🏆 Landmark papers (most cited)
Gravity model estimation: fixed effects vs. random intercept Poisson pseudo-maximum likelihood
Robust M Estimation for Poisson Panel Data Model with Fixed Effects: Method, Algorithm, Simulation, and Application
🆕 Influential since 2022
📚 Books worth reading
Introduction to Probability and StatisticsJ. Susan Milton, Jesse C. Arnold · 1990- 📕Structural Aspects of Quantum Field Theory and Noncommutative GeometryGerhard Grensing · 2013
Introduction to probability and statisticsJ. Susan Milton, Jesse C. Arnold · 2002- 📕Multivariate generalized linear mixed models using RDamon Berridge · 2011
Statistical methods for drug safetyRobert D. Gibbons · 2016
Foundation designN. S. V. Kameswara Rao · 2011
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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