5 papers · 1 filter
Orthogonal Moments in Likelihood Models
Stéphane Bonhomme, Koen Jochmans, Martin Weidner
Many models, such as fixed-effect models for panel or network data, are hard to estimate because they feature nuisance parameters that are both numerous and estimated imprecisely.…
Higher-Order Neyman Orthogonality in Moment-Condition Models
Stéphane Bonhomme, Koen Jochmans, Whitney K. Newey +1
We construct moment functions that are Neyman-orthogonal to a chosen order in parametric moment condition models involving nuisance parameters. These moment functions reduce sensit…
Back to Feedback: Dynamics and Heterogeneity in Panel Data
Stephane Bonhomme
Many popular estimation methods in panel data rely on the assumption that the covariates of interest are strictly exogenous. However, this assumption is empirically restrictive in…
Moment Restrictions for Nonlinear Panel Data Models with Feedback
Stéphane Bonhomme, Kevin Dano, Bryan S. Graham
Many panel data methods, while allowing for general dependence between covariates and time-invariant agent-specific heterogeneity, place strong a priori restrictions on feedback: h…
A Neyman-Orthogonalization Approach to the Incidental Parameter Problem in Likelihood Models
Stéphane Bonhomme, Koen Jochmans, Martin Weidner
A popular approach to perform inference on a target parameter in the presence of nuisance parameters is to construct estimating equations that are orthogonal to the nuisance parame…