no code implementations • 17 Sep 2023 • Cavit Pakel, Martin Weidner
In discrete choice panel data, the estimation of average effects is crucial for quantifying the effect of covariates, and for policy evaluation and counterfactual analysis.
no code implementations • 11 Sep 2023 • Irene Botosaru, Raffaella Giacomini, Martin Weidner
We consider estimation and inference of the effects of a policy in the absence of a control group.
no code implementations • 31 Jan 2023 • Geert Dhaene, Martin Weidner
Inference on common parameters in panel data models with individual-specific fixed effects is a classic example of Neyman and Scott's (1948) incidental parameter problem (IPP).
no code implementations • 13 Oct 2022 • Timothy B. Armstrong, Martin Weidner, Andrei Zeleneev
We consider estimation and inference for a regression coefficient in panels with interactive fixed effects (i. e., with a factor structure).
no code implementations • 15 Jul 2022 • Bo E. Honoré, Luojia Hu, Ekaterini Kyriazidou, Martin Weidner
Two of Peter Schmidt's many contributions to econometrics have been to introduce a simultaneous logit model for bivariate binary outcomes and to study estimation of dynamic linear fixed effects panel data models using short panels.
1 code implementation • 9 Nov 2021 • Sokbae Lee, Martin Weidner
Our bounds are designed to be robust in challenging situations, for example, when the conditioning variables take on a large number of different values in the observed sample, or when the overlap condition is violated.
no code implementations • 24 Sep 2021 • Hugo Freeman, Martin Weidner
We discuss two different estimation approaches that allow consistent estimation of the regression parameters in this setting as the number of individuals and the number of time periods grow to infinity.
no code implementations • 7 Jul 2021 • Bo E. Honoré, Chris Muris, Martin Weidner
This paper studies a dynamic ordered logit model for panel data with fixed effects.
no code implementations • 23 Oct 2020 • Iván Fernández-Val, Hugo Freeman, Martin Weidner
We provide estimation methods for nonseparable panel models based on low-rank factor structure approximations.
no code implementations • 12 May 2020 • Bo E. Honoré, Martin Weidner
This paper investigates the construction of moment conditions in discrete choice panel data with individual specific fixed effects.
1 code implementation • 3 Sep 2019 • Martin Weidner, Thomas Zylkin
We study the incidental parameter problem for the ``three-way'' Poisson {Pseudo-Maximum Likelihood} (``PPML'') estimator recently recommended for identifying the effects of trade policies and in other panel data gravity settings.
no code implementations • 14 Jun 2019 • Stéphane Bonhomme, Martin Weidner
For such quantities, we propose and study posterior average effects (PAE), where the average is computed conditional on the sample, in the spirit of empirical Bayes and shrinkage methods.
no code implementations • 25 Oct 2018 • Hyungsik Roger Moon, Martin Weidner
We propose two new estimation methods that are based on minimizing convex objective functions.
no code implementations • 5 Jul 2018 • Stéphane Bonhomme, Martin Weidner
We propose a framework for estimation and inference when the model may be misspecified.
no code implementations • 13 Mar 2018 • Koen Jochmans, Martin Weidner
We consider a situation where the distribution of a random variable is being estimated by the empirical distribution of noisy measurements of that variable.