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Found 15 papers, 2 papers with code
Bounds on Average Effects in Discrete Choice Panel Data Models
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.
Forecasted Treatment Effects
We consider estimation and inference of the effects of a policy in the absence of a control group.
Approximate Functional Differencing
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).
Robust Estimation and Inference in Panels with Interactive Fixed Effects
We consider estimation and inference for a regression coefficient in panels with interactive fixed effects (i. e., with a factor structure).
Simultaneity in Binary Outcome Models with an Application to Employment for Couples
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.
Bounding Treatment Effects by Pooling Limited Information across Observations
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.
Linear Panel Regressions with Two-Way Unobserved Heterogeneity
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.
Dynamic Ordered Panel Logit Models
This paper studies a dynamic ordered logit model for panel data with fixed effects.
Low-Rank Approximations of Nonseparable Panel Models
We provide estimation methods for nonseparable panel models based on low-rank factor structure approximations.
Moment Conditions for Dynamic Panel Logit Models with Fixed Effects
This paper investigates the construction of moment conditions in discrete choice panel data with individual specific fixed effects.
Bias and Consistency in Three-way Gravity Models
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.
Posterior Average Effects
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.
Nuclear Norm Regularized Estimation of Panel Regression Models
We propose two new estimation methods that are based on minimizing convex objective functions.
Minimizing Sensitivity to Model Misspecification
We propose a framework for estimation and inference when the model may be misspecified.
Inference on a Distribution from Noisy Draws
We consider a situation where the distribution of a random variable is being estimated by the empirical distribution of noisy measurements of that variable.
