Search Results for author:
Found 4 papers, 0 papers with code
On Optimal Set Estimation for Partially Identified Binary Choice Models
We illustrate the general problem in the context of a semiparametric binary choice model with discrete covariates as an example of a model which is partially identified as shown in, e. g. Bierens and Hartog (1988).
Endogeneity in Weakly Separable Models without Monotonicity
We identify and estimate treatment effects when potential outcomes are weakly separable with a binary endogenous treatment.
Estimating High Dimensional Monotone Index Models by Iterative Convex Optimization1
For such monotone index models with increasing dimension, we propose to use a new class of estimators based on batched gradient descent (BGD) involving nonparametric methods such as kernel estimation or sieve estimation, and study their asymptotic properties.
Informational Content of Factor Structures in Simultaneous Binary Response Models
Our main findings are that imposing a factor structure yields point identification of parameters of interest, such as the coefficient associated with the endogenous regressor in the outcome equation, under weaker assumptions than usually required in these models.
