6 citations · 7 across the 7 of their papers we have counts for
7 papers
Empirical Likelihood with Generative AI
Jiguang Li, Sid Kankanala, Veronika Rockova
Moment conditions are widely used to identify parameters in models where the full likelihood is either unknown or intentionally left unspecified. Empirical likelihood methods addre…
Compound decisions and empirical Bayes via Bayesian nonparametrics
Nikolaos Ignatiadis, Sid Kankanala
We study compound decision theory from a nonparametric Bayesian perspective, with particular emphasis on their relationship to empirical Bayes (EB) procedures. Motivated by the sha…
Generalized Bayes in Conditional Moment Restriction Models
Sid Kankanala
This paper develops a generalized (quasi-) Bayes framework for conditional moment restriction models, where the parameter of interest is a nonparametric structural function of endo…
On Gaussian Process Priors in Conditional Moment Restriction Models
Sid Kankanala
This paper studies quasi Bayesian estimation and uncertainty quantification for an unknown function that is identified by a nonparametric conditional moment restriction. We derive…
Quasi-Bayes in Latent Variable Models
Sid Kankanala
Latent variable models are widely used to account for unobserved determinants of economic behavior. This paper introduces a quasi-Bayes approach to nonparametrically estimate a lar…
Kernel-weighted specification testing under general distributions
Sid Kankanala, Victoria Zinde-Walsh
Kernel-weighted test statistics have been widely used in a variety of settings including non-stationary regression, inference on propensity score and panel data models. We develop…
Adaptive Estimation and Uniform Confidence Bands for Nonparametric Structural Functions and Elasticities
Xiaohong Chen, Timothy Christensen, Sid Kankanala
We introduce two data-driven procedures for optimal estimation and inference in nonparametric models using instrumental variables. The first is a data-driven choice of sieve dimens…