4 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 the Gaussian sequence compound decision problem and analyze a Bayesian nonparametric estimator from an empirical Bayes, regret-based perspective. Motivated by sharp result…
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…
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…