Bayesian inference for partially identified smooth convex models

DOI10.1016/J.JECONOM.2019.03.001zbMath1452.62227OpenAlexW2924086783WikidataQ128128842 ScholiaQ128128842MaRDI QIDQ2000867

Anna Simoni, Yuan Liao

Publication date: 1 July 2019

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2019.03.001

zbMATH Keywords

Bernstein-von Mises theoremsupport functionpartial identificationBayesian credible setsmoment inequality models

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Bayesian inference (62F15)

Related Items (2)

Posterior-based Wald-type statistics for hypothesis testing ⋮ Classical \(p\)-values and the Bayesian posterior probability that the hypothesis is approximately true

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Confidence sets for partially identified parameters that satisfy a finite number of moment inequalities
• The semiparametric Bernstein-von Mises theorem
• Optimal rates of convergence for convex set estimation from support functions
• EL inference for partially identified models: large deviations optimality and bootstrap validity
• Bernstein-von Mises theorems for Gaussian regression with increasing number of regressors
• Bernstein-von Mises theorem for linear functionals of the density
• Bayesian analysis in moment inequality models
• A Bernstein-von Mises theorem for smooth functionals in semiparametric models
• On rates of convergence for posterior distributions in infinite-dimensional models
• Consistent semiparametric Bayesian inference about a location parameter.
• A general projection framework for constrained smoothing.
• Posterior consistency of Dirichlet mixtures in density estimation
• On the behaviour of Bayesian credible intervals in partially identified models
• On the Bernstein-von Mises phenomenon in the Gaussian white noise model
• Bayesian regression with nonparametric heteroskedasticity
• Quasi-Bayesian analysis of nonparametric instrumental variables models
• Coverage probability bias, objective Bayes and the likelihood principle
• Bayesian and Frequentist Inference in Partially Identified Models
• Set Identified Linear Models
• Sharp Identification Regions in Models With Convex Moment Predictions
• VALIDITY OF SUBSAMPLING AND “PLUG-IN ASYMPTOTIC” INFERENCE FOR PARAMETERS DEFINED BY MOMENT INEQUALITIES
• Asymptotic Properties for a Class of Partially Identified Models
• Bootstrap Inference in Partially Identified Models Defined by Moment Inequalities: Coverage of the Identified Set
• Incomplete Simultaneous Discrete Response Model with Multiple Equilibria
• Asymptotic Normality of Semiparametric and Nonparametric Posterior Distributions
• Inference on sets in finance
• Bayesian inference in a class of partially identified models
• Inference for subvectors and other functions of partially identified parameters in moment inequality models
• Semiparametric Inference in Dynamic Binary Choice Models
• Monte Carlo Confidence Sets for Identified Sets
• Inference for Parameters Defined by Moment Inequalities Using Generalized Moment Selection
• Inference for the Identified Set in Partially Identified Econometric Models
• Confidence Intervals for Projections of Partially Identified Parameters
• More on Confidence Intervals for Partially Identified Parameters
• Bayesian and frequentist confidence intervals via adjusted likelihoods under prior specification on the interest parameter
• Asymptotically Efficient Estimation of Models Defined by Convex Moment Inequalities
• Estimation and Confidence Regions for Parameter Sets in Econometric Models
• Inference on Regressions with Interval Data on a Regressor or Outcome
• Confidence Intervals for Partially Identified Parameters
• Convex Analysis

This page was built for publication: Bayesian inference for partially identified smooth convex models