Asymptotic Properties for a Class of Partially Identified Models

By Arie Beresteanu, Francesca Molinari. 2006

301 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/82decd7741a096c6065ea7e973c99434fcda3469

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In Artificial Intelligence

In Statistics and Probability

Citations in the corpus

Inference for identifiable parameters in partially identified econometric models (2006, background): “Beresteanu and Molinari (2006) propose an alternative approach to inference in partially identified models that is based on the theory of random sets.”
Monte Carlo Confidence Sets for Identified Sets (2016, unknown): “…and Shaikh (2010) where subsampling based methods are used for general partially-identified models, Bugni (2010) and Armstrong (2014) where bootstrap methods are used for moment inequality models, and Beresteanu and Molinari (2008) where random set methods are used when ΘI is strictly convex.”
Semiparametric Inference in Dynamic Binary Choice Models, Second Version (2014, background): “See for example, Manski (2003), Imbens and Manski (2004), Chernozhukov, Hong, and Tamer (2007), Rosen (2008), Stoye (2009), Beresteanu and Molinari (2008), Romano and Shaikh (2010), Andrews and Soares (2010), Canay (2010), Bugni (2010), and Moon and Schorfheide (2012).”
Set Identified Linear Models (2011, methodology): “Interestingly enough, our approach also reveals that the asymptotic results of Beresteanu and Molinari (2008) actually simplify to a quite standard linear model format for the covariance matrix in the case in which the support function is differentiable.”
Partial identification using random set theory (2010, methodology): “= E ( (Πw−1 + λ) ( ψ − w′ −1θ−1 − θ1 )) = 0 (18)Stata code implementing sample analog estimators of these identification regions, along with confidence sets, confidence collections, and test of hypothesis as in Beresteanu and Molinari (2008), is freely downloadable at http://www.”
Confidence Sets for Partially Identified Parameters that Satisfy a Finite Number of Moment Inequalities (2006, background): “…Henry (2006b), Romano and Shaikh (2006), Andrews and Guggenberger (2007), Andrews and Soares (2007), Bontemps, Magnac, and Maurin (2007), Bugni (2007), Canay (2007), Guggenberger, Hahn, and Kim (2008), Fan and Park (2007), Stoye (2007), Beresteanu and Molinari (2008), and Romano and Shaikh (2008).”
Partial identification of spread parameters (2010, background): “This leads to (looser) bounds of the form (4) on P ∗∗ if one can bound P .”
Intersection bounds: estimation and inference (2009, background): “Some examples include Andrews and Jia (2008), Beresteanu and Molinari (2008), Chernozhukov, Hong, and Tamer (2007), Galichon and Henry (2009), Romano and Shaikh (2008), Romano and Shaikh (2009), and Rosen (2008), among others.”
Asymptotically exact inference in conditional moment inequality models (2011, background): “…(2004), Andrews and Jia (2008), Andrews and Guggenberger (2009), Andrews and Soares (2010), Chernozhukov, Hong, and Tamer (2007), Romano and Shaikh (2010), Romano and Shaikh (2008), Bugni (2010), Beresteanu and Molinari (2008), Moon and Schorfheide (2009), Imbens and Manski (2004) and Stoye (2009).”
VALIDITY OF SUBSAMPLING AND “PLUG-IN ASYMPTOTIC” INFERENCE FOR PARAMETERS DEFINED BY MOMENT INEQUALITIES (2009, background): “Other papers in the literature that consider inference with moment inequalities include: CHT, Andrews, Berry, and Jia (2004, 2007), Pakes, Porter, Ho, and Ishii (2004), Moon and Schorfheide (2004), Rosen (2005), Beresteanu and Molinari (2006) , Galichon and Henry (2006), Bugni (2007), and Canay (20”
EL inference for partially identified models: Large deviations optimality and bootstrap validity (2010, methodology): “The methodology used by Beresteanu and Molinari (2008) is a promising direction for this type of analysis.”
Weighted KS Statistics for Inference on Conditional Moment Inequalities (2011, methodology): “Galichon and Henry (2009) propose a similar statistic for a class of models under a different setup with possible lack of point identification. More broadly, this paper relates to the literature on set identified models. Much of this research has been on models defined by finitely many unconditional”
PARTIAL IDENTIFICATION OF THE DISTRIBUTION OF TREATMENT EFFECTS AND ITS CONFIDENCE SETS (2009, background): “…Hong, and Tamer (2007), Galichon and Henry (2006), Horowitz and Manski (2000), Romano and Shaikh (2008), Stoye (2008), Rosen (2008), Soares (2006), Beresteanu and Molinari (2006), Andrews and Guggenberger (2007), Andrews and Soares (2007), Fan and Park (2007b), and Moon and Schorfheide (2007).”