EL inference for partially identified models: Large deviations optimality and bootstrap validity

By Ivan A. Canay. 2010

201 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/a14e466e952bade4a21d681e30edf15ae24095ed

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In Control and Systems Engineering

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Citations in the corpus

Partial identification using random set theory (2010, methodology): “In the case of sharp identification regions of type (b) with unconditional moment inequalities, test of hypothesis and confidence statements can be carried out using the methods proposed by Chernozhukov, Hong, and Tamer (2007), Andrews and Soares (2010), Bugni (2010) and Canay (2010), among others.”
Adaptive test of conditional moment inequalities (2011, background): “The list of published papers on unconditional moment inequalities includes Chernozhukov et al. (2007), Romano and Shaikh (2008), Rosen (2008), Andrews and Guggenberger (2009), Andrews and Han (2009), Andrews and Soares (2010), Bugni (2010), Canay (2010), Pakes (2010), and Romano and Shaikh (2010).”
Weighted KS Statistics for Inference on Conditional Moment Inequalities (2011, background): “Indeed, the lack of such results has motivated interest in large deviations optimality (Canay, 2010), which are of particular interest when local power comparisons do not give a clear recommendation.”
Specification tests for partially identified models defined by moment inequalities (2013, background): “(2.9) have been proposed by Romano and Shaikh (2008); Andrews and Guggenberger (2009); Andrews and Soares (2010); Canay (2010); and Bugni (2010), among others.”
Nonparametric Analysis of Random Utility Models (2016, methodology): “With more than two goods, pairwise testing of a stochastic analog of WARP amounts to testing a necessary but not sufficient condition for stochastic rationalizability. This is explored by Hoderlein and Stoye (2014) in a setting that is otherwise ours and also on the same data. Kawaguchi (2017) tests”
Inference on Causal and Structural Parameters using Many Moment Inequalities (2013, background): “…(unconditional) moment inequalities is large; see White (2000), Chernozhukov, Hong, and Tamer (2007), Romano and Shaikh (2008), Rosen (2008), Andrews and Guggenberger (2009), Andrews and Soares (2010), Canay (2010), Bugni (2011), Andrews and Jia-Barwick (2012), and Romano, Shaikh, and Wolf (2014).”
Sensitivity Analysis in Semiparametric Likelihood Models (2011, background): “…(1981) establishes consistency of the parametric MLE without assuming that it is uniquely identified, and Liu and Shao (2003) obtain the 2See also the papers of Rosen (2008), Bugni (2010), Canay (2010), Chernozhukov, Lee, and Rosen (2009), Andrews and Shi (2010) and other papers referenced therein.”
Inference on endogenously censored regression models using conditional moment inequalities (2009, background): “Other papers that consider moment inequalities are Andrews and Soares (2007), Canay (2007) and references therein.”
PARTIAL IDENTIFICATION OF THE DISTRIBUTION OF TREATMENT EFFECTS AND ITS CONFIDENCE SETS (2009, background): “…belongs to the recently fast growing area of inference for partially identified parameters, see for example, Imbens and Manski (2004), Bugni (2007), Canay (2007), Chernozhukov, Hong, and Tamer (2007), Galichon and Henry (2006), Horowitz and Manski (2000), Romano and Shaikh (2008), Stoye (2008),…”
Testing Many Moment Inequalities (2013, background): “…(unconditional) moment inequalities is large; see, for example, Chernozhukov, Hong, and Tamer (2007), Romano and Shaikh (2008), Rosen (2008), Andrews and Guggenberger (2009), Andrews and Soares (2010), Canay (2010), Bugni (2011), Andrews and Jia-Barwick (2012), and Romano, Shaikh, and Wolf (2013).”
Inference on Directionally Differentiable Functions (2014, unknown): “(2007, 2013), Romano and Shaikh (2008, 2010), Bugni (2010), and Canay (2010) among many others.”
Bayesian inference in a class of partially identified models (2016, background): “…approach (e.g., Imbens and Manski (2004), Rosen (2008), Andrews and Guggenberger (2009), Stoye (2009), Andrews and Soares (2010), Bugni (2010), Canay (2010), and Andrews and Barwick (2012)) generally requires working with discontinuous-in-parameters asymptotic (repeated sampling)…”