Sharp identification regions in models with convex moment predictions

By Arie Beresteanu, Ilya S. Molchanov, Francesca Molinari. 2010

209 citations recorded by the source corpus.

Subfields: Economics and Econometrics, General Decision Sciences, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d982e561f1762bf7582c40c7e73c08db9b784f36

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In Economics and Econometrics

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Citations in the corpus

Bayesian inference in a class of partially identified models (2016, methodology): “…approach in this paper can be viewed as a sort of Bayesian analogue to the frequentist “random sets” approach (e.g., Beresteanu and Molinari (2008), Beresteanu, Molchanov, and Molinari (2011) and Beresteanu, Molchanov, and Molinari (2012)), in the sense that the posterior concerns the random…”
Discrete games with flexible information structures: an application to local grocery markets (2014, unknown): “1 Electronic copy available at: http://ssrn.com/abstract=1859643”
Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing (2021, background): “…constraint” (9) which can be used to rule out incompatible values of ¯ e In other words, any sharp sensitivity analysis must contend with an infinite number of constraints, which is typically computationally intractable (Beresteanu, Molchanov, and Molinari 2011; Davezies and D’Haultfoeuille 2016).”
Counterfactual Sensitivity and Robustness (2019, methodology): “Our approach has connections with global prior sensitivity in Bayesian analysis (Chamberlain and Leamer, 1976; Leamer, 1982; Berger, 1984), most notably Giacomini, Kitagawa, and Uhlig (2016) and Ho (2018) who consider sets of priors constrained by Kullback–Leibler divergence relative to a default pr”
Testing Many Moment Inequalities (2013, background): “Other prominent examples leading to many moment inequalities are developed in Beresteanu, Molchanov, and Molinari (2011), Galichon and Henry (2011), and Chesher, Rosen, and Smolinski (2013), where moment inequalities are used to provide sharp identification regions for parameters in partially…”