Inference for identifiable parameters in partially identified econometric models

By Joseph P. Romano, A. Shaikh. 2006

243 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Marketing

View Paper: https://www.semanticscholar.org/paper/3b51f2ec0c6f3290aaf70f22dd33eac479c80d3e

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Citations in the corpus

Discrete games with flexible information structures: an application to local grocery markets (2014, methodology): “Instead, I approximate this distribution and use it for inference using the weighted 23See Romano and Shaikh (2006, 2008) for more on subsampling in this context.”
Asymptotically Efficient Estimation of Models Defined by Convex Moment Inequalities (2014, background): “The set of tangent, or supporting, hyperplanes can in turn be identified with a unique function on the unit sphere called the support function of the identified set (Rockafellar, 1970).”
Inference in Nonparametric Instrumental Variables With Partial Identification (2012, methodology): “This type of equivalence was originally used in Romano & Shaikh (2006a) to derive confidence regions for functions of the identifiable parameters and is similar in spirit to the Anderson & Rubin test (1949).”
Set Identified Linear Models (2011, background): “The next contribution of the paper is to provide a simple estimator of the support function of the identified set.”
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).”
Confidence Sets for Partially Identified Parameters that Satisfy a Finite Number of Moment Inequalities (2006, background): “(cid:18) is diagonal include both the mean with missing data and regression with censored outcomes such as those considered by Beresteanu and Molinari (2008), Manski and Tamer (2002), and Romano and Shaikh (2006).”
VALIDITY OF SUBSAMPLING AND “PLUG-IN ASYMPTOTIC” INFERENCE FOR PARAMETERS DEFINED BY MOMENT INEQUALITIES (2009, methodology): “The closest papers are those of Romano and Shaikh (2005, 2008).”
Control of the false discovery rate under dependence using the bootstrap and subsampling (2008, methodology): “The standard errors in the bootstrap world, σ̂ ∗ n,j , use the corresponding ‘natural’ variance estimator; for details, see Götze and Künsch (1996) or Romano and Wolf (2006). The choice of the block sizes for the circular bootstrap is detailed in Romano et al.”
Inference for Parameters Defined by Moment Inequalities Using Generalized Moment Selection (2007, unknown): “This type of statistic has been considered in CHT, AG4, Romano and Shaikh (2005a,b), and Soares (2005). Note that S1 normalizes the moment functions by dividing by σj in each summand.”
A practical two-step method for testing moment inequalities (2014, unknown): “As in Romano and Shaikh (2008), we refer to such sets as confidence regions for identifiable parameters that are uniformly consistent in level to distinguish them from confidence regions satisfying the weaker coverage requirement”
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.”
Set identification via quantile restrictions in short panels (2009, methodology): “…the number of inequality restrictions that define the identified set are finite, and potentially applicable methods include those of Andrews and Soares (2007), Beresteanu and Molinari (2008), Bugni (2007), Canay (2007), CHT, Galichon and Henry (2009), Romano and Shaikh (2008), and Rosen (2008).”
A Test of Non-Identifying Restrictions and Confidence Regions for Partially Identified Parameters (2009, unknown): “Romano and Shaikh (2006a) and Romano and Shaikh (2006b) give high level conditions for uniformity of sub-sampling procedures in the criterion-based approach, with specific conditions under which these results hold in case of regression with interval outcomes.”