Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/272829 
Year of Publication: 
2022
Series/Report no.: 
cemmap working paper No. CWP17/22
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
We propose a novel optimal transport-based version of the Generalized Method of Moment (GMM). Instead of handling overidentified models by reweighting the data until all moment conditions are satisfied (as in Generalized Empirical Likelihood methods), this method proceeds by introducing measurement error of the least mean square magnitude necessary to simultaneously satisfy all moment conditions. This approach, based on the notion of optimal transport, aims to address the problem of assigning a logical interpretation to GMM results even when overidentification tests reject the null, a situation that cannot always be avoided in applications. Our approach thus introduces a practical alternative to standard GMM estimation to circumvent concerns regarding overidentification test rejections.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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