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- W2597102657 abstract "The problem of demand inversion -- a crucial step in the estimation of randomutility discrete-choice models -- is equivalent to the determination of stable outcomes intwo-sided matching models. This equivalence applies to random utility models that are notnecessarily additive, smooth, nor even invertible. Based on this equivalence, algorithmsfor the determination of stable matchings provide e ffective computational methods forestimating these models. For non-invertible models, the identifi ed set of utility vectorsis a lattice, and the matching algorithms recover sharp upper and lower bounds on theutilities. For invertible models, our matching approach facilitates estimation of models thatwere previously dicult to estimate, such as the pure characteristics model. An empiricalapplication to voting data from the 1999 European Parliament elections illustrates thegood performance of our matching-based demand inversion algorithms in practice." @default.
- W2597102657 created "2017-03-23" @default.
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- W2597102657 date "2017-01-01" @default.
- W2597102657 modified "2023-09-23" @default.
- W2597102657 title "Yogurts Choose Consumers? Identification of Random Utility Models via Two-Sided Matching" @default.
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- W2597102657 doi "https://doi.org/10.2139/ssrn.2928876" @default.
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