We consider the one-to-one matching model with transfers of Choo and Siow (2006) and Galichon and Salani\'e (2015). When the analyst has data on one large market only , we study  identification of the systematic components of the agents' preferences without imposing parametric  restrictions on the probability distribution of the latent variables . We provide a tractable characterisation of the sharp identified set  , under various classes of nonparametric distributional assumptions on the unobserved terms. Simulations suggest that the model can be informative about the sign and magnitude of the systematic components of the agents' preferences, under different nonparametric distributional restrictions. We also discuss a way to conduct inference on the sharp identified set. We use our methodology to investigate if the variations in marriage matching patterns observed over time in the U.S. are caused by changes in the agents' preferences for assortativeness in education .
 When the analyst has data on one large market , we study partial identification of the preference parameters in models of one-to-one matching with transfers without imposing parametric distributional restrictions on the agents' unobserved characteristics . We provide a tractable characterisation of the sharp identified set and discuss inference , under various classes of nonparametric distributional assumptions on the agents' unobserved characteristics. We use our methodology to test if the variations in marriage matching patterns observed over time in the U.S. are caused by changes in the agents' preferences for education assortativeness or by a shift in the proportion of educated women .
D
We consider the one-to-one matching model with transfers of Choo and Siow (2006) and Galichon and Salani\'e (2015).
D
only
A
partial
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systematic components of the agents' preferences
preference parameters in models of one-to-one matching with transfers
A
distributional
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probability distribution of the latent variables
agents' unobserved characteristics
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and discuss inference
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unobserved terms. Simulations suggest that the model can be informative about the sign and magnitude of the systematic components of the agents' preferences, under different nonparametric distributional restrictions. We also discuss a way to conduct inference on the sharp identified set. We
agents' unobserved characteristics. We
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investigate
test
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assortativeness in education
education assortativeness or by a shift in the proportion of educated women