Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/241897 
Year of Publication: 
2020
Series/Report no.: 
cemmap working paper No. CWP22/20
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
We provide a finite sample inference method for the structural parameters of a semiparametric binary response model under a conditional median restriction originally studied by Manski (1975, 1985). Our inference method is valid for any sample size and irrespective of whether the structural parameters are point identified or partially identified, for example due to the lack of a continuously distributed covariate with large support. Our inference approach exploits distributional properties of observable outcomes conditional on the observed sequence of exogenous variables. Moment inequalities conditional on this size n sequence of exogenous covariates are constructed, and the test statistic is a monotone function of violations of sample moment inequalities. The critical value used for inference is provided by the appropriate quantile of a known function of n independent Rademacher random variables. Simulation studies compare the performance of the test to two alternative tests using an infeasible likelihood ratio statistic and Horowitz's (1992) smoothed maximum score estimator.
Subjects: 
Finite sample inference
Maximum score estimation
Moment inequalities
Partial identification
JEL: 
C12
C14
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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