This article describes some aspects of maximum score estimation of parameters of multinomial and, especially, binomial choice models. In the context of binomial choice models, strengths and weaknesses of the estimation procedure are discussed, as well as its relation to classical quantile regression estimation and its nonstandard rate of convergence. The benefits of smoothing the score criterion function are also noted.
Binary response models Bootstrap Central limit theorems Heteroskedasticity Linear median regression Maximum likelihood Maximum score methods Multinomial choice models Quantile regression Random utility maximization Semiparametric estimation
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