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Predicting binary outcomes
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DOI：10.1016/j.jeconom.2013.01.003.png)
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We address the issue of using a set of covariates to categorize or predict a binary outcome. This is a common problem in many disciplines including economics. In the context of a prespecified utility (or cost) function we examine the construction of forecasts suggesting an extension of the Manski (1975, 1985) maximum score approach. We provide analytical properties of the method and compare it to more common approaches such as forecasts or classifications based on conditional probability models. Large gains over existing methods can be attained when models are misspecified. (C) 2013 Elsevier B.V. All rights reserved.
Keyword:
MAXIMUM SCORE ESTIMATOR
UNIFORM-CONVERGENCE
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A SMOOTHED MAXIMUM SCORE ESTIMATOR FOR THE BINARY RESPONSE MODEL二元响应模型的平滑最大得分估计器.png)
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