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Revealed Preference Analysis of Characteristics Models

机译:特征模型的显示偏好分析

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Characteristics models have been found to be useful in many areas of economics. However, their empirical implementation tends to rely heavily on functional form assumptions. In this paper we develop a revealed preference approach to characteristics models. We derive the necessary and sufficient empirical conditions under which data on the market behaviour of heterogeneous, price-taking consumers are non-parametrically consistent with the consumer characteristics model. Where these conditions hold, we show how information may be recovered on individual consumers' marginal valuations of product attributes. In some cases, marginal valuations are point identified, and in other cases, we can only recover bounds. Where the conditions fail, we highlight the role which the introduction of unobserved product attributes can play in rationalizing the data. We implement these ideas using consumer panel data on the Danish milk market.
机译:已经发现特征模型在许多经济学领域中是有用的。但是,它们的经验实现往往严重依赖于功能形式的假设。在本文中,我们开发了一种针对特征模型的显式偏好方法。我们推导出了必要的和充分的经验条件,在这些条件下,关于异类,采取价格行为的消费者的市场行为的数据与消费者特征模型非参数一致。在这些条件成立的情况下,我们将说明如何从单个消费者对产品属性的边际估值中获取信息。在某些情况下,边际评估是点识别的,而在其他情况下,我们只能恢复界限。当条件失败时,我们重点介绍引入未观察到的产品属性可以在合理化数据中发挥的作用。我们使用丹麦牛奶市场上的消费者面板数据来实现这些想法。

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