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首页> 美国卫生研究院文献>Wiley-Blackwell Online Open >Misreporting and econometric modelling of zeros in survey data on social bads: An application to cannabis consumption
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Misreporting and econometric modelling of zeros in survey data on social bads: An application to cannabis consumption

机译：社会不良调查数据中零的误报和计量经济学建模：大麻消费的应用

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摘要

When modelling “social bads,” such as illegal drug consumption, researchers are often faced with a dependent variable characterised by a large number of zero observations. Building on the recent literature on hurdle and double‐hurdle models, we propose a double‐inflated modelling framework, where the zero observations are allowed to come from the following: nonparticipants; participant misreporters (who have larger loss functions associated with a truthful response); and infrequent consumers. Due to our empirical application, the model is derived for the case of an ordered discrete‐dependent variable. However, it is similarly possible to augment other such zero‐inflated models (e.g., zero‐inflated count models, and double‐hurdle models for continuous variables). The model is then applied to a consumer choice problem of cannabis consumption. We estimate that 17% of the reported zeros in the cannabis survey are from individuals who misreport their participation, 11% from infrequent users, and only 72% from true nonparticipants.
机译：在对“社会弊端”（例如非法毒品消费）进行建模时，研究人员经常面临因变量众多而特征为零的现象。在有关跨栏和双栏模型的最新文献的基础上，我们提出了一种双膨胀模型框架，其中零观察值来自以下各项：参与者误报（与真实反应相关的损失功能更大）；和不常使用的消费者。由于我们的经验应用，该模型是针对有序离散相关变量的情况导出的。但是，同样有可能扩充其他此类零膨胀模型（例如，零膨胀计数模型和连续变量的双栏模型）。然后将该模型应用于大麻消费的消费者选择问题。我们估计大麻调查中报告的零数字中有17％来自错误报告其参与的个人，11％来自不经常使用的用户，只有72％来自真正的未参加者。

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