文章基本信息

标题：Usando as respostas previsíveis da abordagem list-experiments como variáveis explicativas em modelos de regressão
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作者：Kosuke Imai ; Bethany Park ; Kenneth Greene 等
期刊名称：Revista debates
印刷版ISSN：1982-5269
出版年度：2015
卷号：9
期号：1
页码：121-151
语种：Portuguese
出版社：Universidade Federal do Rio Grande do Sul
摘要：The list experiment, also known as the item count technique, is becoming increasingly popular as a survey methodology for eliciting truthful responses to sensitive questions. Recently, multivariate regression techniques have been developed to predict the unobserved response to sensitive questions using respondent characteristics. Nevertheless, no method exists for using this predicted response as an explanatory variable in another regression model. We address this gap by first improving the performance of a naive two-step estimator. Despite its simplicity, this improved two-step estimator can only be applied to linear models and is statistically inefficient. We therefore develop a maximum likelihood estimator that is fully efficient and applicable to a wide range of models. We use a simulation study to evaluate the empirical performance of the proposed methods. We also apply them to the Mexico 2012 Panel Study and examine whether vote-buying is associated with increased turnout and candidate approval. The proposed methods are implemented in open-source software.
关键词：List Experiment;Vote Buying;México 2012.;Lista de Experimento;Compra de Votos;México 2012.