Monotone instrumental variables: With an application to the returns to schooling
Monotone instrumental variables: With an application to the returns to schooling
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DOI：
10.1111/1468-0262.00144
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发表时间：
2000-07-01
期刊：
影响因子：
6.1
通讯作者：
Pepper, JV
中科院分区：
文献类型：
--
作者：
Manski, CF;Pepper, JV
治疗反应的计量经济学分析通常使用工具变量（IV）假设来确定治疗效果。然而，IV假设的可信度往往是一个相当大的分歧问题，有很多争论是否一些协变量是或不是一个“有效的工具”，在一个感兴趣的应用程序。因此，有充分的理由考虑较弱但更可信的假设。假设。为此，我们引入单调工具变量（MIV）一个特别有趣的特殊情况下的MIV假设是单调治疗选择（MTS）。IV和MIV假设可以单独使用，也可以与其他假设结合使用。我们研究了MIV假设在三种信息环境中的识别能力：MIV单独; MIV与经典线性反应假设相结合; MIV与单调治疗反应（MTR）假设相结合。我们将结果应用于对学校教育回报的推断问题。我们分析了由白色男性受访者向全国青年纵向调查（NLSY）报告的工资数据，并使用受访者的AFQT评分作为MIV。我们发现，这种MIV假设没有识别力时，单独施加。然而，将MIV假设与MTR和MTS假设相结合，对两种不同的教育回报措施产生了相当严格的限制。
Econometric analyses of treatment response commonly use instrumental variable (IV) assumptions to identify treatment effects. Yet the credibility of IV assumptions is often a matter of considerable disagreement, with much debate about whether some covariate is or is not a "valid instrument" in an application of interest. There is therefore good reason to consider weaker but more credible assumptions. assumptions. To this end, we introduce monotone instrumental variable (MIV) A particularly interesting special case of an MIV assumption is monotone treatment selection (MTS). IV and MIV assumptions may be imposed alone or in combination with other assumptions. We study the identifying power of MIV assumptions in three informational settings: MIV alone; MIV combined with the classical linear response assumption; MIV combined with the monotone treatment response (MTR) assumption. We apply the results to the problem of inference on the returns to schooling. We analyze wage data reported by white male respondents to the National Longitudinal Survey of Youth (NLSY) and use the respondent's AFQT score as an MIV. We find that this MIV assumption has little identifying power when imposed alone. However combining the MIV assumption with the MTR and MTS assumptions yields fairly tight bounds on two distinct measures of the returns to schooling.