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CAREER: Health Determinants and Research Design

CAREER: Health Determinants and Research Design
职业:健康决定因素和研究设计
批准号:
0847329
负责人:
Douglas Almond
金额:
$61.3万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-10-01 至 2014-09-30

项目摘要

项目成果

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中文摘要
翻译
该奖项是根据2009年美国复苏和再投资法案(公法111-5)资助的。即使在因果途径已经确定,很大的不确定性往往存在的关系的强度。需要对这些关系进行令人信服的精确估计,以便为改善人口健康的公共政策提供信息。该项目将利用自然和准实验来提高对这些关系的理解。 该项目重点介绍了利用斋月研究孕产妇营养的影响、中国取暖补贴的影响以研究污染对产前发育的影响以及阿肯色州肥胖报告卡对肥胖和健康的影响等项目。该CAREER提案认为,可反驳的研究假设可以在观察环境中进行评估,其中识别变异可能是外源性的。 理想情况下,研究假设具有很强的影响,可以在现有的(即预先存在的)数据中进行评估。 最有说服力的实证比较不需要复杂的计量经济学修正。相反,良好的自然实验可以用最小的统计调整来确定治疗效果。最干净的实验是随机分配治疗,只需要比较平均值来估计因果效应。应尽可能仿效这一受控实验。在操作上,所提出的方法旨在发掘在观测环境中的比较,其中未经调整的影响估计是非常相似的回归调整的影响estimation.Broader影响:该项目将通过通常的经济学教学和研究社区以外的合作产生重大影响。例如,研究人员正在与阿肯色州健康中心合作,以确定健康信息如何有助于减少儿童肥胖。国际合作也是不可或缺的,清华大学和北京大学的研究人员拟议对淮河附近的中国空气污染进行研究就说明了这一点。 此外,由于所涉及的健康问题至关重要,政策制定者(和大众媒体)可能会产生浓厚的兴趣。
英文摘要
This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).What determines human health is known only in part. Even where causal pathways have been identified, great uncertainty frequently exists regarding the strength of the relationship. Compelling and precise estimates of these relationships are needed to inform public policies that will improve population health. This project would improve understanding of these relationships, using natural and quasi-experiments. The project highlights projects on the use of Ramadan to study the effects of maternal nutrition, the effects of heating subsidies in China to study the effects of pollution on prenatal development, and the impact of obesity report cards on obesity and health in Arkansas.This CAREER proposal argues that refutable research hypotheses can be evaluated in an observational setting where identifying variation is plausibly exogenous. Ideally, the research hypothesis has strong implications which can be evaluated in available (i.e. pre-existing) data. The most compelling empirical comparisons do not require sophisticated econometric fixes. Instead, good natural experiments can identify treatment effects with minimal statistical adjustment. The cleanest of experiments, where the treatment is randomly assigned, requires only the comparison of means to estimate causal effects. This controlled experiment should be emulated wherever possible. Operationally, the proposed approach seeks to unearth comparisons in an observational setting where unadjusted impact estimates are quite similar to regression-adjusted impact estimates.Broader Impact: The project will have substantial impact through collaborations outside the usual Economics teaching and research communities. For example, the investigator is working with the Arkansas Center for Health to determine how health information might help reduce childhood obesity. International collaboration is also integral, as illustrated by the proposed study of Chinese air pollution near the Huai river with researchers at Tsinghua and Beijing University. Also, because the health questions engaged are vitally important, substantial interest from policymakers (and the popular press) is likely.
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会议论文
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