时间偏好与肥胖:来自印度城市的证据

IF 4.5 3区 经济学 Q1 AGRICULTURAL ECONOMICS & POLICY
Archana Dang
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引用次数: 0

摘要

这篇文章探讨了代理人的行为属性(或时间偏好)与肥胖问题之间的关系,以及更普遍的营养过剩和营养不足问题。通过在德里西部进行的初步调查,收集了参与者的食物选择和体重指数数据。时间偏好,如(β, δ ${{\beta}},{{\delta}}$)准双曲折现模型所假定的那样,是通过一个激励的、基于选择的实验得出的。通过同时估算双方程模型,文章发现样本中β值和/或δ值较低(或时间偏好较高)的个体会做出不健康的食物选择,这反过来又显著增加了他们的BMI。此外,一项补充的实证研究分析了一个大型的二级单位记录数据集,以储蓄作为时间偏好的代表,以提供证据证明这些行为属性也解释了体重不足的问题(与发展中国家密切相关)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time preferences and obesity: Evidence from urban India

This article examines the relationship between agents’ behavioral attributes (or time preferences) and the problem of obesity and, more generally, problems of both overnutrition and undernutrition. Through a primary survey in western Delhi data were gathered on participants’ food choices and body mass index. Time preferences, as posited by the ( β , δ ${{\beta}},{{\delta}}$ ) quasi-hyperbolic discounting model, were elicited using an incentivized, choice-based experiment. Estimating a simultaneous two-equation model, the article finds that individuals in the sample with lower β and/or lower δ (or higher time preferences) make unhealthy food choices, which, in turn, significantly increases their BMI. In addition, a supplementary empirical exercise analyzes a large, secondary unit record data set, with savings as a proxy for time preferences, to provide evidence that these behavioral attributes also explain the problem of underweight (germane in developing countries).

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来源期刊
Agricultural Economics
Agricultural Economics 管理科学-农业经济与政策
CiteScore
7.30
自引率
4.90%
发文量
62
审稿时长
3 months
期刊介绍: Agricultural Economics aims to disseminate the most important research results and policy analyses in our discipline, from all regions of the world. Topical coverage ranges from consumption and nutrition to land use and the environment, at every scale of analysis from households to markets and the macro-economy. Applicable methodologies include econometric estimation and statistical hypothesis testing, optimization and simulation models, descriptive reviews and policy analyses. We particularly encourage submission of empirical work that can be replicated and tested by others.
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