摘要翻译：
一个大的“幸福”，或生活满意度，经济学文献使用类似Likert的量表来评估调查对象对他们生活的认知评价。在经济学的每一个经验领域中，这些措施都被用来估计经济效益。通常，对这些数据的分析表明，教育对改善主观幸福感的直接回报非常低。此外，可以说，与其他社会因素相比，以及与经济学家先前的预期相比，使用这种方法推断出的物质财富和收入的影响也出乎意料地低，在某种意义上，经济学家先前的预期支持使用国内生产总值作为更普遍的生活质量目标的代理。在生活满意度报告中普遍使用的离散反应量表给调查对象带来了认知挑战，因此不同的认知能力导致了量表的不同使用，从而导致统计推断中的潜在偏差。这个问题到目前为止还没有引起注意。对生活满意度问题的回答分布的一个被忽视的特点是，它们在焦点值上表现出某些增强，特别是在11点量表上的0、5和10。在本文中，我调查了这些反应模式的原因和含义。我使用一个模型来解释焦点价值行为，使用一个潜在变量方法来捕捉“内部”认知评价，然后将其转化为一个调查问题的离散量表。这种方法得到了其他更启发式方法的支持，发现教育和收入对生活满意度的影响显著向上修正。
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英文标题：
《A critique of the econometrics of happiness: Are we underestimating the
  returns to education and income?》
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作者：
Christopher P Barrington-Leigh
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最新提交年份：
2018
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分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
  A large "happiness", or life satisfaction, literature in economics makes use of Likert-like scales in assessing survey respondents' cognitive evaluations of their lives. These measures are being used to estimate economic benefits in every empirical field of economics. Typically, analysis of these data have shown remarkably low direct returns of education for improving subjective well-being. In addition, arguably, the inferred impact of material wealth and income using this method is also unexpectedly low as compared with other, social factors, and as compared with economists' prior expectations which underlie, in some sense, support for using GDP as a proxy for more general quality of life goals. Discrete response scales used ubiquitously for the reporting of life satisfaction pose cognitive challenges to survey respondents, so differing cognitive abilities result in different uses of the scale, and thus potential bias in statistical inference. This problem has so far gone unnoticed. An overlooked feature of the distribution of responses to life satisfaction questions is that they exhibit certain enhancements at focal values, in particular at 0, 5, and 10 on the eleven-point scale. In this paper, I investigate the reasons for, and implications of, these response patterns. I use a model to account for the focal-value behavior using a latent variable approach to capture the "internal" cognitive evaluation before it is translated to the discrete scale of a survey question. This approach, supported by other more heuristic ones, finds a significant upward correction for the effects of both education and income on life satisfaction.
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PDF链接：
https://arxiv.org/pdf/1807.11835