Seasonality and the female happiness paradox.

Q1 Mathematics Quality & Quantity Pub Date : 2023-02-21 DOI:10.1007/s11135-023-01628-5
David G Blanchflower, Alex Bryson
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Abstract

Most studies tracking wellbeing do not collect data across all the months in a year. This leads to error in estimating gender differences in wellbeing for three reasons. First, there are seasonal patterns in wellbeing (particularly life satisfaction and happiness) which are gendered, so failure to account for those confounds estimates of gender differences over time. Second, studies fielded in discrete parts of the year cannot extrapolate to gender differences in other parts of the year. Making inferences about trends over time is particularly problematic when a survey changes its field survey dates across years. Third, without monthly data, surveys miss big shifts in wellbeing that occur for short periods. This is a problem because women's wellbeing is more variable over short periods of time than men's wellbeing. It also bounces back faster. We show that simply splitting the data by months in a happiness equation generates a positive male coefficient in one subset of months from September to January and a negative coefficient in months February to August. Such a split has no impact on the male coefficients in an anxiety equation. Months matter.

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季节性与女性幸福悖论
大多数跟踪幸福感的研究都没有收集一年中所有月份的数据。这导致在估计幸福感的性别差异时出现误差,原因有三。首先,幸福感(尤其是生活满意度和幸福感)的季节性模式是有性别差异的,因此,如果不考虑这些因素,就会混淆对不同时期性别差异的估计。其次,在一年中不同时期进行的实地研究无法推断出一年中其他时期的性别差异。当一项调查的实地调查日期在不同年份发生变化时,对不同时期的趋势进行推断尤其困难。第三,如果没有月度数据,调查就会遗漏短时间内发生的福利方面的重大变化。这是一个问题,因为女性的幸福感在短时间内比男性的幸福感变化更大。它的反弹速度也更快。我们的研究表明,在幸福方程中简单地将数据按月份分割,就会在 9 月至 1 月的一个子月份中产生正的男性系数,而在 2 月至 8 月的月份中产生负的系数。这种分割对焦虑方程中的男性系数没有影响。月份很重要。
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来源期刊
Quality & Quantity
Quality & Quantity 管理科学-统计学与概率论
CiteScore
4.60
自引率
0.00%
发文量
276
审稿时长
4-8 weeks
期刊介绍: Quality and Quantity constitutes a point of reference for European and non-European scholars to discuss instruments of methodology for more rigorous scientific results in the social sciences. In the era of biggish data, the journal also provides a publication venue for data scientists who are interested in proposing a new indicator to measure the latent aspects of social, cultural, and political events. Rather than leaning towards one specific methodological school, the journal publishes papers on a mixed method of quantitative and qualitative data. Furthermore, the journal’s key aim is to tackle some methodological pluralism across research cultures. In this context, the journal is open to papers addressing some general logic of empirical research and analysis of the validity and verification of social laws. Thus The journal accepts papers on science metrics and publication ethics and, their related issues affecting methodological practices among researchers. Quality and Quantity is an interdisciplinary journal which systematically correlates disciplines such as data and information sciences with the other humanities and social sciences. The journal extends discussion of interesting contributions in methodology to scholars worldwide, to promote the scientific development of social research.
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