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The more, the better: Life Satisfaction in the bitter welfare state

机译：越多越好：苦福利国家的生活满意度

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The subject of the welfare state is the object of a critical debate in the context of current global economic turmoil. An important issue surrounding this topic is whether people truly thrive in the welfare state or is they better off without it. Recently, there has been a growing interest in measuring the quality of life using subjective well-being indicators in order to complement the perspective offered by objective well-being indicators. These indicators are perceived as being an increasingly important component of human welfare, as they are not only an assessment of a person's life, but can also serve as a means to improve one's life. The objective of this research is to provide empirical evidence for the existence of a positive relationship between social expenditure and life satisfaction. Based on the happiness economics literature, the current paper distinguishes itself by examining the connection between life satisfaction, as a proxy for wellbeing, and social expenditure. The paper contributes by examining the link between well-being and social expenditure components to offer a more holistic view on the subject at hand. Given the structure of the data, a dynamic panel data model with 'small T, large N', we involve a GMM methodological framework. We use this approach mainly because estimators like random and fixed effects, or even standard GMM, may turn up biased results. We use a two-step expanded system estimator (System GMM) which features a set of supplementary restrictions applied to the already existing ones in the process generating the dependent variable. We use a dataset of 21 European countries covering a time span between 2004 and 2011.
机译：福利国家的主题是当前全球经济动荡的背景下的批判性辩论的目的。围绕这一主题的一个重要问题是人们是否真正在福利状态中茁壮成长，或者他们没有它更好。最近，利用主观福祉指标衡量生活质量越来越兴趣，以补充客观福祉指标所提供的视角。这些指标被认为是人类福利日益重要的组成部分，因为它们不仅是对一个人的生命的评估，而且还可以作为改善一个人的生命的手段。本研究的目的是为社会支出和生活满意度之间存在积极关系的实证证据。基于幸福经济学文献，目前的论文通过检查生活满意度与健康和社会支出的代理之间的联系来区分自己。本文通过审查福祉和社会支出组件之间的联系，为手头的主题提供更全面的观点。鉴于数据的结构，带有“小T，大n”的动态面板数据模型，我们涉及GMM方法框架。我们使用这种方法主要是因为估算器，如随机和固定效果，甚至标准GMM，可能会出现偏见的结果。我们使用两步扩展系统估计器（系统GMM），其特征在于生成从属变量的过程中，它具有应用于已经存在的数据集的一组补充限制。我们使用21个欧洲国家的数据集，涵盖2004年至2011年之间的时间跨度。

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