G2TT
来源类型Discussion paper
规范类型论文
来源IDDP16541
DP16541 The Cognitive Load of Financing Constraints: Evidence from Large-Scale Wage Surveys
Clémence Berson; Claire Lelarge; Raphael Lardeux
发表日期2022-06-04
出版年2022
语种英语
摘要In this paper, we take advantage of the implicit cognitive exercise available in standard Labor Force Surveys in order to provide a new, population-wide quantification of the cognitive load associated with financial constraints (Mullainathan and Shafir, 2013). This quantification is based on a well-defined index of worker-level attention which filters out rounding behavior and reporting biases. We estimate it using unsupervised clustering techniques and find that workers perceive their own wages with a degree of uncertainty of around 10%, which through the lens of a simple rational signal extraction model translates into estimates of workers' attention ranging from 30% to 84% depending on their wage, education, tenure and gender. Most importantly, the attention of the lowest paid 30% of workers is cyclical and increases steadily (by 17 percentage points) in the ten days preceding payday, before immediately dropping on that day. We show theoretically that this pattern is indicative of end-of-month financing (liquidity) constraints. Furthermore, it reveals that these financing constraints induce cognitive costs arising from the not too concave (or convex) costs of achieving high levels of attention, and the convex costs of maintaining them over time. Our model identifies a lower bound for the annual attention cost burden incurred by financially constrained workers, which ranges between 10 and 50 euros depending on risk aversion.
主题Labour Economics
关键词Behavioral inattention Cognitive costs Wage volatility Financing constraints
URLhttps://cepr.org/publications/dp16541-1
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/546404
推荐引用方式
GB/T 7714
Clémence Berson,Claire Lelarge,Raphael Lardeux. DP16541 The Cognitive Load of Financing Constraints: Evidence from Large-Scale Wage Surveys. 2022.
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