取决于规模的儿童保育政策的再分配效应

IF 1.9 3区 经济学 Q2 ECONOMICS
Diego Escobar , Jeanne Lafortune , Loris Rubini , José Tessada
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引用次数: 0

摘要

政府经常采取政策来降低工薪家庭的育儿成本,但这些政策可能会扭曲资源分配。我们建立并校准了一个具有企业和家庭异质性的一般均衡模型,并研究了智利的案例,在智利,女性雇员超过 19 人的企业必须提供托儿服务。我们发现,如果取消这一政策,在其一生中平均会增加 2.3% 的消费当量单位的福利。然而,取消该政策并不会转化为国内生产总值的增长,部分原因是劳动力供应减少。相反,该政策的主要影响是重新分配,将资源从女性转向男性。该政策降低了大多数女性的福利,而这些损失是随收入递减的。特别是那些不依赖第二份工资的低学历单身女性,如果取消该政策,她们将获得高达 20% 的消费当量单位。我们建议采用其他托儿融资方案。具体来说,通过劳动税为儿童保育提供资金将使总福利增加 13% 以上,其中单身、低学历母亲的收益最大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The redistributive effects of size-dependent childcare policies

Governments often adopt policies to reduce the cost of childcare for working families, but those can distort the allocation of resources. We develop and calibrate a general equilibrium model with firm and household heterogeneity and study the case of Chile, where firms with more than 19 female employees must provide childcare. We find that removing this policy would increase welfare on average by 2.3% of consumption equivalent units over their lifetime. However, the removal would not translate into increases in GDP, in part because of a reduced labor supply. Instead, the main effects of the policy are redistributive, shifting resources away from females towards males. The policy reduces welfare for most females, and these losses are decreasing in income. In particular, low-education single females, who do not rely on a second wage, would gain up to 20% in consumption equivalent units by removing the policy. We propose that alternative childcare financing options would be preferred. Specifically, financing childcare through labor taxes would increase aggregate welfare by over 13%, with the largest gains accruing to single, low-education mothers.

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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
199
期刊介绍: The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.
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