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  • 标题:Building an ex-ante simulation model for estimating the capacity impact, benefit incidence, and cost effectiveness of child care subsidies in Turkey
  • 本地全文:下载
  • 作者:Meltem A. Aran ; Ana Maria Munoz-Boudet ; Nazli Aktakke
  • 期刊名称:International Journal of Child Care and Education Policy
  • 电子版ISSN:2288-6729
  • 出版年度:2018
  • 卷号:12
  • 期号:1
  • 页码:1-25
  • DOI:10.1186/s40723-018-0052-3
  • 出版社:Springer Singapore
  • 摘要:Public financing of privately provided child care can allow for access to these services in places where public provision and capacity are low. However, the mechanisms of subsidy delivery will affect who benefits, and the overall cost-effectiveness of such subsidies. This paper sets out an ex-ante simulation model for estimating the benefit incidence of expanded capacity and enrollments resulting from different child care subsidy mechanisms. It combines a supply-side provider level and a demand-side household model in one simulation. The paper considers investment vs. operational monthly grants to child care providers, combinations of investment and operational grants, and demand-side vouchers to households. The model is applied to empirical data from child care centers and households in Turkey. The results reveal that the choice of the subsidy delivery model has a strong bearing on the benefit incidence and cost-effectiveness of the subsidy. In the case of Turkey, where significant supply-side constraints exist in the market, a demand-side voucher system is shown to be the least cost-effective subsidy delivery model. A targeted demand-side voucher does not necessarily deliver the most “pro-poor results,” and combinations show different benefits and costs. The proposed simulation model can be applied in other country contexts, with the only data requirements being microdata on the costs and pricing structure of child care providers, as well as household data with variables on household welfare and child care utilization.
  • 关键词:Day care centers; Subsidies and evidence-based policy; Vouchers; Education finance; Poverty
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