首页> 美国卫生研究院文献>PLoS Clinical Trials >A new method of identifying target groups for pronatalist policy applied to Australia
【2h】

A new method of identifying target groups for pronatalist policy applied to Australia

机译:为澳大利亚确定促进生育政策的目标群体的新方法

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

A country’s total fertility rate (TFR) depends on many factors. Attributing changes in TFR to changes of policy is difficult, as they could easily be correlated with changes in the unmeasured drivers of TFR. A case in point is Australia where both pronatalist effort and TFR increased in lock step from 2001 to 2008 and then decreased. The global financial crisis or other unobserved confounders might explain both the reducing TFR and pronatalist incentives after 2008. Therefore, it is difficult to estimate causal effects of policy using econometric techniques. The aim of this study is to instead look at the structure of the population to identify which subgroups most influence TFR. Specifically, we build a stochastic model relating TFR to the fertility rates of various subgroups and calculate elasticity of TFR with respect to each rate. For each subgroup, the ratio of its elasticity to its group size is used to evaluate the subgroup’s potential cost effectiveness as a pronatalist target. In addition, we measure the historical stability of group fertility rates, which measures propensity to change. Groups with a high effectiveness ratio and also high propensity to change are natural policy targets. We applied this new method to Australian data on fertility rates broken down by parity, age and marital status. The results show that targeting parity 3+ is more cost-effective than lower parities. This study contributes to the literature on pronatalist policies by investigating the targeting of policies, and generates important implications for formulating cost-effective policies.
机译:一个国家的总生育率(TFR)取决于许多因素。很难将TFR的变化归因于政策的变化,因为它们很容易与未衡量的TFR驱动因素的变化相关。一个典型的例子是澳大利亚,从2001年到2008年,促孕工作和TFR的增长步调一致,然后又下降。全球金融危机或其他未被观察到的混杂因素可能解释了2008年之后TFR降低和鼓励生育的动机。因此,很难使用计量经济学的方法来估算政策的因果关系。这项研究的目的是查看人口结构,以确定哪些子群对TFR的影响最大。具体而言,我们建立了一个将TFR与各个亚组的受精率相关的随机模型,并针对每个速率计算了TFR的弹性。对于每个子组,使用其弹性与组数的比率来评估该子组作为增生目标的潜在成本效益。此外,我们测量了群体生育率的历史稳定性,从而衡量了变化的倾向。具有高效率比率和较高变革倾向的群体是自然政策目标。我们将这种新方法应用于按性别,年龄和婚姻状况细分的澳大利亚生育率数据。结果表明,针对同等价位3+的广告客户比较低的同价位的广告更具成本效益。这项研究通过调查政策的针对性,为有关孕产妇政策的文献做出了贡献,并对制定具有成本效益的政策产生了重要的启示。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号