Save More Tomorrow™:: Using behavioral economics to increase employee saving
Save More Tomorrow™:: Using behavioral economics to increase employee saving
复制标题
DOI：
10.1086/380085
复制
发表时间：
2004-02-01
影响因子：
8.2
通讯作者：
Benartzi, S
中科院分区：
文献类型：
--
作者：
Thaler, RH;Benartzi, S
随着公司从固定收益计划转向固定缴款计划，员工在决定存多少钱方面承担了更多的责任。未加入计划或参与程度很低的员工的储蓄率似乎低于预期的生命周期储蓄率。对这种行为的行为解释强调有限理性和自我控制，并表明至少有一些低储蓄家庭正在犯错误，并希望在做出储蓄决定时得到帮助。在本文中，我们提出了这样一个规定性的储蓄计划，称为明天储蓄更多（TM）（以下简称SMartT计划）。该计划的本质很简单：人们提前承诺将未来加薪的一部分用于退休储蓄。我们报告的前三个实施的SMartT计划的证据。我们从第一次实施以来的主要调查结果如下，第一次实施已经进行了四次年度加薪：（1）高比例（78%）提供该计划的人加入了，（2）绝大多数参加SMartT计划的人（80%）在第四次加薪时仍留在公司，（3）在40个月的时间里，SMartT计划参与者的平均储蓄率从3.5%上升到13.6%。研究结果表明，行为经济学可以用来设计有效的处方计划，重要的经济决策。
As firms switch from defined-benefit plans to defined-contribution plans, employees bear more responsibility for making decisions about how much to save. The employees who fail to join the plan or who participate at a very low level appear to be saving at less than the predicted life cycle savings rates. Behavioral explanations for this behavior stress bounded rationality and self-control and suggest that at least some of the low-saving households are making a mistake and would welcome aid in making decisions about their saving. In this paper, we propose such a prescriptive savings program, called Save More Tomorrow(TM) (hereafter, the SMarT program). The essence of the program is straightforward: people commit in advance to allocating a portion of their future salary increases toward retirement savings. We report evidence on the first three implementations of the SMarT program. Our key findings, from the first implementation, which has been in place for four annual raises, are as follows: (1) a high proportion (78 percent) of those offered the plan joined, (2) the vast majority of those enrolled in the SMarT plan (80 percent) remained in it through the fourth pay raise, and (3) the average saving rates for SMarT program participants increased from 3.5 percent to 13.6 percent over the course of 40 months. The results suggest that behavioral economics can be used to design effective prescriptive programs for important economic decisions.