Date of this Version
I study the optimal default saving rate in automatic enrollment retirement saving plans. If individuals tend to procrastinate to make an active decision, the optimal de-fault rate should be high to encourage people to opt out of the default. If individuals tend to actively undersave, the optimal default rate should be low to encourage people to stay at the default. Using an exogenous increase in the default savings rate in OregonSaves, the ﬁrst state-sponsored auto-enrollment plan in U.S., I estimate individual adherence to the default rate. Combining individual-level administrative data with survey data, I suggest that the optimal default savings rate 8%.
state-sponsored retirement plans, automatic enrollment, optimal default saving rate, undersaving, inattention
D14, D60, D91, G51, H00
Working Paper Number
Mingli Zhong is a postdoctoral fellow at the National Bureau of Economic Research (NBER).
The findings and conclusions are solely those of my own and do not represent the views of SSA, any agency of the federal government, the MRRC, OregonSaves, or any other institutions with which I am affiliated. ©2020 Zhong. All rights reserved.
I am extremely grateful to my advisors Hanming Fang, Benjamin Lockwood, and Olivia S. Mitchell for their guidance and support, and to Mike Abito, Douglas Bernheim, Judd Kessler, Corinne Low, Sendhil Mullainathan, James Poterba, Juuso Toikka, Alex Rees-Jones, Jonathan Reuter, Katja Seim, and Lin Shen for comments and discussions. I also thank participants at the Wharton Applied Economics Workshop and the 21st Annual SSA Research Consortium Meeting for helpful comments. This research was supported by a grant from the US Social Security Administration (SSA) to the Michigan Retirement Research Center (MRRC) as part of the Retirement Research Consortium (RRC). Support was also provided by the AARP; the Pew Foundation; the Pension Research Council/Boettner Center of the Wharton School at the University of Pennsylvania; and the Quartet program at the University of Pennsylvania. I thank many individuals from the OregonSaves program for numerous discussions and insights into the OS program, and Yong Yu as well as Wenliang Hou for excellent research assistance.
Date Posted: 08 January 2020