Predicting Retirement Savings Using Survey Measures of Exponential-Growth Bias and Present Bias

Gopi Goda, Matthew Levy (), Colleen Flaherty Manchester (), Aaron Sojourner () and Joshua Tasoff ()
Additional contact information
Matthew Levy: London School of Economics
Colleen Flaherty Manchester: University of Minnesota, Carlson School of Management
Aaron Sojourner: University of Minnesota
Joshua Tasoff: Claremont Graduate University

No 2018-059, Working Papers from Human Capital and Economic Opportunity Working Group

Abstract: In a nationally-representative sample, we predict retirement savings using survey- based elicitations of exponential-growth bias (EGB) and present bias (PB). We find that EGB, the tendency to neglect compounding, and PB, the tendency to value the present over the future, are highly significant and economically meaningful predictors of retirement savings. These relationships hold controlling for cognitive ability, financial literacy, and a rich set of demographic controls. We address measurement error as a potential confound and explore mechanisms through which these biases may operate. Back of the envelope calculations suggest that eliminating EGB and PB would increase retirement savings by approximately 12 percent.

Keywords: household finance; retirement savings; exponential-growth bias; present bias; financial literacy; survey-based elicitations; quasi-hyperbolic discounting (search for similar items in EconPapers)
JEL-codes: C10 C83 D19 D91 (search for similar items in EconPapers)
Date: 2018-08
New Economics Papers: this item is included in nep-age and nep-fle
Note: MIP
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Citations: View citations in EconPapers (1)

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http://humcap.uchicago.edu/RePEc/hka/wpaper/Goda_L ... ponential-growth.pdf First version, August 17, 2018 (application/pdf)

Related works:
Journal Article: PREDICTING RETIREMENT SAVINGS USING SURVEY MEASURES OF EXPONENTIAL‐GROWTH BIAS AND PRESENT BIAS (2019)
Working Paper: Predicting Retirement Savings Using Survey Measures of Exponential-Growth Bias and Present Bias (2018)
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