Predicting Retirement Savings Using Survey Measures of Exponential-Growth Bias and Present Bias
By Gopi Shah Goda (Stanford University), Matthew Levy (London School of Economics & Political Science (LSE) – Department of Economics), Colleen Flaherty Manchester (University of Minnesota), Aaron Sojourner (University of Minnesota; IZA Institute of Labor Economics), Joshua Tasoff (Claremont Colleges – Claremont Graduate University)
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.