Saurabh Bhargava (CMU)

March 29, 2017 @ 1:30 pm – 3:00 pm
Roosevelt House Public Policy Institute
47 E 65th St
New York, NY 10065
Karna Basu

Saurabh Bhargava is an Assistant Professor at Carnegie Mellon University.

Seminar topic: “New Field Evidence on Retirement Savings Puzzles”


A persistent challenge for policy-makers, and a theoretical puzzle for the standard economic model, is that a majority of U.S. households enter retirement with too few assets. This savings deficit is surprising given the documented successes of automatic-enrollment in increasing 401(k) plan participation, especially among at-risk employees, and the proliferation of generous matching incentives to encourage employees to save. We review candidate explanations from standard and behavioral models for these puzzles and offer preliminary new insight from two research projects, conducted in collaboration with two US firms, involving a series of natural and field experiments.

The first project (Bhargava and Conell-Price, in progress) investigates the retirement/financial literacy, decision-complexity, institutional trust, and present-bias on savings among lower-earning employees of a Fortune 200 firm.  Preliminary results document gaps in literacy and pockets of low-trust but suggest that such factors contribute only modestly to low-savings.  Instead the evidence implicates present-bias as a significant factor but to an extent that is more consistent with errors in (affective) forecasting rather than typical models of hyperbolic discounting.  A second project (Bhargava, Conell-Price, Mason, and Benartzi, in progress) tests the sensitivity of employee savings to variation in the non-economic features of the online enrollment interface. Preliminary evidence points to the significant influence of “enrollment architecture” on savings decisions, even in the presence of generous matching incentives, and suggests significant heterogeneity in the reliance on non-economic cues across individuals by income, financial sophistication, and decision-making style.  Proposed follow-ups seek to understand how reliance on non-economic cues varies across the informational complexity of the decision-settings.

Collectively, the projects offer a set of concrete, low-cost, and highly scalable strategies through which policy/program designers might encourage savings, particularly among at-risk populations that appear less responsive to traditional incentives, and new theoretical insights into how individuals grapple with complicated financial decisions, such as those involving retirement savings.