Behavioral Inequality (Public)
Project
Behavioral Inequality
Study ID sspp-2026-0034-v1
Study Title Behavioral Inequality
Authors Stefano DellaVigna, Tim de Silva, Rohan Jha
Completion Time 20 Minutes
Close Date (UTC) Oct. 31, 2026
Discipline Economics
Field Applied Econometrics, Financial Economics, Public Economics, Behavioral Economics
Country United States
Abstract
A large body of literature in economics has studied inequality in income and wealth, documenting its evolution, analyzing its determinants, and evaluating policies that could reduce it. The vast majority of this work uses models with fully optimizing households. At the same time, a large literature in behavioral economics has documented numerous decision-making frictions that lead to losses in income and wealth. For example, individuals fail to claim government benefits for which they are eligible, choose dominated health insurance plans, and pay avoidable fees on credit cards and bank accounts. We aim to quantify how decision-making frictions across different domains aggregate to affect inequality. We do this by combining existing literature with additional analysis of microdata to estimate the prevalence and financial impact of 20 frictions across the income distribution.
Study ID sspp-2026-0034-v1
Study Title Behavioral Inequality
Authors Stefano DellaVigna, Tim de Silva, Rohan Jha
Completion Time 20 Minutes
Close Date (UTC) Oct. 31, 2026
Discipline Economics
Field Applied Econometrics, Financial Economics, Public Economics, Behavioral Economics
Country United States
Abstract
A large body of literature in economics has studied inequality in income and wealth, documenting its evolution, analyzing its determinants, and evaluating policies that could reduce it. The vast majority of this work uses models with fully optimizing households. At the same time, a large literature in behavioral economics has documented numerous decision-making frictions that lead to losses in income and wealth. For example, individuals fail to claim government benefits for which they are eligible, choose dominated health insurance plans, and pay avoidable fees on credit cards and bank accounts. We aim to quantify how decision-making frictions across different domains aggregate to affect inequality. We do this by combining existing literature with additional analysis of microdata to estimate the prevalence and financial impact of 20 frictions across the income distribution.
Log In to Receive Additional Forecasting Benefits
Save your progress and compare your forecasts to the actual results of the study upon release by logging in.Don't have an account? Sign up here.
Continue without logging in
You can choose to make an account upon completion.