[We evaluate why individuals invest in high-fee index funds. In our experiments, subjects each allocate $ 10,000 across four S&P 500 index funds and are rewarded for their portfolio's subsequent return. Subjects overwhelmingly fail to minimize fees. We reject the hypothesis that subjects buy high-fee index funds because of bundled nonportfolio services. Search costs for fees matter, but even when we eliminate these costs, fees are not minimized.Instead, subjects place high weight on annualized returns since inception. Fees paid decrease with financial literacy. Interestingly, subjects who choose high-fee funds sense they are making a mistake.]

Many experiments have found that participants take more investment risk if they see less frequent returns, portfolio-level returns (rather than each individual asset's returns), or long-horizon (rather than one-year) historical return distributions. In contrast, we find that such information aggregation treatments do not affect total equity investment when we make the investment environment more realistic than in prior experiments. Previously documented aggregation effects are not robust to changes in the risky asset's return distribution or to the introduction of a multiday delay between portfolio choice and return realizations.

We conduct an experiment to evaluate why individuals invest in high-fee index funds. In our experiments, subjects allocate $10,000 across four S&P 500 index funds and are rewarded for their portfolio's subsequent return. Subjects overwhelmingly fail to minimize fees. We can reject the hypothesis that subjects buy high-fee index funds because of bundled non-portfolio services. Search costs for fees matter, but even when we eliminate these costs, fees are not minimized. Instead, subjects place high weight on annualized returns since inception. Fees paid decrease with financial literacy. Interestingly, subjects who choose high-fee funds sense they are making a mistake.

We estimate β-δ time preferences and relative risk aversion (RRA) using a lifecycle model including stochastic income, liquid and illiquid assets, credit cards, dependents, Social Security, mortality, and bequests. Preference parameters are identified by cross-tabulating four lifecycle age intervals and four balance sheet moments: the share of households carrying (ie, revolving) credit card debt, average carried credit card debt, average net wealth among households carrying credit card debt, and average net wealth among households not carrying credit card debt. The 16 moments are approximately matched by (MSM) parameter estimates β=0.53, δ=0.99, and RRA = 1.9.

Many experiments have found that participants take more investment risk if they see returns less frequently, see portfolio-level returns (rather than each individual asset's returns), or see long-horizon (rather than one-year) historical return distributions. In contrast, we find that such information aggregation treatments do not affect total equity investment when we make the investment environment more realistic than in prior experiments. Previously documented aggregation effects are not robust to changes in the risky asset's return distribution or the introduction of a multi-day delay between portfolio choice and return realizations.