Internet-based educational resources are proliferating rapidly. One concern associated with these (potentially transformative) technological changes is that they will be disequalizing—as many technologies of the last several decades have been—creating superstar teachers and a winner-take-all education system. These important concerns notwithstanding, we contend that a major impact of web-based educational technologies will be the democratization of education: educational resources will be more equally distributed, and lower-skilled teachers will benefit. At the root of our results is the observation that skilled lecturers can only exploit their comparative advantage if other teachers complement those lectures with face-to-face instruction. This complementarity will increase the quantity and quality of face-to-face teaching services, potentially increasing the marginal product and wages of lower-skill teachers.

We review research that measures time preferences-i.e., preferences over intertemporal tradeoffs. We distinguish between studies using financial flows, which we call "money earlier or later" (MEL) decisions and studies that use time-dated consumption/effort. Under different structural models, we show how to translate what MEL experiments directly measure (required rates of return for financial flows) into a discount function over utils. We summarize empirical regularities found in MEL studies and the predictive power of those studies. We explain why MEL choices are driven in part by some factors that are distinct from underlying time preferences.

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 identify employees at seven companies whose 401(k) investment choices are dominated because they are contributing less than the employer matching contribution threshold despite being vested in their match and being able to make penalty-free 401(k) withdrawals for any reason because they are older than 59½. At the average firm, 36% of match-eligible employees over 59½ forego arbitrage profits that average 1.6% of their annual pay, or $507. A survey educating employees about the free lunch they are foregoing raised contribution rates by a statistically insignificant 0.67 percent of income among those completing the survey.

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.

Consistent with mental accounting, we document that investors sometimes choose the asset allocation for one account without considering the asset allocation of their other accounts. The setting is a firm that changed its 401(k) matching rules. Initially, 401(k) enrollees chose the allocation of their own contributions, but the firm chose the match allocation. These enrollees ignored the match allocation when choosing their own-contribution allocation. In the second regime, enrollees simultaneously selected both accounts' allocations, leading them to mentally integrate the two. Own-contribution allocations before the rule change equal the combined own- and match-contribution allocations afterwards, whereas combined allocations differ sharply across regimes.

The directed cognition model assumes that agents use partially myopic option-value calculations to select their next cognitive operation. The current paper tests this model by studying information acquisition in two experiments. In the first experiment, information acquisition has an explicit financial cost. In the second experiment, information acquisition is costly because time is scarce. The directed cognition model successfully predicts aggregate information acquisition patterns in these experiments. When the directed cognition model and the fully rational model make demonstrably different predictions, the directed cognition model better matches the laboratory evidence.

The directed cognition model assumes that agents use partially myopic option-value calculations to select their next cognitive operation. The current paper tests this model by studying information acquisition in two experiments. In the first experiment, information acquisition has an explicit financial cost. In the second experiment, information acquisition is costly because time is scarce. The directed cognition model successfully predicts aggregate information acquisition patterns in these experiments. When the directed cognition model and the fully rational model make demonstrably different predictions, the directed cognition model better matches the laboratory evidence.

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.