I document a new empirical puzzle in initial public offerings (IPOs): trading volume over the 600 business days following an IPO exhibits a pronounced U-shaped pattern. After the well-known post-IPO drop in turnover, trading activity rises steadily by about 22% per year. This increase cannot be explained by standard drivers of high turnover and is robust to aggregate market trends and to firm size at issuance. I further show that the U-shape is closely linked to lockup agreements, but not through their direct consequences such as insider sales or changes in free float. Instead, the results suggest that lockups shape long-run liquidity dynamics, pointing to persistent effects from investor anticipation, underwriter reputation, or shifts in trading clientele. These findings link IPO contract design to secondary market liquidity and open new questions for asset pricing and market microstructure.

This paper studies whether probability weighting can jointly account for three features of household retirement behavior: low wealth accumulation, limited risky-asset exposure, and low annuity demand. I embed rank-dependent utility in a calibrated life-cycle model with laborincome, equity, and mortality risk and an annuitization choice at retirement. Probability weighting of survival risk shifts consumption toward earlier ages and approximately halves retirement wealth. Probability weighting of labor-income and equity risk reduces risky-asset exposure at the benchmark calibration, while survival weighting works in the opposite direction through the composition of human and financial wealth. The largest effect is on annuitization: among households reaching retirement, demand for an actuarially fair annuity falls from 98% to 5%. These effects are robust across alternative calibrations. LISS survival beliefs display the same qualitative pattern as probability-weighted survival probabilities, helping reconcile longevity optimism with low annuity demand.

Financial losses provide a natural basis for disaster compensation, but may misidentify which generations bear the largest lifetime welfare costs. Evidence from the experience-effects literature shows that adverse events, including disasters, can change risk preferences and subsequent financial behavior. I examine these consequences in a life-cycle portfolio model by comparing an identical disaster occurring at different ages. Under CRRA preferences, a disaster early in working life reduces remaining-lifetime welfare by approximately 11%, despite small financial wealth losses. Evaluating consumption paths under common pre-disaster preferences, I find that the preference change has little welfare effect in isolation but alters households' responses to simultaneous income and wealth losses. A higher elasticity of intertemporal substitution shifts the largest welfare losses toward retirement. In the benchmark, wealth- and welfare-based measures consequently direct the same compensation budget toward different generations.

Do preference measures become more informative when elicited in the same context as the behavior they are meant to explain? Using a representative Dutch household panel, we compare risk-and time-preference tasks framed as lotteries, investments, work, or health and link them to independently observed field behavior. Context matters sharply for risk but not for time preferences. Domain-matched risk aversion predicts risky investment, self-employment, and insurance choices, whereas lottery risk aversion does not. Lottery-context impatience, however, already predicts wealth, financial resilience, and exercise. In pooled tests, matching strengthens the risk-preference slope by 0.21 outcome standard deviations more than the time-preference slope (p = 0.006). More broadly, our results show that the portability of preference measures across domains depends on the preference being measured.

Risk preference elicitation methods are widely used to measure behavior under risk, but typically interpret choices through the lens of expected utility. When actual preferences depart from expected utility, the resulting estimates may therefore be distorted. We characterize the resulting measurement error. In the Holt-Laury multiple price list, probability weighting can either raise or lower estimated risk aversion, with the sign determined jointly by underlying risk aversion and task design. The error persists with a finer probability grid and appears in the fixed-probability Eckel-Grossman task. We then show how task design can mitigate this error under rank-dependent utility. Setting the probability to 37% eliminates the probability-weighting component under one-parameter Prelec weighting and reduces it under Tversky-Kahneman weighting.