We consider an agent who chooses from a set of options after receiving some private information. This information however is unobserved by an analyst, so from the latter’s perspective, choice is probabilistic or random. We provide a theory in which information can be fully identified from random choice. In ad-dition, the analyst can perform the following inferences even when information is unobservable: (1) directly compute ex-ante valuations of option sets from ran-dom choice and vice-versa, (2) assess which agent has better information by using choice dispersion as a measure of informativeness, (3) determine if the agent’s beliefs about information are dynamically consistent, and (4) test to see if these beliefs are well-calibrated or rational. ⇤ I am deeply indebted to both Faruk Gul and Wolfgang Pesendorfer for their continuous advice, guidance and encouragement. I am very grateful to Stephen Morris for some highly valuable and insightful discussions.

We provide a revealed preference methodology for identifying beliefs and utilities that can vary across states. A notion of comparative informativeness is introduced that is weaker than the standard Blackwell ranking. We show that beliefs and state-dependent utilities can be identified using stochastic choice from two informational treatments, where one is strictly more informative than another. Moreover, if the signal structure is known, then stochastic choice from a single treatment is enough for identification. These results illustrate novel identification methodologies unique to stochastic choice. Applications include identifying biases in job hiring, loan approvals, and medical advice. (JEL D11, D82, D83, J23, M51)

Buyers often search across sellers to learn which product best fits their needs. We study how sellers manage these search incentives through their disclosure strategies (e.g., product trials, reviews, and recommendations) and ask how competition affects information provision. If sellers can observe the beliefs of buyers or can coordinate their strategies, then there is an equilibrium in which sellers provide the “monopoly level” of information. In contrast, if buyers’ beliefs are private, then there is an equilibrium in which sellers provide full information as search costs vanish. Anonymity and coordination thus play important roles in understanding how advice markets work.

[We examine situations where the same fund manager simultaneously manages mutual funds and hedge funds. We refer to this as side-by-side management. We document 344 such cases involving 693 mutual funds and 538 hedge funds. Proponents of this practice argue that it is essential to hire and retain star performers. Detractors argue that the temptation for abuse is high, and the practice should be banned. Our analysis based on various performance metrics shows that side-by-side mutual fund managers significantly outperform peer funds, consistent with this privilege being granted primarily to star performers. Interestingly, side-by-side hedge fund managers are at best on par with their style category peers, casting further doubt on the idea that conflicts of interest undermine mutual fund investors. Thus, we find no evidence of welfare loss for mutual fund investors due to exploitation of conflicts of interest.]

We examine the extent to which a fund's cash flows are affected by the stellar performance of other funds in its family–and consequences of such spillovers. We show that star performance results in greater cash inflow to the fund and to other funds in its family. Moreover, families with higher variation in invetment strategies across funds are shown to be more likely to generate star performance. We argue that spillovers may induce lower ability families to pursue star-creating strategies. Consistent with our conjecture, families with high variation in investment strategies across funds significantly underperform low-variation families.

[Does the mutual fund industry lose its best managers to hedge funds? We find that mutual funds are able to retain managers with good performance in the face of competition from a growing hedge fund industry. On the other hand, poor performers are more likely to leave the mutual fund industry. A small fraction of these poor performers find jobs with smaller and younger hedge fund companies, especially when the hedge fund industry is growing rapidly. Analogously, a small fraction of the better-performing mutual fund managers are retained by allowing them to manage a hedge fund side-by-side.]

We examine situations where the same fund manager simultaneously manages mutual funds and hedge funds. We refer to this as side-by-side management. We document 344 such cases involving 693 mutual funds and 538 hedge funds. Proponents of this practice argue that it is essential to hire and retain star performers. Detractors argue that the temptation for abuse is high, and the practice should be banned. Our analysis based on various performance metrics shows that side-by-side mutual fund managers significantly outperform peer funds, consistent with this privilege being granted primarily to star performers. Interestingly, side-by-side hedge fund managers are at best on par with their style category peers, casting further doubt on the idea that conflicts of interest undermine mutual fund investors. Thus, we find no evidence of welfare loss for mutual fund investors due to exploitation of conflicts of interest.

We study a significant innovation with widespread consequences for the mutual fund industry: the introduction of multiple-class funds that give investors a choice among alternative load and fee structures. The transition to a multiple-class structure represents an important step in the evolution of the mutual fund industry. It also provides a well-controlled setting for research on the structure of funds, on investor clienteles and their impact on fund performance and, more generally, about the manner in which financial innovations tend to be adopted. We develop a simple model of a fund's decision on whether and when to introduce new classes and empirically investigate the model's predictions that: (a) Funds with more skilled management, less sensitivity of flows to performance, smaller size, higher existing loads and membership in larger families are better positioned to benefit and, therefore, more likely to switch to a multiple-class structure earlier; (b) The new classes increase the level and volatility of fund inflow by attracting investors with short and uncertain investment horizons – which, in turn, can negatively impact fund performance. Our empirical results are generally supportive of the model's predictions.

We propose a novel model of stochastic choice: the single-crossing random utility model (SCRUM). This is a random utility model in which the collection of preferences satisfies the single-crossing property. We o↵er a characterization of SCRUMs based on two easy-to-check properties: the classic Monotonicity property and a novel condition, Centrality. The identified collection of preferences and associated probabilities is unique. We show that SCRUMs nest both single-peaked and single-dipped random utility models and establish a stochastic monotone comparative result for the case of SCRUMs.

We examine the extent to which a fund's cash flows are affected by the stellar performance of other funds in its family — and consequences of such spillovers. We show that star performance results in greater cash inflow to the fund and to other funds in its family. Moreover, families with higher variation in investment strategies across funds are shown to be more likely to generate star performance. We argue that spillovers may induce lower ability families to pursue star-creating strategies. Consistent with our conjecture, families with high variation in investment strategies across funds significantly underperform low-variation families.