学术论文

Mutual funds investing in illiquid corporate bonds actively manage Treasury positions to buffer redemption shocks. This liquidity management practice can transmit non-fundamental fund flow shocks onto Treasuries, generating excess return volatility. Consistent with this hypothesis, we find that Treasury excess return volatility is positively associated with bond fund ownership, and this pattern is more pronounced among funds conducting intensive liquidity management. Causal evidence is provided by exploiting the U.S. Securities and Exchange Commission’s 2017 Liquidity Risk Management Rule. Evidence also suggests that the COVID-19 Treasury market turmoil was attributed to intensified liquidity management, an unintended consequence of the 2017 Liquidity Risk Management Rule.

Customer reviews help communicate product information, but their effectiveness may suffer from selection bias (i.e., depending on factors, such as the individual experience and price, not all consumers may voluntarily write reviews). Consequently, a seller may have to resort to additional means (e.g., signaling through price in the context of an experience good) to convey its quality. This paper develops an analytical model to investigate the interaction of customer reviews and price with the presence of selection bias in marketing an experience good with uncertain quality to consumers. Our analysis reveals the dual roles played by both customer reviews and price in communicating quality information. On one hand, customer reviews may either directly convey product information with unbiased distribution of reviews or facilitate price signaling when reviews are biased because of selection. On the other hand, price may be adjusted to mitigate the selection bias of reviews to make them more informative, and it may also signal quality directly in the presence of review bias. As a result, we show that bias in reviews may actually benefit consumers without compromising information communication as the incentive to reduce review selection bias makes it credible and profitable for the high-quality seller to signal its type by undercutting the price that would be set if it is of low quality. We then extend our analysis to examine the information, profits, and welfare impacts of several important design elements of a review system as well as the impact of consumers’ aversion to risk. Finally, the implications of our findings on the management of user-generated content and pricing are discussed.

Nonparametric estimation of the mean and covariance functions is ubiquitous in functional data analysis and local linear smoothing techniques are most frequently used. Zhang and Wang (2016) explored different types of asymptotic properties of the estimation, which reveal interesting phase transition phenomena based on the relative order of the average sampling frequency per subject TT to the number of subjects nn, partitioning the data into three categories: “sparse”, “semi-dense”, and “ultra-dense”. In an increasingly available high-dimensional scenario, where the number of functional variables pp is large in relation to nn, we revisit this open problem from a non-asymptotic perspective by deriving comprehensive concentration inequalities for the local linear smoothers. Besides being of interest by themselves, our non-asymptotic results lead to elementwise maximum rates of L2L2 convergence and uniform convergence serving as a fundamentally important tool for further convergence analysis when pp grows exponentially with nn and possibly TT. With the presence of extra logplog⁡p terms to account for the high-dimensional effect, we then investigate the scaled phase transitions and the corresponding elementwise maximum rates from sparse to semi-dense to ultra-dense functional data in high dimensions. We also discuss a couple of applications of our theoretical results. Finally, numerical studies are carried out to confirm the established theoretical properties.

We study information sharing between strategic investors who are informed about asset fundamentals. We demonstrate that a coarsely informed investor optimally chooses to share information if his counterparty investor is well informed. By doing so, the coarsely informed investor invites the other investor to trade against his information, thereby reducing his price impact. Paradoxically, the well informed investor loses from receiving information because of the resulting worsened market liquidity and the more aggressive trading by the coarsely informed investor. Our analysis sheds light on phenomena such as private communications among investors and public information sharing on social media.

Short selling regulation has been a longstanding topic of debate in financial markets, particularly during times of crisis. While proponents argue that short selling aids in price discovery and market efficiency, critics raise concerns about manipulative short selling practices that can destabilize markets. This paper presents a theoretical model to analyze the impact of short selling, specifically manipulative short selling (MSS), on bank runs and efficiency. The model demonstrates that MSS can emerge as an equilibrium outcome driven by uninformed speculators seeking to profit from artificially depressing stock prices. The prevalence of MSS is influenced by the level of informed trading and coordination friction among creditors. We find that short selling bans can enhance welfare by mitigating the negative effects of MSS, particularly in scenarios with high coordination frictions. We also provide policy and empirical implications.

Using variations in the timing of the New Rural Pension Scheme (NRPS) across rural Chinese counties, we examine its effects on eldercare mode, child investment, and son preference. Our findings are three-fold: (1) After the introduction of NRPS, married sons are less likely to live with and provide care for their parents, while married daughters show no significant change in their caregiving behavior; (2) Parents reduce the brideprice for their sons but not the dowry for their daughters; (3) The sex ratio at birth becomes more balanced, indicating a reduction in son preference. These results suggest that public pension programs can significantly influence traditional family dynamics, including eldercare modes and cultural norms around gender preference.

Credit information sharing allows creditors to obtain borrowers' relevant credit information, and it can improve borrowers' investment outcomes that are funded by debt. Using reforms to European countries' public credit registries (PCRs) to capture mandated information sharing among creditors, we examine the impact of such sharing on firms' investment efficiency. We find that information sharing enhances firms' investment efficiency, which we measure by their investment-q sensitivity. This finding is consistent with credit information sharing enabling creditors to better screen borrowers to mitigate adverse selection and enhancing borrower discipline to avoid a bad credit record, which leads to the borrower making more efficient investments. We also document that the information sharing effect is more pronounced when firms rely more on debt financing, when the shared credit information is more accessible, when firms' information environment is more opaque, and when there is a greater information monopoly in the banking system. We offer supplementary evidence that the effect is also more salient when PCRs have characteristics that suggest more effective credit information sharing. Overall, our paper offers new insight into whether and how information sharing in credit markets enhances firms' investment efficiency. More broadly, it highlights how making more borrower information available to creditors can have important economic spillover effects on firm outcomes.

This paper examines the role of information in two-sided matching markets where preference mismatch is present. Two-sided markets are characterized by different preferences of the parties involved, and a match occurs when both sides show a preference for each other. In practice, however, there is often a preference mismatch. In this study, we use a large data set from an online dating website to provide empirical evidence for preference mismatch in the field. We also develop empirical models to investigate the impact of information under preference mismatch by analyzing variations in the amount of available information. Specifically, we compare partial and complete information contained in the users’ short and long profiles, respectively. We find that more information about the other side does not necessarily improve the likelihood of a match. In fact, the side making the proposal has a better chance of matching if the decision is based on the information contained in the short profile rather than the long profile. This suggests that users are better off seeing partial rather than complete information about the candidates, a phenomenon we refer to as the “less information is more” effect. Our empirical analysis shows that this effect is driven by the mismatched preferences of the two sides. These results imply that there is an optimal amount of information that one side should possess about the other before making a proposal. Our study highlights the importance of optimal information design strategies to determine the appropriate amount of information that should be provided to each side. Our findings also offer managerial implications regarding information provision strategies for online platforms in general.

Using data on nearly 20,000 restaurants in China during the COVID-19 outbreak, we find evidence that the government-sponsored rent reduction program reduced debt overhang problems. Rent reductions, which averaged 36,000 RMB per restaurant, increase the open rate of restaurants by 3.7higher committed costs benefit more from the rent reduction. The stimulus has a positive spillover effect that boosts the revenue of restaurants in the immediate vicinity of subsidized restaurants. The treatment effect varies with organizational structure in a manner consistent with an information frictions hypothesis