Latest Research Publications

We introduce a learning model in which the decision maker does not know how recommendations are generated, called the contraction rule. We present behavioral postulates that characterize it. The contraction rule can be uniquely identified and reveals how the decision maker interprets and how much she trusts the recommendation. In a dynamic stationary setting, we show that the contraction rule is not dominated by completely following recommendations and is incompatible with a property called compliance with balanced recommendations. Following this negative result, we demonstrate that the contraction rule may generate and reinforce recency bias and disagreement.

We build on AGM belief revision (Alchourrón et al. (1985)) and propose a class of updating rules called pragmatic rules. Pragmatic updating applies to multiple priors and requires that the agent's posteriors be the subset of her priors under which the realized event occurs with probability 1, if such priors exist. We construct a propositional language based on qualitative probability and demonstrate the strong relation between belief updating rules and belief revision rules in this language. We show that an updating rule is consistent with AGM belief revision if and only if it is pragmatic. While maximum likelihood updating is pragmatic in general, full-Bayesian updating is not. We characterize maximum likelihood updating within the AGM framework, and show that full-Bayesian updating can be obtained by dropping one of AGM's postulates.

We study how proprietary information flows in strategic alliances facilitate banks’ information collection in private debt markets. We argue that lenders that have previously worked with a borrower’s alliance partners have an information advantage and show that firms entering a strategic alliance receive a lower interest spread on loans from banks that have previously lent to their strategic partners than loans from other banks. Cross-sectional tests on alliances’ economic importance and participants’ information environment support our hypothesis that the loan price effect is driven by reduced information asymmetry between borrowers and their partners’ relationship banks. Last, we find borrowers are more likely to obtain debt financing from alliance-related banks than from other banks. Overall, our findings are consistent with lenders that have previously worked with an alliance counterparty possessing debt contracting-relevant information about the soft nature of alliance value and the partners’ commitment to alliances.

What is the most cost-efficient way to impose trade sanctions against Russia? We build a quantitative model of international trade with input–output connections. Sanctioning countries choose import tariffs to simultaneously maximize their income and minimize Russia’s income, with different weights placed on these objectives. We find, first, that for countries with low willingness to pay for sanctions against Russia, the most cost-efficient sanction is an approximately 20% tariff on all Russian products. Second, if countries are willing to pay at least US$0.70 for each US$1 drop in Russian welfare, an embargo on Russia’s mining and energy products is the most cost-efficient policy.

In flexible manufacturing lines with delayed differentiation, the production process may fluctuate sharply when a control action is performed. As a result, the steady-state analysis algorithm is inaccurate for these production lines, and transient behavior studies have become crucial. However, dynamic analysis remains unexplored compared with the well-established theoretical system of steady-state analysis. Therefore, in this study, we propose a fast algorithm for predicting the production process performance in the delayed differentiation-based flexible production line under operation control. We first formulate practical problems existing in the auto, food, and furniture industries into a mathematical formation. Then, we offer closed-form formulae for predicting the production process performance using the built stochastic model in the production line with three machines. We also propose an algorithm to predict the performance of a production line having more than three machines. The proposed methods were verified to be highly accurate through comparison experiments. In terms of theoretical contributions, this study offers a research foundation for other transient-based studies. From a practical perspective, the proposed algorithms can be employed to predict the production process performance of processing lines under production control in advance.

Transaction costs have a first-order effect on the performance of currency portfolios. Proportional costs based on quoted bid–ask spread are relatively small, but when a fund is large, costs due to the trading volume price impact are sizable and quickly erode returns, leaving many popular strategies unprofitable. A mean–variance-transaction-cost optimized approach (MVTC) that accounts for costs in the optimization efficiently tackles the problem with only relatively minor negative implications on before-cost profitability. MVTC is robust even when the price impact of trading is severe. Finally, we introduce an accurate extrapolation approach to expand the sample of the realized Amihud measure of Ranaldo and Santucci de Magistris (2022) from 12 to 26 currencies and from 2012 back in time to 1986.

Although food waste is an urgent issue with widespread economic, societal, and environmental impacts, it remains understudied in the marketing discipline. This is surprising, since most food waste occurs at the retail and consumption stages of the food life cycle. This research fills this gap by examining how resource mindset and self-construal jointly shape consumer food waste. Specifically, inducing a scarcity mindset signals that there is no resource to waste, mitigating consumer food waste regardless of self-construal. In contrast, under an abundance mindset, where there is resource to waste, activating an interdependent (vs. independent) self-construal can effectively reduce consumer food waste. The authors identify sharing obligation, the tendency to share valuable resources with in-groups, as a key mechanism behind the effect. In support of this mechanism, enhancing sharing obligation (e.g., highlighting the sharing concept, highlighting others’ food needs) or diminishing it (e.g., highlighting family resource abundance) attenuates the effect of self-construal on consumer food waste under an abundance mindset. The results from one large-scale field study, four controlled experiments, and a country-level secondary data analysis provide convergent support for the proposed framework. This research not only contributes to the related literature but also provides actionable strategies for mitigating consumer food waste.

Washington policy research analysts (WAs) monitor political developments and produce research to interpret the impact of these events. We find institutional clients channel more commissions to brokerages providing policy research and commission-allocating institutional clients generate superior returns on their politically sensitive trades. We find that WA policy research reports are associated with significant price and volume reactions. Finally, we find sell-side analysts with access to WA issue superior stock recommendations on politically sensitive stocks. These effects are particularly acute during periods of high political uncertainty. Overall, we uncover a unique and an important conduit through which political information filters into asset prices.

The Securities and Exchange Commission’s 2016 Tick Size Pilot Program was a natural experiment that imposed increases in tick size for randomly selected small-cap firms. Using a difference-in-differences research design, we examine the effect of this increase in tick size on earnings guidance. We find that after initiation of the program, treatment firms provide significantly less earnings guidance. We provide further evidence that this decrease is driven by increases in investors’ fundamental information acquisition and in firms’ financial reporting quality, consistent with firms reducing earnings guidance when investors are already more informed. The decrease is stronger for firms with higher proprietary costs of disclosure, consistent with firms being more likely to reduce costly disclosure when investors are more informed. In contrast, the decrease is weaker for firms with greater external financing needs, consistent with these firms continuing to seek the benefits of disclosure, even when investors are more informed. Taken together, our results suggest that an increase in tick size makes investors more informed, which, in turn, reduces the need for firms to provide earnings guidance, though the extent of the reduction depends on the costs and benefits of providing earnings guidance.