Publications

The department published or had accepted for publication 28 research articles in peer-reviewed academic journals including the following featured publications:

Professor Jay Huang published "The Global Credit Spread Puzzle" in the Journal of Finance with coauthors Zhan Shi and Yoshio Nozawa.

Abstract: We examine the ability of structural models to predict credit spreads using global default data and security-level credit spread data in eight developed economies. We find that two representative, pure default-risk models tend to underpredict the average credit spreads on investment-grade (IG) bonds, especially their spreads over government bonds, thereby providing evidence for a “global credit spread puzzle.” However, a model incorporating endogenous liquidity in the secondary debt market helps mitigate the puzzle. Furthermore, the model captures certain determinants of corporate bond market frictions across the eight economies and substantially improves the cross-sectional fit of individual IG credit spreads.

Associate Professor Mish Velikov published "Show me the receipts: B2B payment timeliness and expected returns" in the Journal of Financial Economics with coauthors Paul Lieberman, Atanas Mihov, and Andy Naranjo.

Abstract: Trade credit is an important source of firm financing, yet its rich informational content pertaining to payment timeliness is under-explored in asset pricing. Using an extensive data set from a leading private information exchange on business payment performance, we study the effects of trade credit payment timeliness on stock returns. We document two distinct channels through which trade credit payment behavior impacts future stock returns — slow diffusion of information and risk stemming from a customer firm’s vertical bargaining power position in the supply chain. Consistent with our first channel, a sudden delay in a firm’s payment to its suppliers predicts significantly lower future returns for its stock. Consistent with our second channel, firms that pay their bills moderately late on a consistent basis relative to terms earn significantly higher stock returns.

Professor Zhe Wang’s paper "Peer Learning, Enforcement, and Reputation" was accepted for publication in The Rand Journal of Economics with coauthors Yi Chen, Kai Du, and Phillip Stocken.

Abstract: We consider a two-period learning model featuring a sequentially-rational regulator, which tries to build a reputation for strict enforcement, and self-interested firms, which test the regulator's enforcement propensity through their misconduct. We find that peer learning between the firms yields more misconduct than when misconduct and enforcement are not observable between the firms, because the regulator's reputation concern creates enforcement externalities between them. When the regulator's reputation concerns are sufficiently strong, these enforcement externalities dominate the information externalities and heighten misconduct. Although seeking to develop a strong reputation for enforcement always benefits the regulator in the opaque setting, it often backfires in the presence of peer learning in a transparent setting.