Inferring Market Structure from Customer Response to Competing and Complementary Products

We consider customer influences on market structure, arguing that market structure should explain the extent to which any given set of market offerings are substitutes or complements. We describe recent additions to the market structure analysis literature and identify promising directions for new research in market structure analysis. Impressive advances in data collection, statistical methodology and information technology provide unique opportunities for researchers to build market structure tools that can assist real-time marketing decision-making.     

Women Entrepreneurs and Family Firm Heterogeneity: Evidence from an Emerging Economy

Family firms add to the economic and social well-being of countries. While research on heterogeneity of family firms is gaining momentum, it has mostly been gender-neutral. The study fills this gap by examining heterogeneity of family firms owned and managed by women, in the context of a developing country—Brazil. The study draws upon the resource-based view of the firm to investigate the relationships between firm performance, family involvement, and financial resources at the start-up phase. An inductive analysis reveals two patterns. First, family firms that are started with the family achieve better performance than firms that are launched without the family and later evolve into a family business. Second, family firms that are funded with women entrepreneur’s own savings achieve worse performance than family firms that are started with borrowed funds. The results are useful for strategic decision making in fostering family businesses headed by women and proactive public policies for future innovation to enhance the success of women entrepreneurs.     

Seller experimentation and trade

Review of Economic Design - This paper studies the effect of trade opportunities on a seller’s incentive to acquire information through experimentation. I characterize the unique equilibrium...     

Bailouts and the modeling of bank distress

In this article, we develop a model for predicting distress events among large banks. We show that a bailout possibility induces different behaviors among small and large banks, and the proposed failure prediction model for large banks is thus considerably different from that for small banks. Major bank-level fundamentals show opposite conjecture directions for large versus small banks. The Tier 1 capital ratio, which is under the scrutiny of regulators and investors, has almost no distress prediction power among large banks. However, banks rescued by governments tend to maintain a lower Tier 1 ratio. The cost of funding in large banks is negatively correlated with the probability of failure, reflecting the fact that lenders internalize the too-big-to-fail (TBTF) policy and demand a lower interest rate from TBTF banks.