We provide a solution to the informed-principal problem in the independent private values setting with monetary transfers. The principal's private information creates signaling considerations that may distort the implemented allocation. We show that there is no distortion: all principal types implement an allocation that is optimal for the principal ex ante, before he/she learns his/her type. As an application, we consider settings with linear utility. For bilateral exchange in which the principal is one of the traders, the solution is a combination of a participation fee, a buy-out option for the principal, and a resale stage with posted prices.

Research suggests that boards of directors select CEOs using signals of ability. However, little is known about how boards determine the combination of attributes that constitute a ‘good’ CEO, especially attributes without an ex ante clear impact on managerial quality, such as CEO optimism. I argue that boards will learn the optimal level of such attributes more quickly from past success, and empirical results support this. Boards, particularly those with high reputation/independence, are significantly more likely to select a moderately optimistic (optimal) successor following a moderately optimistic CEO departure. Robustness checks rule out alternate explanations and support this conclusion.

We study capital structure choices that entrepreneurs make in their firms' initial year of operation, using restricted-access data from the Kauffman Firm Survey. Firms in our data rely heavily on external debt sources, such as bank financing, and less extensively on friends-and-family-based funding sources. Many startups receive debt financed through the personal balance sheets of the entrepreneur, effectively resulting in the entrepreneur holding levered equity claims in their startups. This fact is robust to numerous controls, including credit quality. The reliance on external debt underscores the importance of credit markets for the success of nascent business activity.

We present new identification results for nonparametric models of differentiated products markets, using only market level observables. We specify a nonparametric random utility discrete choice model of demand allowing rich preference heterogeneity, product/market unobservables, and endogenous prices. Our supply model posits nonparametric cost functions, allows latent cost shocks, and nests a range of standard oligopoly models. We consider identification of demand, identification of changes in aggregate consumer welfare, identification of marginal costs, identification of firms' marginal cost functions, and discrimination between alternative models of firm conduct. We explore two complementary approaches. The first demonstrates identification under the same nonparametric instrumental variables conditions required for identification of regression models. The second treats demand and supply in a system of nonparametric simultaneous equations, leading to constructive proofs exploiting exogenous variation in demand shifters and cost shifters. We also derive testable restrictions that provide the first general formalization of Bresnahan's (1982) intuition for empirically distinguishing between alternative models of oligopoly competition. From a practical perspective, our results clarify the types of instrumental variables needed with market level data, including tradeoffs between functional form and exclusion restrictions.

In light of the growing numbers of women of color in the entrepreneurial sector in the United States, employing public-use microdata from the 2007 Survey of Business Owners, this study finds that new firms owned by black and Hispanic women were more likely to cease operations than those owned by their male counterparts or by non-Hispanic whites, even when controlling for other owner- and firm-level characteristics and labor market conditions. These differences occurred despite the existence of public programs designed to help female and minority entrepreneurs, raising the question of efficiency of the current policy infrastructure in the United States.

This paper investigates the network structure of interbank markets. Using a dataset of interbank exposures in the Netherlands, we corroborate the recent hypothesis that the core periphery model is a ‘stylised fact’ of interbank markets. We find a core of highly connected banks intermediating between periphery banks and pay particular attention to model selection. Our analysis can help improve systemic risk assessments, especially as more granular data is becoming available.

Taking advantage of unique longitudinal data, we provide the first characterization of what college students believe at the time of entrance about their final major, relate these beliefs to actual major outcomes, and provide an understanding of why students hold the initial beliefs about majors that they do. The data collection and analysis are based directly on a conceptual model in which a student's final major is best viewed as the end result of a learning process. We find that students enter school quite optimistic about obtaining a science degree, but that relatively few students end up graduating with a science degree. The substantial overoptimism about completing a degree in science can be attributed largely to students beginning school with misperceptions about their ability to perform well academically in science.

We study capital structure choices that entrepreneurs make in their firms' initial year of operation, using restricted-access data from the Kauffman Firm Survey. Firms in our data rely heavily on external debt sources, such as bank financing, and less extensively on friends-and-family-based funding sources. Many startups receive debt financed through the personal balance sheets of the entrepreneur, effectively resulting in the entrepreneur holding levered equity claims in their startups. This fact is robust to numerous controls, including credit quality. The reliance on external debt underscores the importance of credit markets for the success of nascent business activity.