Michael EwensTepper School of Business, Carnegie Mellon University

This paper explores the relationship between debt in the entrepreneurial capital structure and outcomes. In contrast to public firms where debt is considered a positive signal, venture capital (VC) debt predicts poorer future firm performance across several dimensions. VC-backed firms that issue debt or debt-like instruments, even after paying back debt in the successive period, have a 25% lower probability of success (IPO/acquisition). Fixed effects estimates show that entrepreneurial firm valuation also falls an average of 20% after debt financing. VCs with equity stakes lend in about about 45% of venture debt financings. We present a model where debt arises endogenously and the insider VC’s decision to provide debt to the entrepreneurial firm has informational content. When inside VCs with equity stakes provide debt financing, valuation declines 50% more compared to outside debt financed firms. These results suggest that not only is it important how a firm finances itself, it is also important who finances the firm.

Venture capital firms’ ability to repeatedly make top performing investments suggests the importance of some aspect of organizational or human capital. However, it is an unanswered question as to what extent the important attributes of performance are a part of the firm’s organizational capital or embodied in the human capital of the people inside the firm. We examine the performance at the partner-investment level to determine the extent of persistence in individual partners’ ability to IPO, achieve outsized exits or fail, and to what extent that performance is attributable to the firm or the partner. Shedding light on the sources of performance in venture capital firms will help us make progress on a fundamental question in economics as to whether a firm is more than the sum of its parts.

A model of racial discrimination provides testable implications for two features of statistical discriminators: differential treatment of signals by race and heterogeneous experience that shapes perception. We construct an experiment in the U.S. rental apartment market that distinguishes statistical discrimination from taste-based discrimination. Responses from over 14,000 rental inquiries with varying applicant quality show that landlords treat identical information from applicants with African-American and white sounding names differently. This differential treatment varies by neighborhood racial composition and signal type in a way consistent with statistical discrimination and in contrast to patterns predicted by a model of taste-based discrimination.