We estimate the impact of venture capital (VC) contract terms on startup outcomes and the split of value between the entrepreneur and investor, accounting for endogenous selection via a novel dynamic search-and-matching model. The estimation uses a new, large data set of first financing rounds of startup companies. Consistent with efficient contracting theories, there is an optimal equity split between agents, which maximizes the probability of success. However, venture capitalists (VCs) use their bargaining power to receive more investor-friendly terms compared to the contract that maximizes startup values. Better VCs still benefit the startup and the entrepreneur due to their positive value creation. Counterfactuals show that reducing search frictions shifts the bargaining power to VCs and benefits them at the expense of entrepreneurs. The results show that the selection of agents into deals is a first-order factor to take into account in studies of contracting.

Abstract We use new hand-collected data from corporate filings to study the drivers of corporate capital structure adjustment. Classifying firms by their adjustment frequencies, we reveal previously unknown patterns in their reasons for financing and the financial instruments used. Some are consistent with existing theory, whereas others are understudied. Many leverage changes are outside of the firm’s control (e.g., executive option exercise) or incur negligible adjustment costs (e.g., credit-line usage). This implies a lower frequency of proactive leverage adjustments than indicated by prior research using accounting data, suggesting that costs of adjustment are higher, or the benefits lower, than previously thought.

ABSTRACT We adapt stochastic discount factor (SDF) valuation methods for venture capital (VC) performance evaluation. Our approach generalizes the popular Public Market Equivalent (PME) method and allows statistical inference in the presence of cross‐sectionally dependent, skewed VC payoffs. We relax SDF restrictions implicit in the PME so that the SDF can accurately reflect risk‐free rates and returns of public equity markets during the sample period. This generalized PME yields substantially different abnormal performance estimates for VC funds and start‐up investments, especially in times of strongly rising public equity markets and for investments with betas far from one.