Person:

Nanda, Ramana

We review the recent literature on the financing of innovation, inclusive of large companies and new startups. This research strand has been very active over the past five years, generating important new findings, questioning some long-held beliefs, and creating its own puzzles. Our review outlines the growing body of work that documents a role for debt financing related to innovation. We highlight the new literature on learning and experimentation across multi-stage innovation projects and how this impacts optimal financing design. We further highlight the strong interaction between financing choices for innovation and changing external conditions, especially reduced experimentation costs.

Entrepreneurship research is on the rise, but many questions about its fundamental nature still exist. We argue that entrepreneurship is about experimentation: the probabilities of success are low, extremely skewed, and unknowable until an investment is made. At a macro level, experimentation by new firms underlies the Schumpeterian notion of creative destruction. However, at a micro level, investment and continuation decisions are not always made in a competitive Darwinian contest. Instead, a few investors make decisions that are impacted by incentive, agency, and coordination problems, often before a new idea even has a chance to compete in a market. We contend that costs and constraints on the ability to experiment alter the type of organizational form surrounding innovation and influence when innovation is more likely to occur. These factors not only govern how much experimentation is undertaken in the economy, but also the trajectory of experimentation, with potentially very deep economic consequences.

We review the growing literature on the relationship between venture capital (VC) booms and start-up financing, focusing on three broad areas. First, we discuss the drivers of large inflows into the VC asset class, particularly in recent years, which are related to but also distinct from macroeconomic business cycles and stock market fluctuations. Second, we review the emerging literature on the real effects of VC financing booms. A particular focus of this work is to highlight the potential impact that booms (and busts) can have on the types of firms that VC investors choose to fund and the terms at which they are funded, independent of investment opportunities—thereby shaping the trajectory of innovation being conducted by start-ups. Third, an important insight from recent research is that booms in VC financing are not just a temporal phenomenon but can also be seen in terms of the concentration of VC investment in certain industries and geographies. We also review the role of government policy, exploring the degree to which it can explain the concentration of VC funding in the United States over the past 40 years in just two broad areas—information and communication technologies and biotechnology. We conclude by highlighting promising areas of further research.

Venture capital is associated with some of the most high-growth and influential firms in the world. Academics and practitioners have effectively articulated the strengths of the venture model. At the same time, venture capital financing also has real limitations in its ability to advance substantial technological change. Three issues are particularly concerning to us: 1) the very narrow band of technological innovations that fit the requirements of institutional venture capital investors; 2) the relatively small number of venture capital investors who hold and shape the direction of a substantial fraction of capital that is deployed into financing radical technological change; and 3) the relaxation in recent years of the intense emphasis on corporate governance by venture capital firms. While our ability to assess the social welfare impact of venture capital remains nascent, we hope that this article will stimulate discussion of and research into these questions.

We find a negative relationship between bank distress and the level, quality, and trajectory of firm-level innovation during the Great Depression, particularly for R&D firms operating in capital intensive industries. However, we also show that because a sufficient number of R&D intensive firms were located in counties with lower levels of bank distress, or were operating in less capital intensive industries, the negative effects were mitigated in aggregate. Although Depression era bank distress was associated with the stifling of innovation, our results also help to explain why technological development was still robust following one of the largest shocks in the history of the U.S. banking system.

We provide a model of investment into new ventures that demonstrates why some places, times, and industries should be associated with a greater degree of experimentation by investors. Investors respond to financing risk―a forecast of limited future funding―by modifying their focus to finance less innovative firms. Potential shocks to the supply of capital create the need for increased upfront financing, but this protection lowers the real option value of the new venture. In equilibrium, financing risk disproportionately impacts innovative ventures with the greatest real option value. We propose that extremely novel technologies may need "hot" financial markets to get through the initial period of discovery or diffusion.

We study how technological shocks to the cost of starting new businesses have led the venture capital model to adapt in fundamental ways over the prior decade. We both document and provide a framework to understand the changes in the investment strategy of VCs in recent years—an increased prevalence of a "spray and pray" investment approach—where investors provide a little funding and limited governance to an increased number of startups that they are more likely to abandon, but where initial experiments significantly inform beliefs about the future potential of the venture. This adaptation and related entry by new financial intermediaries has led to a disproportionate rise in innovations where information on future prospects is revealed quickly and cheaply and has reduced the relative share of innovation in complex technologies where initial experiments cost more and reveal less.