R&D, Patents and Innovation

Paper Session

Friday, Jan. 6, 2017 2:30 PM – 4:30 PM

Sheraton Grand Chicago, Sheraton Ballroom III
Hosted By: American Finance Association
  • Chair: David Robinson, Duke University

Innovation Waves, Investor Sentiment, and Mergers

David Dicks
,
University of North Carolina-Chapel Hill
Paolo Fulghieri
,
University of North Carolina-Chapel Hill

Abstract

We develop a theory of innovation waves, investor sentiment, and merger activity based on uncertainty aversion. Investors must typically decide whether or not to fund an innovative project with very limited knowledge of the odds of success, a situation that is best described as "Knightian uncertainty." We show that uncertainty-averse investors are more optimistic on an innovation if they can also make contemporaneous investments in other innovative ventures. This means that uncertainty aversion makes investment in innovative projects strategic complements, which results in innovation waves. Innovation waves occur in our economy when there is a critical mass of innovative companies and are characterized by strong investor sentiment, high equity valuation in the technology sector, and "hot" IPO and M&A markets. We also argue that M&A promotes innovative activity and leads to greater innovation rates and firm valuations.

Patents as Substitutes for Relationships

Farzad Saidi
,
Stockholm School of Economics
Alminas Zaldokas
,
Hong Kong University of Science and Technology

Abstract

Firms face a trade-off between patenting, thereby disclosing innovation, and secrecy. In this paper, we show how such public-information provision through patents acts as a substitute for private information acquired in financial relationships. As a shock to innovation disclosure, we use the American Inventor's Protection Act that made the content of firms' patent applications public within 18 months after filing, rather than at the grant date. Firms in industries that experienced a greater change in the publicity of their patent applications were significantly more likely to switch lenders. We also consider the reverse link of the substitution relationship, and explore the impact of improved lender informedness following the creation of universal banks on firms' patenting behavior. We find that firms patent less, without negatively altering their investment in innovation and its outcomes, such as new-product announcements.

Optimal Financing for R&D-Intensive Firms

Richard Thakor
,
University of Minnesota
Andrew Lo
,
Massachusetts Institute of Technology

Abstract

We develop a theory of optimal financing of R&D-intensive firms that uses their unique features—large capital outlays, long gestation periods, and low probabilities of R&D success—to explain three prominent stylized facts about these firms: their relatively low use of debt, large cash balances, and underinvestment in R&D. This model relies on three key frictions: adverse selection, moral hazard from risk shifting, and costs from “two-audience” proprietary information disclosure. We establish the optimal pecking order of securities with direct market financing when information disclosure partially endogenizes the extent of adverse selection. Using the familiar debt tradeoff between tax benefits and the costs of risk shifting, we show that under plausible conditions, equity dominates debt, and firms raise enough financing to carry excess cash. However, market financing still leaves potentially valuable R&D investments unfunded. We then use a mechanism design approach to explore the potential of intermediated financing, with a binding precommitment by firm insiders to make costly ex post payouts. We show that a mechanism consisting of put options can be used in combination with equity to eliminate underinvestment in R&D and improve welfare relative to the direct market financing outcome. This optimal intermediary-assisted mechanism consists of bilateral “insurance” contracts, with investors offering firms insurance against R&D failure and firms offering investors insurance against very high R&D payoffs not being realized.

Learning across Peer Firms and Innovation Waves

Merih Sevilir
,
Indiana University

Abstract

This paper presents a model where firms learn from each other's innovation,, and innovation by one firm spurs subsequent innovations by peer firms, leading to the emergence of innovation waves. In our model, innovation of a firm reaches peer firms competing in similar markets. Peer firms receiving the innovation can either expropriate it, or learn from it to generate a subsequent innovation. As an innovation reaches a greater number of peer firms, each peer firm's expropriation incentives decline while its incentives to generate a subsequent innovation increase. In addition, as the intensity of the innovation transmission across peer firms gets larger, expropriation incentives decline even further. Hence, perhaps surprisingly, as the innovation travels to a greater number of peer firms at a greater speed, and becomes easier to be expropriated, it becomes less desirable to expropriate it. Our results are consistent with the empirical evidence presented in Matray (2014) that innovation by one firm spurs innovation by neighboring peer firms, and firms innovate by building on previous technologies produced by peer firms. Our model predicts that a concentrated mass of interconnected firms that both compete and learn from each other as well as a speedy flow of ideas from one firm to another are necessary conditions for innovation waves to emerge. Finally, our analysis has implications for the innovation output of a firm and industry after a merger wave. A wave of consolidating mergers in an industry will reduce the number of firms, and increase each firm's incentive to expropriate a given innovation, with a negative effect on incentives to invest in innovation in the first place.
Discussant(s)
Ramana Nanda
,
Harvard University
Xuan Tian
,
Indiana University
Dirk Hackbarth
,
Boston University
Richmond Mathews
,
University of Maryland
JEL Classifications
  • G3 - Corporate Finance and Governance