We model innovation investments as real options and explore the implications of ambiguity—Knightian uncertainty—and risk for innovation decisions. Our model provides predictions for creating options to invest and options to wait. The ensuing empirical analysis uses a risk measure and a new outcome-independent measure of ambiguity. We find a consistently significant negative effect of ambiguity on R\&D, patents, and citations, supporting our theoretical predictions. We also find a significant positive effect of risk on R\&D, but the effect of risk on patents and citations is negative and significant. Ambiguity matters more for high-tech firms, consistent with intuition.
Presenter: Avri Ravid (Yeshiva University)
Coauthors: Gabriela Coiculescu (Yeshiva University) and Yehuda (Yud) Izhakian (City University of New York)
Discussant: Stephen J. Terry (Boston University)