I show that patents are pledged as collateral to raise significant debt financing, and that the pledgeability of patents contributes to the financing of innovation. In 2013, 38% of US patenting firms had previously pledged patents as collateral, and these firms performed 20% of research and development expense and patenting in Compustat. Employing court decisions as a source of exogenous variation in creditor rights, I show that patenting companies raised more debt, and spent more on R&D, when creditor rights to patents strengthened. Subsequently, these companies exhibited a gradual increase in patenting output and the use of patents as collateral.

Is there a trade-off between the short-run and long-run real effects of monetary policy “leaning against the wind”? We provide novel evidence on this question from the United States in 1920–1921. Our identification strategy exploits county-level variation in access to the Federal Reserve’s discount window, and hand-collected data on banking and agriculture in Illinois. In the short term, tightened conditions at the discount window decreased bank lending and lowered crop prices and farm revenues. In the long term, however, they lowered debt-to-output levels and led to greater farmland utilization, suggesting an avoidance of debt overhang problems.

We present a model rationalizing the economic value of digital tokens for launching peer-to-peer platforms. By using the blockchain to transparently distribute tokens before the platform launches, a token sale overcomes later coordination failures between the platform’s users. This result follows from forward induction reasoning, under which the costly and observable action of token acquisition credibly communicates the intent to participate on the platform. Our framework demonstrates the applications of digital tokens to entrepreneurship, and offers guidance for both practitioners and regulators.

How much do students benefit from student loan subsidies? We investigate this question, exploiting a natural experiment: a demand shock due to the 2011 tightening of credit standards in the PLUS program. We first establish that the Bennett hypothesis is best explained by colleges charging large markups over their marginal costs, rather than by advantageous selection. Then we use our results to estimate that students plausibly capture less than 60 cents of each dollar of resources expended on loan subsidies. We discuss alternative approaches that would more directly benefit students.

We show that the relation between aggregate investment and Tobin’s q has become remarkably tight in recent years, contrasting with earlier times. We connect this change with the growing empirical dispersion in Tobin’s q, which we show both in the cross-section and the time series. To study the source of this dispersion, we augment a standard investment model with two distinct mechanisms related to firms’ research activities: innovations and learning. Both innovation jumps in cash flows and the frequent updating of beliefs about future cash flows endogenously amplify volatility in the firm’s value function. Perhaps counterintuitively, the investment-q regression works better for research-intensive industries, a growing segment of the economy, despite their greater stock of intangible assets. We confirm the model’s predictions in the data, and we disentangle the results from measurement error in q.