This article studies optimal patents with respect to the timing of innovation disclosure. In a simple model, we identify forces that lead firms to either suboptimally patent too early or too late in equilibrium, and we determine conditions so that stronger patents induce earlier or later equilibrium disclosure. Then, by solving an infinite multistage patent game with a more explicit structure, we describe innovation growth, and derive detailed predictions that can be used for policy experiments. As an application, we calibrate our multistage game using summary statistics from the seeds breeding industry. We find that weaker patent rights may result in welfare gains of 46% relative to the status quo. The gains are achieved because weaker patents reduce competition, thus leading firms to postpone patenting.

We propose a theory linking imperfect information to resource misallocation and hence to aggregate productivity and output. In our setup, firms look to a variety of noisy information sources when making input decisions. We devise a novel empirical strategy that uses a combination of firm-level production and stock market data to pin down the information structure in the economy. Even when only capital is chosen under imperfect information, applying this methodology to data from the United States, China, and India reveals substantial losses in productivity and output due to the informational friction. Our estimates for these losses range from 7% to 10% for productivity and 10% to 14% for output in China and India, and are smaller, though still significant, in the United States. Losses are substantially higher when labor decisions are also made under imperfect information. We find that firms turn primarily to internal sources for information; learning from financial markets contributes little, even in the United States.