Institutions and Incentives in R&D Finance

Abstract

This dissertation contains three chapters. The first two chapters share a combined emphasis on heterogeneity in innovation, using modern text analysis and patent data to enhance our understanding of innovation over the past four decades. In Chapter 1, I focus on the venture capital industry and the federal government in the U.S. Chapter 2 builds the first comprehensive dataset on Chinese innovation and investigates the role of the Chinese government in supporting innovation, especially in technologies critical for national security. In Chapter 3, I study volatility in public equity markets during conferences held by chairs of the federal reserve. In Chapter 1, I evaluate the allocation of venture capital across 643 technologies using a new technology-level measure of the gestation lag between investment and innovation. Using natural language processing, I assign innovation funding between 1980-2022 from the following sources to these technologies: venture capital firms, public companies, two federal programs that target commercialization of innovation, and the top four federal agencies most important for government funding of innovation. I find that venture capital is disproportionately allocated to technologies with short development lags compared to the federal government; this allocation resembles that by public companies and is shorter-term relative to the distribution of commercial value and scientific opportunities across technologies, as inferred from other sources of innovation funding. I show theoretically and empirically that investors' desire to raise follow-on funds earlier (``fundraising pressure’’) is a potential driver of this short-termism. Chapter 2 studies Chinese innovation in critical technologies between 1985 and 2023. Anecdotally, the Chinese economy has become increasingly innovative over time. However, there is little systematic knowledge about the technologies in which it has progressed, whether it has surpassed the global technological frontier, and what role the government has played in the production of innovation. We address this gap by constructing a comprehensive dataset of Chinese patents. We enhance this dataset with patent-level measures of creativity and influence constructed using text data. These measures of patent value allow us to separate the more influential innovation from the rest, which is difficult to do using the traditional measure of citations in the Chinese context. We also link this dataset to resume data and firm financial data, allowing us to identify inventors and companies with links to the U.S. Using our newly constructed patent dataset, we document a rapid rise in domestic, Chinese innovation in technologies deemed critical by the U.S. Department of Defense. We also find that the Chinese government---via state-owned enterprises, the Seven Sons of Defense universities, and the People's Liberation Army---and U.S.-trained inventors play a disproportionate role in the rise of Chinese innovation in critical technologies. In Chapter 3, we document a shift in the market impact of the press conference given by the Federal Reserve Chair at the close of FOMC meetings. Using intraday trading data, we find that market volatility is more than three times higher during press conferences given by Chair Jerome Powell than during press conferences by his predecessors Janet Yellen and Ben Bernanke. Press conferences since the start of Covid-19 are largely responsible for the heightened market volatility during Chair Powell's conferences. During this period, we find that markets tend to move in the opposite direction during the press conference compared to their movements following the release of the FOMC statement. In contrast, press conferences by Chairs Bernanke and Yellen tended to reinforce the markets' initial reactions to the FOMC statement. Text analysis of press conferences transcripts suggests that Chair Powell's choice of language during the press Q&A correlates with these market movements. We find that Fed communications during this period have been less effective in reducing forward-looking interest rate uncertainty.