Knowledge that Transforms

We investigate the information contained in foreign exchange (FX) volume using a novel data set from the over-the-counter market. We find volume helps predict next-day currency returns and is economically valuable for currency investors. Predictability implies a stronger return reversal for currency pairs with abnormally low volume and is driven by the component of volume unrelated to volatility, liquidity, and order flow. We rationalize these findings via a simple model, in which FX volume helps reveal the degree of asymmetric information in currency markets. Testing this prediction shows that asymmetric information is uniform across currency pairs but varies across instruments.

We study the effects of patent scope and review times on startups and externalities on their rivals. We leverage the quasi-random assignment of U.S. patent applications to examiners and find that grant delays reduce a startup’s employment and sales growth, chances of survival, access to external capital, and future innovation. Delays also harm the growth, access to external capital, and follow-on innovation of the patentee’s rivals, suggesting that quick patents enhance both inventor rewards and generate positive externalities. Broader scope increases a startup’s future growth (conditional on survival) and innovation but imposes negative externalities on its rivals’ growth and innovation.

The debt-to-GDP ratio negatively predicts cumulative nominal consumption growth up to a 10-year horizon, resulting from the ratio’s ability to forecast lower inflation and real growth. Moreover, the debt-to-GDP ratio is positively associated with yield spreads. I rationalize these facts in a model in which positive shocks to government debt cause lower inflation and growth, making bonds attractive assets. Furthermore, because longer-term bonds are less exposed to current debt shock than are shorter-term bonds, they are better hedges, resulting in high yield spreads in high-debt states. The model highlights the importance of fiscal risk in understanding the Treasury bond market.

Patents and citations are powerful tools increasingly used in financial economics (and management research more broadly) to understand innovation. Biases may result, however, from the interactions between the truncation of patents and citations and the changing composition of inventors. When aggregated at the firm level, these patent and citation biases can survive popular adjustment methods and are correlated with firm characteristics. These issues can lead to problematic inferences. We provide an actionable checklist to avoid biased inferences and also suggest machine learning as a potential new way to address these problems.

We study the efficiency implications of funding directly provided by consumers. Intermediaries fail to finance all efficient projects, and crowdfunding can improve efficiency. Whereas intermediaries value projects based on cash flows, consumers also receive a consumption benefit. Unique to crowdfunding is the ability of consumers to commit to pay for the benefit, and the degree to which they can do so determines its efficiency. We discuss the implications of introducing a resale market for consumers’ claims, as in the case of initial coin offerings, and the speculation that necessarily accompanies such markets. We provide testable and policy-related implications.

We assess the consequences for market quality and welfare of different entry regimes and exchange pricing policies. To do so, we integrate a microstructure model with a free-entry, exchange competition model where exchanges have market power in technological services. Free-entry delivers superior liquidity and welfare outcomes vis-á-vis an unregulated monopoly, but entry can be excessive or insufficient. Depending on the extent of the monopolist’s technological services undersupply compared to the first best, a planner can achieve a higher welfare controlling entry or platform fees. Review of Financial Studies, forthcoming

We study a standard real-option problem in which sequential decisions are made through voting by a group of members with heterogeneous beliefs. We show that, when facing both investment and abandonment timing decisions, the group behavior cannot be replicated by that of a representative “median” member. As a result, members’ disagreement generates inertia—the group delays investment relative to a single-agent case—and underinvestment—the group rejects projects that are supported by a majority of members, acting in autarky. These coordination frictions hold in groups of any size, for general voting protocols, and are exacerbated by belief polarization.

Recent empirical studies have shown that innovative firms heavily rely on debt financing. Debt overhang implies that debt hampers innovation by incumbents. A second effect of debt is that it stimulates innovation by entrants. Using a Schumpeterian growth model with endogenous R&D and financing choices, we demonstrate that this second effect always dominates, so that debt fosters innovation and growth at the aggregate level. Our analysis suggests that the relation between debt and investment is more complex than previously acknowledged and highlights potential limitations of empirical work that solely focuses on incumbents when measuring the effects of debt on investment.

We analyze the effects of a reform of capital regulation for U.S. insurance companies in 2009. The reform eliminates capital buffers against unexpected losses associated with portfolio holdings of MBS, but not for other fixed-income assets. After the reform, insurance companies are much more likely to retain downgraded MBS compared to other downgraded assets. This pattern is more pronounced for financially constrained insurers. Exploiting discontinuities in the reform’s implementation, we can identify the relevance of the capital requirements channel. We also document that the insurance industry crowds outs other investors in the new issuance of (high-yield) MBS.

Using multiple short-sale measures, we examine the predictive power of short sales for future stock returns in 38 countries from July 2006 to December 2014. We find that the days-to-cover ratio and the utilization ratio measures have the most robust predictive power for future stock returns in the global capital market. Our results display significant cross-country and cross-firm differences in the predictive power of alternative short-sale measures. The predictive power of shorts is stronger in countries with nonprohibitive short sale regulations and for stocks with relatively low liquidity, high shorting fees, and low price efficiency.