Knowledge that Transforms

This paper quantifies how investors’ portfolio demand responds to price changes at long horizons versus short horizons. Using investor trades – changes in portfolios – at different horizons, I first present reduced-form evidence that elasticities increase significantly over time. I then propose a dynamic demand system via a parsimonious partial-adjustment model that recovers the full term structure of elasticities while mitigating long-horizon identification challenges. The estimates imply that price impacts are three times larger at quarterly horizons than in the long-run equilibrium. The model produces a novel, stock-level measure of long-term reversal that avoids the noise of long-horizon return regressions.

How do bank networks facilitate information flows that shape market outcomes? Using international banks’ advisory activities in corporate takeovers as their source of private information, we show in supervisory data that banks with closer ties to the target, but not the acquirer, advisor trade profitably in the target’s stock prior to the deal announcement. This trading behavior is associated with a higher premium paid without compromising deal success. As connected banks’ incentives are aligned only with target shareholders’ interests, which are represented by the target advisor, our evidence suggests that economic incentives determine which banks share information and with whom.

We examine the effects of mandatory board gender quotas on unregulated firms that are connected to regulated ones via interlocking directorates. After the introduction of quotas, connected firms significantly increase their share of female directors relative to similar unconnected firms. The spillover effects are substantial — at least as large as the direct effects on regulated firms, challenging previous claims that quotas have no broader impact on women in business. Our results suggest that quotas indirectly broaden the supply of candidates for connected firms, along dimensions that include, but are not limited to, gender.

Blended finance—the use of public and philanthropic funding to crowd in private capital—has emerged as a potential tool for financing sustainable development. Yet little is known about the design of blended finance contracts. We develop a conceptual framework in which development finance institutions (DFIs) allocate concessional capital across projects to maximize societal impact while crowding in private investors. Our framework highlights a trade-off between sustainability impact and the amount of concessionality required to make projects commercially viable and characterizes how DFIs optimally combine different instruments, including concessional debt, junior equity tranches, and risk management facilities. We then provide empirical evidence on blended finance using deal-level data from a major DFI. Consistent with our conceptual framework, projects with higher anticipated sustainability impact receive greater concessionality. Moreover, concessionality is higher in countries with greater political risk and information asymmetries, and these projects are more likely to include risk management provisions. Our findings provide new evidence on how DFIs deploy catalytic capital to mobilize private investment in sustainable development.

Using a new equilibrium representation, I characterize dynamic, nonstationary risk sharing in a complete-information setting among strategic traders submitting demand schedules and heterogeneous in risk aversion. In equilibrium, more risk-averse (smaller) traders diversify more aggressively due to endogenously lower price impact. This creates term structure effects, where smaller traders dynamically hedge the persistent order flow of larger, slower traders and become the marginal pricers at short horizons. When pre-announced security issuances (e.g., bond reopenings) or predictable trades take place, the model generates the gradual, V-shaped price response observed around these events and delivers new predictions about institutional trading.