We document the presence of market power in the equity securities lending market and evaluate its impact on different investor groups and valuations. Our analysis reveals high market concentration, non-competitive fees, and low inventory utilization in the cross-section of stocks. Motivated by this evidence, we develop and estimate a dynamic asymmetric-information model that sheds light on the benefits of this current market structure for both security lenders and short sellers. We find that lending fee income raises shares lenders’ equity valuations by 1.5% for large-cap, low-fee stocks, by up to 25% for small-cap stocks, and by even more than 100% for nano-cap stocks. Our model yields estimates of the distribution of alphas from shorting different segments of the cross-section of stocks, indicating that fees reduce short sellers’ profits by about 60%.

Countries committed to environmental goals, such as mitigating global warming, face the challenge that pollution and emissions originate to a large extent from  activities in foreign countries. While governments may attempt to tax domestic firms' sourcing of inputs from brown international firms, such approaches often have to rely on voluntary disclosures by the foreign trade partners. Addressing this issue, we examine a government's optimal regulatory policy when domestic firms' international supply chain partners set their own disclosure standards. We show that tax schedules should generally be a non-linear function of the disclosed externalities, contrasting with current practices in carbon credit markets. Our analysis characterizes how domestic households' exposure to the damages associated with global externalities shape both a government's optimal regulatory interventions and the granularity of foreign firms' voluntary disclosures.

I develop a tractable dynamic model of financially distressed firms' interactions with large equity investors. The framework quantitatively matches key empirical facts related to distressed equity issuances, including the provision of substantial discounts in private placements of public equity. The model captures the pivotal signaling role played by large distressed equity investors and facilitates counterfactual analyses that distill blockholders' externalities on other claimants. The analysis reveals that blockholders' impact on inefficient default is generically non-monotone. Whereas inefficiencies are exacerbated for intermediate levels of distress, they are alleviated in deep distress, when blocks are acquired in last-minute rescue interventions. The setting proposes a novel set of modeling choices that yield global solutions in environments with optimal default and learning.

We present a novel modeling approach for granular general equilibrium economies with persistent heterogeneity that yields exact global solutions. A key feature of our approach is the use of stochastic lumpy adjustment (SLA) technologies. The associated stochastic structure can capture any degree of granularity in adjustments of asset positions, and is thus more flexible than standard technologies. We show how SLA technologies can be employed in the context of both capital investment and the trading of financial assets. As our approach does not impose any restrictions on the shape of the state variable distribution, it can also be used to evaluate the conditions under which previous solution methods are likely to succeed. Obtaining exact solutions in these granular economies primarily involves inverting sparse matrices, a computational operation that can take full advantage of recent advances in high-performance parallel computing architectures.

We analyze the effectiveness of preventive investments aimed at increasing agents' life expectancy, with a focus on influenza and COVID-19 mitigation. Maximizing overall life expectancy requires allocating resources across hazards so as to equalize investments' marginal effectiveness. Based on estimates for the marginal effectiveness of influenza vaccines, we determine the level of COVID-19 mitigation investments that would imply such equalization. Given current projections for COVID-19 mitigation costs, our results suggest that wide-spread influenza vaccination would be an effective life-preserving investment.

This paper studies intertemporal information acquisition by agents that are rational Bayesian learners and that dynamically optimize over consumption, investment in capital, and investment in information. The model predicts that investors acquire more information in times when future capital productivity is expected to be high, the cost of capital is low, new technologies are expected to have a persistent impact on productivity, and the scalability of investments is expected to be high. My results shed light on the economic mechanisms behind various dynamic aspects of information production by the financial sector, such as the sources of variation in returns on information acquisition for investment banks or private equity funds.

Episodes of boom-bust cycles tend to occur in sectors with recent arrivals of new technologies and are often related to excessive funding by the financial sector. In this paper, I develop a dynamic general equilibrium model consistent with a role for the financial sector in propagation during such episodes. I extend a standard Schumpeterian growth model by incorporating (a) a monopolistically competitive financial sector and (b) time-varying technological conditions in real sectors. I identify two propagation channels. The first operates through financial firms' acquisition of sector-specific knowledge (skill channel); financial firms chase "hot sectors" and thereby amplify fluctuations. The second channel originates in an interaction between competition in the financial sector and patent races in product markets (competition channel). Financial firms' temporary competitive advantages in access to new ventures imply market segmentation: financial firms maximize the surplus generated by the client firms they can currently attract, anticipating competing financial firms' future screening and funding decisions. Relative to the Pareto optimum, the competition channel generates overinvestment in sectors with temporarily improved technological conditions; excessively high growth in these sectors comes at the cost of lower growth in the economy as a whole. The model links financial propagation to time variation in the cross section of asset prices. Exposures to aggregate risk dampen amplification effects.