Knowledge that Transforms

We study the role of brokers in selection markets. We find broker-clients in the Canadian mortgage market are observationally different from branch-clients. They finance larger loans with more leverage and longer amortization. We build and estimate a model of mortgage demand to disentangle three possible explanations for these riskier product choices: (1) selection on observables, (2) unobserved borrower preferences for riskier loans, and (3) a causal effect of brokers. Although we find that brokers influence product choices, the main reason borrowers choose high-leverage products is unobserved preferences. Borrowers prefer larger loans and brokers facilitate qualification for them.

I study the real effects of centralized derivative markets using the staggered introduction of futures contracts for different steel products in the United States. Employing a difference-in-differences strategy, I find that the arrival of centralized futures markets improves price transparency and risk management in the underlying product market: price dispersion decreases and steel producers increase their hedging activity. Moreover, market share is reallocated toward low-cost producers, while product prices, producers’ profits, and valuations decrease. Overall, the results indicate that centralized futures markets foster competition in the product market.

This paper examines whether capital structure is irrelevant for enterprise value and investment when investors care about environmental, social, and governance issues, which we refer to as “ESG-Modigliani-Miller” (ESG-MM). Theoretically, we show that ESG-MM holds with linear pricing and additive ESG. ESG-MM means that issuing low-yielding green bonds does not lower the overall cost of capital because it makes the issuer’s other securities browner. Hence, a firm’s incentive to make a green investment does not depend on its financing choice. We provide suggestive evidence of failure of ESG-MM, implying that firms and governments can exploit inconsistent ESG attribution or segmented markets.

How should an investor value financial data? The answer is complicated because it depends on the characteristics of all investors. We develop a sufficient statistics approach that uses equilibrium asset return moments to summarize all relevant information about others’ characteristics. Our approach values public or private data, data about one or many assets, and data relevant for dividends or sentiment. While different data types, of course, have different valuations, heterogeneous investors also value the same data very differently. This finding suggests a low price elasticity for data demand. Heterogeneous investors’ data valuations are also affected very differentially by market illiquidity.

In an investment experiment, we show variations in information affect beliefs and decision-making within the information-beliefs-decisions chain. Subjects observe the time series of a risky asset and a signal that, in random rounds, helps predict returns. Subjects form extrapolative forecasts following a signal they perceive as useless, and their investment decisions underreact to their beliefs. If the same subjects perceive the signal as predictive, they rationally use it in their forecasts, they no longer extrapolate, and they rely significantly more on their forecasts when making risk allocations. Analyzing investments without observing forecasts and information sets leads to erroneous interpretations.

We offer new evidence on the relationship between competition and innovation that overcomes two measurement difficulties compromising the extant literature: aggregation at either firm level (or higher) of innovative activity, and the mediating influence of distance-to-technological-frontier. FDA awards of Breakthrough Therapy Designations (BTDs) on specific drugs, instrument stochastic unleveling of therapeutic (ie, product) markets. Rivals’ innovative responses generally show an inverted-U pattern in ex ante competitiveness of the shocked market. However, the shape of the relation changes with distance to technological frontier in that market, proxied by whether the rival project uses one of the technologies embedded in the BTD-awarded drug.

We develop an economic model to compare equilibrium security of Proof-of-Work (PoW) versus Proof-of-Stake (PoS) blockchains. We derive general conditions to determine when PoW blockchains are more secure than otherwise equivalent PoS blockchains and vice versa. Applying real-world parameter values to these conditions, we demonstrate that PoS blockchains are more secure than otherwise equivalent PoW blockchains. Furthermore, we demonstrate that PoS’s security advantage over PoW is particularly salient for high-scale blockchains.

In the United States, a significant number of criminal defendants are held in pretrial detention and face substantial financial burdens. Matching individual-level criminal case records to household-level financial data, we exploit the quasi-random assignment of court commissioners to study how pretrial detention affects household solvency. We find that pretrial detention results in higher rates of household insolvency, driven by higher rates of chapter 7 bankruptcies and judgment liens, and higher foreclosure rates during periods of decreasing house prices. We document that the effects spill over to family members and show that home equity can cushion households from insolvency.

We document that persistent aggregate capital flows to hedge and mutual funds predict monthly factor returns with an out-of-sample R2 reaching 6.6%. Transient flows display no such power despite being more predictable. We show—both empirically and theoretically—that persistent flows’ predictive power stems from active fund managers’ capital constraints. As a result, managers invest persistent, but not transient, capital flows into factor trading strategies, leading to factor-return predictability and factor momentum, yet greater price efficiency. Our key insight is that capital-constrained managers account for both current and anticipated future flows in the arbitrage sector, thereby incorporating the dynamics of capital into their strategies.

We develop a continuous-time general equilibrium model with intermediaries at the heart of international financial markets. Global intermediaries bargain with households and extract rents from providing access to foreign claims. By tilting state prices, intermediaries’ market power breaks monetary neutrality and makes international risk-sharing inefficient. Despite having zero net positions, markups charged by intermediaries significantly distort international asset prices, affecting exchange rate dynamics and their response to shocks. Our model can reproduce patterns consistent with several well-known exchange rate puzzles, such as deviations from uncovered and covered interest parity. All equilibrium quantities are derived in closed form, allowing us to pin down the underlying economic mechanisms explicitly.