Knowledge that Transforms

When lenders screen borrowers using a menu, they generate a contractual externality by rendering the composition of their competitors’ borrowers worse. Using data from the UK mortgage market and a structural model of screening with endogenous menus, this paper quantifies the impact of asymmetric information on equilibrium contracts and welfare. Counterfactual simulations show that, because of the externality, there is too much screening along the loan-to-value dimension. The deadweight loss, expressed in borrower utility, is equivalent to an interest rate increase of 30 basis points (a 15% increase) on all loans.

A central finding of the theoretical literature on bargaining is that parties’ attitudes towards delay influence bargaining outcomes. However, the ability to endure delays, resilience, is often private information and hard to measure in most real-world contexts. In the context of collective bargaining, we show firms actively attempt to become financially resilient in anticipation of labor negotiations. Firms adjust their financial resilience to respond to the passage of right-to-work laws (RWLs). Unions’ financial structure also responds to RWLs. Our findings suggest resilience is key to understanding the process through which collective bargaining determines wages.

After 1945, expected returns have started to dominate the variation in equity price movements, leaving little room for expected dividend growth. An increase in equity duration can help explain this change. Expected returns vary more for payouts further into the future. Furthermore, because expected returns are more persistent than growth rates, they are more important for longer-duration assets. We provide empirical support for this explanation across three datasets: dividend strips, the long time series for the aggregate market, and the cross-section of stocks. A simple present value model with time-varying duration can largely explain the post-1945 dominance of expected returns.

The blockchain settlement layer facilitates systematic frontrunning, resulting in inefficient block-space allocation. Private transaction pools can reduce these inefficiencies and enhance welfare. However, full adoption is limited by misaligned incentives between users and validators. Validators are reluctant to forgo rents they earn from frontrunning – referred to as maximal extractable value – leading to a partial adoption equilibrium in which frontrunning persists. Our empirical analysis of Ethereum’s Flashbots private pool supports these findings: validators earn higher revenues, users facing greater frontrunning risk are more likely to use the private pool, and attackers’ cost-to-revenue ratios in private pools converge to one.

Frequent, yet uninformed, market timing recommendations by a financial advisory firm generate significant flows for Chilean pension funds. These flows induce substantial changes in the Chilean foreign exchange rate due to the funds’ high allocation to international securities. Local banks provide liquidity to pension funds in the spot market and their hedging transactions propagate the demand fluctuations from the spot to the forward market, resulting in deviations from covered interest rate parity. Using bank balance sheet data, we confirm that banks’ risk bearing constraints create limits to arbitrage.

We examine how stakes affect investor behaviors. In our unique setting, investors trade stocks in real accounts using their own money and simultaneously in a simulated setting. Our real-world within-investor estimation shows that investors exhibit stronger biases and perform worse in higher-stakes real accounts than in lower-stakes simulated accounts. Investors exhibit strong biases in both types of accounts, and the biases in both are strongly positively correlated. Such behavioral consistency suggests that low-stakes experiments are informative about real-world behaviors. Using additional account-level datasets, we demonstrate external validity by documenting a stronger (reverse) disposition effect on stocks (funds) with greater portfolio weights.

We propose a model of lending, payments choice, and privacy in the digital economy. While digital payments enable merchants to sell goods online, they reveal information to their lender. Cash guarantees anonymity, but limits distribution to less efficient offline venues. In equilibrium, merchants trade off the efficiency gains from online distribution (with digital payments) and the informational rents from staying anonymous (with cash). While new technologies can reduce the privacy concerns associated with digital payments, they also redistribute surplus from the lender to merchants. Hence, privacy enhancements do not always improve welfare.

Using a regime change in the commercialization of university innovation in 1980 that strongly increased university incentives to patent and license discoveries, we document that an increase in the supply of commercializable innovation attracts venture capital investment to the region. The Bayh-Dole Act shifted ownership of intellectual property stemming from federally-funded research from the federal government to universities, spurring technology transfer into the local area. Because universities have different technological strengths, each local area surrounding a university experienced an increase after 1980 in commercializable innovation relevant to particular sets of industries which differed widely across university counties. Comparing industries within a county that were more versus less related to the local university's innovative strengths, we show that venture capital dollars after 1980 flowed systematically towards geographic areas and industries affected most by the sudden influx of commercializable innovation from universities. These results persist even when controlling for ex ante geographic and industry distributions of corporate patenting and prior venture financing. The findings support the notion that increased supply of commercializable innovation serves to draw private capital investment to a region.

This paper studies a search-based model of OTC markets in which clients with heterogeneous trading needs direct their trades to one of ex-ante identical dealers. The main insight of the paper is that the way clients sort across dealers shapes dealer-to-dealer trading patterns and, in turn, generates a core–periphery interdealer network structure. Dealers in the model become heterogeneous because they attract different clients in equilibrium. Some dealers attract clients who trade frequently (e.g., index funds); others attract clients with infrequent trading needs (e.g., pension funds). Dealers attracting clients with frequent trading needs receive a larger volume of client orders, trade more with other dealers, and, as a result, form the core of the interdealer network. Conversely, dealers specializing in clients with infrequent trading needs form the periphery. I also show that accounting for client heterogeneity across dealers (a) challenges standard measurements and interpretations of bid–ask spreads and (b) generates predictions on bid–ask spreads and dealer centrality consistent with the empirical literature.

The Tax Cuts and Jobs Act unlocked as much as $1.7 trillion of U.S. multinationals’ foreign cash. We examine the real and financial response to this liquidity shock and find that firms did not increase capital expenditures, employment, R&D, or M&A, regardless of financial constraints. On the financial side, firms paid out only about one-third of the new liquidity to shareholders and retained half as cash. This high retention was not associated with poor governance. The high propensity to retain the liquidity shock as cash, even among well-governed firms with limited financial constraints, is difficult to reconcile with existing theory.