Knowledge that Transforms

We compare prices of financial derivatives whose payouts are based on future weather outcomes to CMIP5 climate model predictions as well as observed weather station data across eight cities in the US from 2001 through 2020. Derivative prices respond both to short-term weather forecasts for the next two weeks and longer-term warming trends. We show that the long-term trends in derivative prices are comparable to station-level data and climate model output. The one exception is February in the northeastern US, where financial markets price in a polar vortex-induced cooling effect, a recent scientific finding that was not present in the older CMIP5 climate output. When looking at the spatial and temporal heterogeneity in trends, futures prices are more aligned with climate model output than observed weather station trends, suggesting that market participants closely align their expectations with scientific projections rather than recent observations.

Using security-level holdings for all euro-area investors, we study portfolio rebalancing during the quantitative easing program from March 2015 to December 2017. Foreign investors outside the euro area accommodated most of the Eurosystem’s purchases. Duration, government credit, and corporate credit risk did not get concentrated in particular regions or investor sectors. We estimate a demand system for government bonds by instrumental variables to relate portfolio rebalancing to yield changes. Government bond yields decreased by 65 basis points on average, and this estimate varies from 38 to 83 basis points across countries.

We provide a model-free framework for studying the dynamics of the state vector and its risk prices. Specifically, we derive a frequency domain decomposition of the unconditional asset return premium in a general setting with a log-affine stochastic discount factor (SDF). Importantly, we show that the cospectrum between returns and the SDF only displays frequency dependencies through the state vector and that its dynamics and risk prices can be inferred from covariances between asset (portfolio) returns, that is, from the cross-section. Empirically, we find low and high-frequency state vector risk to be differentially priced for US equities.

The efficiency of federal lending guarantees depends on whether guarantees increase lending supply or simply act as a subsidy to lenders. We use notches in the guarantee rate schedule for Small Business Administration (SBA) loans to estimate the elasticity of bank lending volume to loan guarantees. We show significant bunching in the loan distribution on the side of the size threshold that carries a more generous loan guarantee. The excess mass implies that increasing guarantee generosity by one percentage point of loan principal would increase per-loan lending volume by $19,000. Excess mass increases in periods with guarantee generosity, and placebo results indicate that the effect disappears when the guarantee notch is eliminated.

We present evidence on the asset pricing implications of salience theory. In our model, investors overweight salient past returns when forming expectations about future returns. Consequently, investors are attracted to stocks with salient upsides, which are overvalued and earn low subsequent returns. Conversely, stocks with salient downsides are undervalued and yield high future returns. We find empirical support for these predictions in the cross section of US stocks. The salience effect is stronger among stocks with greater limits to arbitrage and during high-sentiment periods. Our results are not explained by common risk factors, return reversals, lottery demand, and attention-grabbing news events.

We develop a model in which a start-up firm issues tokens to finance a digital platform, which creates agency conflicts between platform developers and outsiders. We show that token financing is preferred to equity financing unless the platform expects strong cash flows, has large financing needs, or faces severe agency conflicts. Tokens are characterized by their utility features, facilitating transactions, and security features, granting cash flow rights. While security features trigger endogenous network effects and spur platform adoption, they also dilute developers’ equity stake and incentives so that the optimal level of security features decreases with agency conflicts and financing needs.

How efficient is corporate bankruptcy in the United States? Two frictions, asymmetric information and conflicts of interest among creditors, can cause several inefficiencies: excess liquidation, excess continuation, and excess delay. We find large bankruptcy inefficiencies, mainly due to excess delay. Eliminating information asymmetries would increase average total payouts by 4%, and eliminating conflicts of interest would increase them by 18% more. Without these frictions, 14% more cases would be resolved pre-court, and court cases would be 73% shorter. With less delay, bankruptcy’s indirect costs would be much lower. In contrast, inefficiencies from excess liquidation and excess continuation are quite small.

We examine how search frictions affect merger outcomes. Exploiting firm connections in common bank networks (CBNs) as a channel for reducing search costs, we show that like-buys-like mergers are more probable between firms connected through a CBN. This effect is amplified if the connection has been recently formed or the network contains many plausible choices for merger partners. CBN-facilitated mergers exhibit higher synergy and lower post-merger cost of debt. We confirm that CBNs reduce search costs even after alternative explanations are considered. These findings highlight the importance of search in the process of redrawing firm boundaries.

Ten years after the financial crisis, the central question of what explains the rise and fall in house prices remains unresolved. We provide a unified framework to examine four excess credit supply variables and three speculation variables that have been proposed in the literature. Credit supply variables, particularly subprime share and worse originator share, strongly relate to future zip-code-level house price changes in the boom and bust, whereas none of the speculation variables consistently relate to house prices within MSAs. Pre-trends, supply elasticity, and depressed areas suggest these relations are not driven by lenders anticipating house price growth.

A growing number of studies suggest that common ownership caused cooperation among firms to increase and competition to decrease. We take a closer look at four approaches used to identify these effects. We find that the effects that some studies have attributed to common ownership are caused by other factors, such as differential responses of firms (or industries) to the 2008 financial crisis. We propose a modification to one of the previously used empirical approaches that is less sensitive to these issues. Using this to re-evaluate the link between common ownership and firm outcomes, we find little robust evidence that common ownership affects firm behavior.