Knowledge that Transforms

We show that search frictions in credit markets affect accepted interest rates and loan sizes and distort consumption. Using data on car loan applications and originations not intermediated by car dealers, we isolate quasi-exogenous variation in both the costs and benefits to searching for credit. After identifying lender-specific policies that price risk discontinuously, we study the differential response to offered interest rates by borrowers who face high and low search costs. High-search-cost borrowers are 10% more likely to accept loan offers with higher markups, consequently originating smaller loans and purchasing older and less expensive cars than lower-search-cost borrowers.

This paper investigates the effects of college tuition on student debt and human capital accumulation. We exploit data from a random sample of undergraduate students in the United States and implement a research design that instruments for realized tuition with relatively large changes to the advertised tuition of students who enrolled at the same school in different cohorts. We find that $5,000 in higher tuition causally reduces the probability of graduating with a graduate degree by 3.1 percentage points and increases student debt by $1,480. Higher tuition also leads to a decline in mortgage balances and an increase in credit card delinquencies.

In this paper, we infer how the estimates of firm value by “optimists” and “pessimists” evolve in response to information shocks. Specifically, we examine returns and disagreement measures for portfolios of short-sale-constrained stocks that have experienced large gains or large losses. Our analysis suggests the presence of two groups, one of which overreacts to new information and remains biased over about 5 years, and a second group, which underreacts and whose expectations are unbiased after about 1 year. Our results have implications for the belief dynamics that underlie the momentum and long-term reversal effect.

The strength of the U.S. dollar has attributes of a barometer of dollar credit conditions, with a stronger dollar associated with tighter dollar credit conditions. We find that following dollar appreciation, exporters that are more reliant on dollar-funded bank credit suffer a greater decline in credit and slowdown in exports, including those exporting to the United States. Our findings shed light on the role of the U.S. dollar in the interaction between financial globalization and international trade and show a novel channel of exchange rate transmission that goes in the opposite direction to the competitiveness channel.

We provide new evidence that disruptions in firms’ access to credit during the Global Financial Crisis significantly affected product innovation in the consumer goods sector. We combine highly granular retail scan data with lending data and find that credit-constrained firms introduced fewer new products, those products were less novel, and new products sold less well. Overall, these findings suggest that disruptions to credit markets impair firms’ ability to compete for profits through new product offerings.

I analyze the inter vivo transfers and bequest decisions of 700,000 individuals during a period when the decision maker receives negative news regarding their life expectancy. The event that initiates the news is a health outcome. Expected mortality increases both the likelihood of transferring wealth to the next generation and the amount transferred. The size of the inter vivo transfer and bequest are positively related to the wealth of the parent and the severity of the diagnosis, regardless of diagnosis-specific demand for informal care. Using a structural life cycle model, I estimate the bequest parameters that are consistent with the causal effect estimates.

We show that analyst behavior changes in response to a randomly assigned shock that exogenously varies the timeliness and cost of accessing mandatory disclosures in the cross-section of investors: analysts reduce coverage and issue less optimistic, more accurate, less bold, and less informative forecasts. Our evidence indicates that analysts reduce a strategic component of their behavior: the changes are stronger among analysts with more strategic incentives like affiliated or retail-focused analysts. We conclude that mandatory disclosure can substitute for analyst information production, which is constrained by investors’ ability to verify forecasts using corporate filings.

We find that firms reduce toxic emissions at their local plants following EPA enforcement actions against nearby plants operated by peer firms that compete in the same product market. These reductions are more pronounced for plants located near socially responsible mutual funds (SRMFs) that hold these plants’ parent firms’ shares. Close proximity to SRMFs is associated with real investment in abatement measures to mitigate emissions. While plants increase emissions again in the long run, such reversals do not occur in plants located near SRMFs. Taken together, our results suggest that local SRMFs complement EPA enforcement in influencing plants’ emissions.

In this paper, we consider conditional measures of lead-lag relations between aggregate growth and industry-level cash flow growth in the United States. Our results show that firms in leading industries pay an average annualized return 3.6 higher than that of firms in lagging industries. Using both time-series and cross-sectional tests, we estimate an annual pure timing premium ranging from 1.2 to 1.7. This finding can be rationalized in a model in which (a) agents price growth news shocks, and (b) leading industries provide valuable resolution of uncertainty about the growth prospects of lagging industries.

Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample performance of option and stock characteristics in predicting future option returns. The nonlinear machine learning models generate statistically and economically sizable profits in the long-short portfolios of equity options even after accounting for transaction costs. Although option-based characteristics are the most important standalone predictors, stock-based measures offer substantial incremental predictive power when considered alongside option-based characteristics. Finally, we provide compelling evidence that option return predictability is driven by informational frictions and option mispricing.