Knowledge that Transforms

Flooding is the most costly natural disaster faced by US households, yet policymakers are puzzled by the low take-up rates for flood insurance. Leveraging novel transaction-level data, this paper studies the influence of social interactions on households’ insurance decisions. I show that households increase flood insurance purchases by 1–5 percent when their geographically distant friends are exposed to flooding events or to campaigns for flood insurance. These exogenous shocks to far-away friends should not affect local households’ own insurance decisions except through peer effects. I provide evidence suggesting that social interactions facilitate learning through information dissemination and attention triggering.

We study how mutual fund managers gain an edge in selecting stocks in an era of globalization. We use textual analysis to construct a measure that captures a mutual fund's offshore exposure concentration through holding US multinational firms. We find that funds with a higher offshore concentration index (OCI) perform significantly better, with the difference in four-factor alpha between the top and bottom deciles amounting to 2.95% per annum. Fund managers’ overweighting of firms with operations in certain countries can be partly attributed to their foreign ethnicity. High OCI fund managers have an information advantage regarding firms’ fundamentals, such as earnings.

By applying machine learning to the accurate and cost-effective classification of photos based on sentiment, we introduce a daily market-level investor sentiment index (Photo Pessimism) obtained from a large sample of news photos. Consistent with behavioral models, Photo Pessimism predicts market return reversals and trading volume. The relation is strongest among stocks with high limits to arbitrage and during periods of elevated fear. We examine whether Photo Pessimism and pessimism embedded in news text act as complements or substitutes for each other in predicting stock returns and find evidence that the two are substitutes.

We show that reaching for yield—a tendency to take more risk when the real interest rate declines while the risk premium remains constant—results from imposing a sustainable spending constraint on an otherwise standard infinitely lived investor with power utility. When the interest rate is initially low, reaching for yield intensifies. The sustainable spending constraint also affects the response of risk-taking to a change in the risk premium, which can even change sign. In a variant of the model where the sustainable spending constraint is formulated in nominal terms, low inflation also encourages risk-taking.

Using the expected option-implied variance reduction to measure the sensitivity of stock returns to monetary policy announcement surprises, this paper shows monetary policy announcements require significant risk compensation in the cross section of equity returns. We develop a parsimonious equilibrium model in which FOMC announcements reveal the Federal Reserve’s private information about its interest-rate target, which affects the private sector’s expectation about the long-run growth-rate of the economy. Our model accounts for the dynamics of implied variances and the cross section of the monetary policy announcement premium realized around FOMC announcement days.

In 2012, Texas and two municipalities therein adopted regulations governing the payday loan market. Austin and Dallas enacted supply restrictions limiting the loan-to-income ratio and mandating amortization. The state adopted an information disclosure inspired by Bertrand and Morse (2011) presenting the cost and typical usage of payday loans in easy-to-understand terms. We find that the municipal restrictions led to a 61% decline in loan volume in Austin and a 44% decline in Dallas, with the effects driven by the start of enforcement. The statewide disclosures led to a persistent 12% decline in loan volume in the first six months.

Following state-level legal changes that increase labor dismissal costs, firms increase their innovation in new processes that facilitate the adoption of cost-saving production methods, especially in industries with a large share of labor costs in total costs. Firms with high innovation ability exhibit larger increases in process innovation and capital-labor ratios, an effect driven by both increases in capital investment and decreases in employment. By facilitating the adjustment of the input mix when conditions in input markets change, innovation ability allows firms to mitigate value losses and is a key driver of their performance.

We develop a dynamic model of a platform economy where tokens serve as a means of payment among platform users and are issued to finance investment in platform productivity. Tokens are optimally rewarded to platform owners when token supply (normalized by productivity) is low and burnt to boost franchise value when the normalized supply is high. Although token price is determined in a liquid market, the platform’s financial constraint generates an endogenous token issuance cost that causes underinvestment through the conflict of interest between insiders (owners) and outsiders (users). Blockchain technology mitigates underinvestment by addressing the owners’ time inconsistency problem.

We build a model of the mortgage market in which banks attain their optimal mortgage portfolio by setting rates and steering customers. Sophisticated households know which mortgage type is best for them; naive households are susceptible to banks’ steering. Using data on the universe of Italian mortgages, we estimate the model and quantify the welfare implications of steering. The average cost of the distortion is equivalent to 16% of the annual mortgage payment. A financial literacy campaign is beneficial for naive households, but hurts sophisticated ones. Since steering also conveys information about mortgages, restricting steering might result in significant welfare losses.

We decompose the decrease (1970s–2000) and subsequent recovery (2000–2018) in the fraction of dividend-paying firms. Changes in firm characteristics and proclivity to pay (probability of paying dividends conditional on characteristics) each drive half of the dividend disappearance. A higher proclivity drives 82% of the dividend reappearance. The remaining 18% is driven by a single characteristic: reduced earnings volatility. Changing characteristics are associated with low-profitability, high-earnings-volatility firms. Changing proclivity is associated with stable, profitable firms. Rather than dividend initiations or omissions, newly listed and delisted firms drive trends. Finally, the magnitude and duration of disappearing total payout is substantially smaller than that of dividends, indicating some substitution between dividends and repurchases.