Landlords appear to use stale information when setting rents. Among over 43,000 California rental houses in 2018–2019, those last purchased during 2005–2007 (the peak) rent for 2–3% more than those purchased during 2008–2010 (bust). Neither house nor landlord characteristics explain this “peak-bust rental spread.” To clarify the mechanism, we test cross-sectional predictions from a simple theory of rent-setting. We find empirical support for both reference dependence and distorted beliefs. In the first, monthly payments establish (recurring) reference points, against which gains or losses are measured. In the second, past sales prices distort landlords’ current estimates of house values/rents.

Firms sharing a board member with a media company receive more news coverage. This in turn affects those firms’ financing choices: they issue more bonds, rely less on bank loans, and have lower blockholder ownership. These findings are consistent with media coverage acting as an external governance mechanism that substitutes for monitoring by banks and equity blockholders. The effect of media-linked directors on financing is evident in panel and time series analyses and using two different instrumental variable analyses, suggesting a causal relation.

Using data on 50 million home sales from the last U.S. housing cycle, we document that much of the variation in volume came from the rise and fall in speculation. Cities with larger speculative booms have larger price booms, sharper increases in unsold listings as the market turns, and more severe busts. We present a model in which predictable price increases endogenously attract short-term buyers more than long-term buyers. Short-term buyers amplify volume by selling faster and destabilize prices through positive feedback. Our model matches key aggregate patterns, including the lead–lag price–volume relation and a sharp rise in inventories.

Green assets delivered high returns in recent years. This performance reflects unexpectedly strong increases in environmental concerns, not high expected returns. German green bonds outperformed their higher-yielding non-green twins as the “greenium” widened, and U.S. green stocks outperformed brown as climate concerns strengthened. Despite that outperformance, we estimate lower expected returns for green stocks than for brown, consistent with theory. We estimate expected returns in two ways: ex ante, using implied costs of capital, and ex post, using realized returns purged of shocks from climate concerns and earnings. A theoretically motivated green factor explains much of value stocks’ recent underperformance.

Building parable economies embedding econometricians, we view alternative estimators (Instrumental variables, fuzzy regression discontinuity, natural experiments, OLS, event studies) from the perspective of privately informed decision-makers, e.g., CFOs. Instrumental variable estimates can be misleading since randomization through observable instruments eliminates signal content arising from discretion. If the goal is informing discretionary decisions, rather than predicting outcomes after forced/mistaken actions, instrumentation is problematic, whereas OLS or event studies can be sufficient. The analysis shows that the utility of alternative estimators hinges upon often neglected assumptions about agent/econometrician information sets, as distinct from exclusion restrictions. We recommend parable economy estimation before real-world IV estimation.

Information asymmetries are known in theory to lead to inefficiently low credit provision, yet empirical estimates of the resulting welfare losses are scarce. This paper leverages a randomized experiment conducted by a large fintech lender to estimate welfare losses arising from asymmetric information in the market for online consumer credit. Building on methods from the insurance literature, we show how exogenous variation in interest rates can be used to estimate borrower demand and lender cost curves and recover implied welfare losses. While asymmetric information generates large equilibrium price distortions, we find only small overall welfare losses, particularly for high-credit-score borrowers.

We use detailed assessments of CEO personalities to explore the nature of CEO overconfidence as it is commonly measured. Longholder, the option-based measure of CEO overconfidence introduced by Malmendier and Tate (2005a) and widely used in the behavioral corporate finance and economics literatures, is significantly related to several specific characteristics that are associated with overconfident individuals as well as individuals with lower ability. Similar relations hold for overconfidence measures based on CEOs’ earnings guidance. Investment-cash flow sensitivities are larger for both Longholder and less able CEOs. After controlling for ability and other characteristics, Longholder CEOs’ investments remain significantly more sensitive to cash flows. These results suggest that overconfidence, as measured by Longholder, is correlated with lower ability but still reflects empirically distinct aspects of overconfidence.

How are financial markets pricing the monetary policy outlook? We use surveys to decompose excess returns on money market instruments into expectation errors and term premia. Excess returns are primarily driven by expectation errors, whereas term premia are negligible. Investors face challenges when learning about the Federal Reserve’s response to large, but infrequent, negative shocks in real-time. Rather than reflecting risk compensation, excess returns stem from investors underestimating how much the central bank eases policy in response to such rare shocks. We show, for the US and internationally, that expectation errors imply excess return predictability from past stock returns.

We document that (i) debt-to-equity ratios and levered equity betas negatively covary with the market risk premium in distressed firms; (ii) the negative covariance generates negative alphas among those firms. We build a dynamic credit risk model to understand the negative covariance between equity betas and the market risk premium, via endogenous and dynamic debt financing over the business cycles. Because of endogenous debt financing and distress, our model naturally connects the negative failure probability-return relation to the positive distress risk premium-return relation.

Fund trades and stock prices vary systematically with the quarterly reporting cycle. Funds accelerate trades that complete the building of existing positions at quarter-end but delay trades that initiate the building of new positions until the start of the new quarter. Evidence suggests these trade dynamics are driven by a dual desire to make disclosures more informative about future holdings but avoid disclosing incomplete positions. Consistent with disclosure-based motives unrelated to new information about intrinsic values driving these quarterly trade dynamics, both stock price informativeness and commissions paid by funds drop at quarter-end.