Knowledge that Transforms

Regulators condition bank capital on risk but struggle to measure risk accurately. Capital requirements thus rely on inputs from banks’ internal risk models, and banks have discretion over modeling choices. Using novel hand-collected data we show that reported bank risk varies systematically with simulation method, holding period, and historical data size. Hence, modeling choices can be a significant channel of underreporting of risk. Consistent with this presumption we find that less-capitalized banks tend to choose less conservative methods. Moreover, banks using a softer simulation method display higher actual market risk, while reporting lower market risk to regulators.

We investigate how households adjust their shopping behavior in response to financial shocks. Our results show that households visit stores more frequently but buy fewer products and spend less in financial downturns. When money is tight, they switch to cheaper products, use more coupons, and reduce bulk purchases. During financially stressful times, households shrink the set of stores that they visit, mainly by discarding high-end stores, and varying the stores within the same set. Our store-level analysis shows that heightened financial stress in the area is associated with a decline in sales of all products, but much less so for cheaper products. Our results underscore the pivotal role of product markets in facilitating consumption smoothing.

Information often spreads and influences beliefs regardless of its reliability. We show that this occurs in part because indicators of reliability tend to be lost in the process of word-of-mouth transmission. We conduct controlled experiments where participants listen to economic forecasts and pass them on through voice messages. Other participants listen either to original or transmitted audio recordings and report incentivized beliefs. Across various transmitter incentive schemes, a claim’s reliability is lost in transmission much more than the claim itself. Reliable and unreliable information, once filtered through transmission, impact listener beliefs similarly. Mechanism experiments show that reliability is lost not because it is perceived as less relevant or harder to transmit, but because it is less likely to come to mind during transmission. Evidence from our experiments, a large corpus of everyday conversations, and economic TV news shows that contextual cues can bring reliability to mind and induce its transmission, but situations in which people share information seldom contain such cues.

Investors’ return expectations are pivotal in stock markets, but the reasoning behind these expectations is not well understood. This paper explores economic agents’ mental models of what drives returns. We survey the general population, retail investors, financial professionals, and academic experts to investigate how they forecast and explain future returns in scenarios with stale news about future company earnings. We find that investors strongly disagree in their forecasts and reasoning. Most academic experts view markets as efficient. By contrast, most households express a perspective we call “expected earnings reasoning”: they directly equate higher expected earnings with higher expected returns. Professionals are split between market efficiency, mispricing, and expected earnings reasoning. In detailed experiments, we dissect why households adopt expected earnings reasoning. We show that it arises from inattention to how stock-price changes affect investor costs — that is, how much investors must pay to acquire a claim to future cash flows — because the typical format and context of investment problems obscure these cost implications. Our results help connect a series of previously documented anomalies in expectation and trading data and highlight the importance of selective attention and context in shaping reasoning and belief formation.

We propose that the arrival of new information is a source of systematic risk for the holder of a financial security. Using several measures of information flows, we demonstrate that a stock’s sensitivity to market-wide information flow is associated with a robust cross-sectional return premium that is distinct from other return premia. We find that the amount of information impounded in prices through trading has increased in recent years consistent with declining trading costs and the rise of algorithmic trading. We show that the information flows risk premium is increasing through time.

How does demand uncertainty affect firms' investment decisions? We examine this question in the context of electricity‐producing firms' planned investments in new power plants. We measure uncertainty about future electricity demand using plausibly exogenous variation in temperature projections across scientific climate models. The results show that uncertainty increases investment in power plants with flexible production technologies, while reducing investment in less flexible technologies. Overall, the net effect of uncertainty on investment is positive when firms have access to flexible investment opportunities. These findings are consistent with models in which production flexibility shapes the investment response to demand uncertainty.

This paper estimates the cross‐sectional distribution of Epstein‐Zin preferences using the wealth and risky portfolio shares of a large panel of Swedish households. We find modestly heterogeneous risk aversion (standard deviation 0.97, median 7.50) and a meaningfully heterogeneous and right‐skewed time preference rate (TPR; standard deviation 7.31%, median 4.08%) and elasticity of intertemporal substitution (EIS; standard deviation 3.17, median 0.70). Risk aversion and the EIS are only very weakly negatively correlated. We estimate lower risk aversion for households with riskier labor income, and a higher TPR and lower EIS for households that enter our sample with low wealth.