Knowledge that Transforms

We examine the pricing of sustainability-linked bonds (SLBs), where the cash flows depend on the bond issuer achieving one or more Environmental, Social and Governance (ESG) goals. Investors are willing to accept a 1–2bps lower yield due to the bond’s ESG label, providing evidence of investors caring about environmental impact. Furthermore, we find the average probability of missing the target is 14%–39% so firms set ESG targets that are easy to reach. We find that the SLB market is efficient: the prices of SLBs depend strongly on the size of the potential penalty and there is no evidence of mispricing. Finally, our results suggest that SLBs serve as financial hedges against ESG risk.

We study the use and economic impact of AI technologies. We propose a new measure of firm-level AI investments using employee resumes. Our measure reveals a stark increase in AI investments across sectors. AI-investing firms experience higher growth in sales, employment, and market valuations. This growth comes primarily through increased product innovation. Our results are robust to instrumenting AI investments using firms' exposure to universities' supply of AI graduates. AI-powered growth concentrates among larger firms and is associated with higher industry concentration. Our results highlight that new technologies like AI can contribute to growth and superstar firms through product innovation.

We show that trade credit flows increase when a firm in a production network becomes a less reliable supplier due to an operating shock. Affected firms extend more trade credit when their customers have lower switching costs or expect more disruption. Suppliers that are more dependent on the affected firms facilitate the trade credit extension. However, when financial constraints at the affected firms and their suppliers prevent the increase in trade credit, customers sever their relationships with the affected firms, and the sales of the affected firms and their suppliers drop, suggesting that trade credit enhances production network stability.

We develop a general equilibrium model of self-fulfilling bank runs. The key novelty is the way in which the banking system’s assets and liabilities are connected. Banks issue loans to entrepreneurs who sell goods to households, which in turn pay for the goods by redeeming bank deposits. The return on bank assets is thus contingent on households being able to withdraw their deposits. In a run, not all households that wish to consume manage to withdraw, since part of banks’ cash reserves end up in the hands of households without consumption needs. This misallocation of liquidity lowers revenues of entrepreneurs and bank asset returns, thereby rationalising the run. Interventions that restrict redemptions in a run can be self-defeating due to their negative effect on demand in goods markets. We show how runs can sometimes be prevented with combinations of deposit freezes and redemption penalties as well as with the provision of emergency liquidity.

A critical question facing speculators contemplating to trade on private information is whether their signal has already been priced in by the market. In our model, speculators assess the novelty of their information based on recent price movements, and market makers are aware that speculators might be trading on stale news. An asymmetric response to past price movements ensues: after price increases, buy volume – because it may result from stale news trading – has a lower price impact than sell volume (and vice versa after price decreases). Consequently, return skewness is negatively related to lagged returns. We find strong support for these and other predictions using a comprehensive sample of US stocks.

We investigate how access to robo-advisors impacts the financial investment and welfare of less-wealthy investors. We leverage a quasi-experiment where a major U.S. robo-advisor significantly expands access by reducing its account minimum, increasing participation by middle-class investors but not the poor. A benchmark model calibrated to portfolio-level data rationalizes this increase: middle-class investors want sophisticated investing but cannot achieve it themselves. Their welfare rises moderately, driven by advanced features like multi-dimensional glide-paths and additional priced risk factors. Middle-age investors gain three times more than millennials. Our results reveal novel margins of demand for robo-advisors, helping explain their sustained growth.

We survey thousands of affluent American investors to examine the relationship between personalities and investment decisions. The Big Five personality traits correlate with investors' beliefs about the stock market and economy, risk preferences, and social interaction tendencies. Two personality traits, Neuroticism and Openness, stand out in their explanatory power for equity investments. Investors with high Neuroticism and those with low Openness tend to allocate less investment to equities. We examine the underlying mechanisms and find evidence for both standard channels of preferences and beliefs and other nonstandard channels. We show consistent out-of-sample evidence in representative panels of Australian and German households.

We show that firms collect almost 70% of their cash flows in the second half of the fiscal year, and that firms that collect more cash by year-end earn a 6.8% higher per annum risk premium and save more cash. We rationalize these facts in a quantitative investment-based asset pricing model. Immediate cash payments negatively affect profitability, but reduce equity financing costs by increasing information transparency. Financially constrained firms optimally collect more cash at year-end when firms’ performance attracts more attention and information transparency is more valuable. Such behavior further results in greater exposure to aggregate productivity and financial shocks.

Endogenous cycles emerge through the two-way interaction between lending standards and production fundamentals. Lax lending standards in booms lead to low interest rates and high output but the deterioration of future loan quality. Low borrower quality in turn precipitates tight standards: the economy enters a recession with high credit spreads and low output but a gradual improvement in the quality of loans. This eventually triggers a shift back to a boom with lax lending, and the cycle continues. The capitalization of expert investors determines the strength of capital reallocation in recessions. Furthermore, although the constrained efficient economy is often cyclical, it features both a static and a dynamic externality in credit supply, hence differing from the decentralized equilibrium.

Do investors reach for yield when interest rates are low and does this behavior affect the housing market? Using the unique setting and data of 18th-century Amsterdam, I show that reach-for-yield behavior of wealthy investors resulted in a large boom and bust in house prices and major changes in rental yields. Exploiting changes in the supply of bonds, I show that investors living off capital income shifted their portfolios towards real estate and other higher-yielding assets when bond yields were low and decreasing. This behavior exacerbated house price volatility and increased housing wealth inequality.