Homes exposed to sea level rise (SLR) sell for approximately 7% less than observably equivalent unexposed properties equidistant from the beach. This discount has grown over time and is driven by sophisticated buyers and communities worried about global warming. Consistent with causal identification of long-horizon SLR costs, we find no relation between SLR exposure and rental rates and a 4% discount among properties not projected to be flooded for almost a century. Our findings contribute to the literature on the pricing of long-run risky cash flows and provide insights for optimal climate change policy.

We propose a new modeling approach for the cross section of returns. Our method, Instrumented Principal Component Analysis (IPCA), allows for latent factors and time-varying loadings by introducing observable characteristics that instrument for the unobservable dynamic loadings. If the characteristics/expected return relationship is driven by compensation for exposure to latent risk factors, IPCA will identify the corresponding latent factors. If no such factors exist, IPCA infers that the characteristic effect is compensation without risk and allocates it to an “anomaly” intercept. Studying returns and characteristics at the stock-level, we find that five IPCA factors explain the cross section of average returns significantly more accurately than existing factor models and produce characteristic-associated anomaly intercepts that are small and statistically insignificant. Furthermore, among a large collection of characteristics explored in the literature, only ten are statistically significant at the 1% level in the IPCA specification and are responsible for nearly 100% of the model’s accuracy.

We find that firms experiencing improvements in crowdsourced employer ratings significantly outperform firms with declines. The return effect is concentrated among reviews from current employees, stronger among early firm reviews, and also stronger when the employee works in the headquarters state. Decomposing employer ratings, we find the return effect is related to changing employee assessments of Career Opportunities and views of senior management. It is unrelated to work-life balance. Employer rating changes are associated with growth in sales and profitability and help forecast one-quarter-ahead earnings announcement surprises. The evidence is consistent with employee reviews revealing fundamental information about the firm.

Elevated levels of government debt raise concerns about their effects on long-term growth prospects. Using the cross-section of US stock returns, we show that (i) high-R&D firms are more exposed to government debt and pay higher expected returns than low-R&D firms, and (ii) higher levels of the debt-to-GDP ratio predict higher risk premiums for high-R&D firms. Furthermore, rises in the cost of capital for innovation-intensive firms predict declines in subsequent productivity and economic growth. We propose a production-based asset pricing model with endogenous innovation and fiscal policy shocks that can rationalize key aspects of the empirical evidence. Our study highlights a novel and distinct risk channel shaping the link between government debt and future growth.