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We model the welfare consequences of mandates that restrict investors to hold firms with net-zero carbon emissions. To qualify for these mandates, value-maximizing firms have to accumulate decarbonization capital. Qualification lowers a firm's required return by its decarbonization investments divided by Tobin's q, that is, the greenium or the dividend yield shareholders forgo to address the global-warming externality. The welfare-maximizing mandate approximates the first-best solution, yielding welfare gains compared to laissez-faire by mitigating the weather disaster risks resulting from carbon emissions. Our model generates optimal transition paths for decarbonization that we use to evaluate proposed net-zero targets. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online [ABSTRACT FROM AUTHOR]

Motivated by the recent subprime mortgage crisis, we explore whether speculative bubble models of equity based on investor disagreement and short-sales constraints can also provide an explanation for the overvaluation of debt contracts. We find that this is unlikely. Equity bubbles are loud: price and volume go together as investors speculate on capital gains from reselling to more optimistic investors. But this resale option is limited for debt since its upside payoff is bounded. Debt bubbles then require an optimism bias among investors. But greater optimism leads to less speculative trading as investors view the debt as safe and having limited upside. Debt bubbles are hence quiet-high price comes with low volume. We find the predicted price-volume relationship of credits over the 2003-2007 credit boom. © 2013 Elsevier B.V.

In a recent, widely covered press release, Larry Fink, chief executive of the world's largest asset management company, BlackRock, pledged significant resources toward developing sustainable investing, for example by offering [...]

We introduce aggregate transmission shocks to an epidemic model and link firm valuations to infections via an asset pricing framework with vaccines. Infections lower earnings growth but firms can mitigate damages. We estimate a large reproduction number |${\mathcal R}_0$| and transmission volatility for COVID-19. Using these estimates, we quantify the bias of deterministic approximations based on |${\mathcal R}_0$|⁠. Our model generates predictions consistent with the data: unexpected infection resurgence, nonmonotonic mitigation policies, and higher price-to-earnings ratios during a pandemic. Valuations would be significantly lower absent mitigation and a high vaccine arrival rate. [ABSTRACT FROM AUTHOR]

We test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability. Using thirty-four industry portfolios and the broad market index as our test assets, we establish several key results. First, a number of industries such as retail, services, commercial real estate, metal, and petroleum lead the stock market by up to two months. In contrast, the market, which is widely followed, only leads a few industries. Importantly, an industry’s ability to lead the market is correlated with its propensity to forecast various indicators of economic activity such as industrial production growth. Consistent with our gradual-information-diffusion hypothesis, these findings indicate that the market reacts with a delay to information in industry returns about its fundamentals.

Emissions abatement alone cannot address the consequences of global warming for weather disasters. We model how society adapts to manage disaster risks to capital stock. Optimal adaptation—a mix of firm‐level efforts and public spending—varies as society learns about the adverse consequences of global warming for disaster arrivals. Taxes on capital are needed alongside those on carbon to achieve the first best. We apply our model to country‐level control of flooding from tropical cyclones. Learning rationalizes empirical findings, including the responses of Tobin's q, equity risk premium, and risk‐free rate to disaster arrivals. Adaptation is more valuable under learning than a counterfactual no‐learning environment. Learning alters social‐cost‐of‐carbon projections due to the interaction of uncertainty resolution and endogenous adaptive response. [ABSTRACT FROM AUTHOR]