Fatal Errors: The Mortality Value of Accurate Weather Forecasts
with Laura Bakkensen and Derek Lemoine (draft available upon request)
We provide the first revealed-preference estimates of the benefits of routine weather forecasts. The benefits come from how people use the information to reduce mortality from heat or cold. We show that more accurate forecasts reduce mortality if and only if mortality risk is convex in forecast errors, which in turn depends on how people use forecasts. Using data on the universe of mortality events and weather forecasts for a twelve-year period in the U.S., we show that making forecasts 50% more accurate would save 3,500 lives per year, for gross annual benefits of $34 billion. The effects of forecast errors indicate that adaptation becomes less effective if temperatures are either higher or lower than expected. Forecast-driven adaptation is especially important in extreme heat, which suggests that short-run weather forecasts could be an important tool for managing the effects of climate change.
Climate change is projected to severely damage the global economy. Adaptation in response to a changing climate will affect how much damage ultimately occurs. A major source of uncertainty in existing damage estimates is the extent to which they include or exclude such adaptation. This paper shows how to estimate damages while accounting for forward-looking adaptation using an empirical strategy that compares responses to forecasts and to realizations of weather. The empirical strategy is applied to study climate damages and adaptation in a fishery using a novel dataset of climate forecasts and detailed, firm-level records. Empirically, the benefit of forward-looking adaptation is large and important, and accounting for adaptation substantially changes the estimated damages from climate variation. Mechanism analysis shows that firms adapt by reducing production costs and timing entry into the fishery.
Research has shown that procrastination has significant adverse effects on individuals, including lower savings and poorer health. Procrastination is typically modeled as resulting from present bias. In this paper we study an alternative: excessively optimistic beliefs about future demands on an individual's time. The models can be distinguished by how individuals respond to information on their past choices. Experimental results refute the hypothesis that present bias is the sole source of dynamic inconsistency, but they are consistent with optimism. The findings offer an explanation for low takeup of commitment and suggest that personalized information on past choices can mitigate procrastination.
Work in progress
Forward-Looking Labor Adjustment
with Mitch Downey and Nelson Lind
Competition Constrains Climate Adaptation
with Francis Annan and Edem Klobodu
It’s the Heat and the Humidity
with Daniel Bressler and Andrew Jordan Wilson
Peer Review and Scientific Risk Taking
with Richard Carson and Joshua Graff Zivin
Revealing Abatement Costs from Permit Banking Behavior
with Sylwia Bialek
Unchecked climate change will cause precipitation volatility to increase around the world, leading to economic damages in the face of adjustment costs. We estimate these damages for construction---an economically important, climate exposed industry. Empirically, employment falls in response to forecasted rainfall and more so as the forecast horizon increases. This pattern allows for identification of labor adjustment costs via a multi-sector model of local labor markets calibrated to our estimates. When rainfall is anticipatable 1 month ahead, construction firms pay 10% of monthly profit to adjust. They pay less than 1% for rainfall anticipatable 6 months ahead. Without further adaptation or forecast improvements, increased rainfall volatility due to climate change is projected to lead to more costly adjustment.
Investors have known about climate change for decades. Yet it is only recently that several countries—including France, Japan, New Zealand, and the United Kingdom—have developed policies requiring large public companies to regularly disclose information about climate-related financial risks. In March 2022, the US Securities and Exchange Commission (SEC) proposed a climate disclosure rule that, distinctively, would affect all firms publicly traded in the United States regardless of their size or country of incorporation. With the policy’s broad scope, the large size and exceptional liquidity of the US financial market, and the SEC’s influence on securities regulations worldwide, this presents a major opportunity to standardize the way that public firms measure, report, and address climate risks. As the SEC digests a substantial number of public comments on their draft rule ahead of a planned October release of the final rule, we discuss their rationale and consider implications and opportunities for research and policy.
Innovation is important for firm performance and broader economic growth. But breakthrough innovations necessarily require greater risk-taking than more incremental approaches. To understand how managers respond to uncertainty when making research and development decisions, we conducted experiments with master’s degree students in a program focused on the intersection of business and technology. Study participants were asked to choose whether to fund hypothetical research projects using a process that mirrors real-world research and development funding decisions. The experiments provided financial rewards that disproportionately encouraged the choice of higher-risk projects. Despite these incentives, most participants chose lower-risk projects at the expense of projects more likely to generate a large payoff. Heterogeneity analysis and additional experimental treatments show that individual risk preferences predict greater tolerance of high-risk projects and suggest that more appropriate decision making can be learned. Thus, for firms seeking to fund breakthrough R&D, appropriate screening and training of employees may play important roles in increasing the likelihood of success.
The emissions impact of operating an energy storage system depends on the system’s efficiency and the generation mix of the grid. Growth in energy storage, therefore, has the potential to increase emissions. Concerns about this outcome are currently prompting many policies to address the issue. We study a particularly popular policy proposal called the “Clean Peak Standard” that incentivizes storage to discharge during periods of high electricity demand. The stated goal of the policy is to shift storage discharge so that it offsets production from peak generators with high emissions. We show that the policy is largely ineffective at achieving this emissions reduction goal. The policy reinforces existing incentives faced by storage operators, so it does not have a strong effect on discharging behavior. It is also unable to capture high-frequency changes in marginal operating emissions rates. Alternative policies, such as a carbon tax, are more effective at reducing the emissions increase caused by storage operations. Policymakers considering Clean Peak-style policies should instead consider these alternative policies.
We investigate how the largest use of time—sleep—affects productivity. Time use data from the United States allow us to test a model in which sleep improves productivity. Consistent with theory, we find sleep is more complementary to home production than to leisure for nonemployed individuals. We then show that later sunset time reduces worker sleep and earnings. After ruling out alternative hypotheses, we implement an instrumental variables specification that provides causal estimates of the impact of sleep on earnings. A 1-hour increase in location-average weekly sleep increases earnings by 1.1% in the short run and 5% in the long run.
We provide empirical evidence for the existence, magnitude, and economic cost of stigma associated with banks borrowing from the Federal Reserve's Discount Window (DW) during the 2007–2008 financial crisis. We find that banks were willing to pay a premium of around 44 basis points (bps) across funding sources (126 bps after the bankruptcy of Lehman Brothers) to avoid borrowing from the DW. DW stigma is economically relevant as it increased some banks' borrowing cost by 32 bps of their pre-tax return on assets (ROA) during the crisis. The implications of our results for the provision of liquidity by central banks are discussed.
The U.S. Environmental Protection Agency (EPA) is considering a new policy that would prohibit the agency from issuing regulations that rely on studies whose underlying data are not publicly available. While the EPA claims it is pursuing this policy in the interest of transparency, we argue that such a prohibition would greatly hinder, rather than help, the rulemaking process and would likely result in undesirable regulatory outcomes that fail to maximize economic welfare. This policy brief argues that a good faith effort to encourage data availability should focus on forward-looking incentives for transparency rather than the exclusion of a whole class of studies, and that weighting older studies based on their evidentiary value is preferable to removing valuable information from agency consideration.
In terrestrial and coastal systems, the mitigation hierarchy is widely and increasingly used to guide actions to ensure that no net loss of biodiversity ensues from development. We develop a conceptual model which applies this approach to the mitigation of marine megafauna by‐catch in fisheries, going from defining an overarching goal with an associated quantitative target, through avoidance, minimization, remediation to offsetting. We demonstrate the framework's utility as a tool for structuring thinking and exposing uncertainties. We draw comparisons between debates ongoing in terrestrial situations and in by‐catch mitigation, to show how insights from each could inform the other; these are the hierarchical nature of mitigation, out‐of‐kind offsets, research as an offset, incentivizing implementation of mitigation measures, societal limits and uncertainty. We explore how economic incentives could be used throughout the hierarchy to improve the achievement of by‐catch goals. We conclude by highlighting the importance of clear agreed goals, of thinking beyond single species and individual jurisdictions to account for complex interactions and policy leakage, of taking uncertainty explicitly into account and of thinking creatively about approaches to by‐catch mitigation in order to improve outcomes for conservation and fishers. We suggest that the framework set out here could be helpful in supporting efforts to improve by‐catch mitigation efforts and highlight the need for a full empirical application to substantiate this.
Physical processes routinely influence economic outcomes, and actions by economic agents can, in turn, influence physical processes. This feedback creates challenges for forecasting and inference, creating the potential for complementarity between models from different academic disciplines. Using the example of prediction of water availability during a drought, we illustrate the potential biases in forecasts that only take part of a coupled system into account. In particular, we show that forecasts can alter the feedbacks between supply and demand, leading to inaccurate prediction about future states of the system. Although the example is specific to drought, the problem of feedback between expectations and forecast quality is not isolated to the particular model–it is relevant to areas as diverse as population assessments for conservation, balancing the electrical grid, and setting macroeconomic policy.
This paper reviews research on the effect of extreme temperatures on health and human capital accumulation of children. Children are potentially more vulnerable to extreme temperatures due to physiology and behavior. Children are less likely to manage their own heat risk than adults and might have more trouble adapting to high heat. Research shows that high heat would lead to more deaths and harm later life prospects among the young children. The review concludes with recommendations for policies that could help avoid these outcomes.
This paper investigates how losses on subprime mortgage assets during the financial crisis of approximately $300 billion led to rapid and deep declines in the value of a wide range of other financial assets and real economic output. The disproportionate amount of total losses compared with the relatively small size of the initial trigger points to the presence of amplification mechanisms that allowed losses centered in one market to cause a systemwide downturn. The study focuses on two financial amplification mechanisms of relevance to the crisis: balance-sheet amplifiers and adverse-selection amplifiers.