About Me

Welcome! I am an Assistant Professor in the economics department at the University of Oklahoma specializing in energy economics, environmental economics, and law and economics. I am also an affiliated faculty member at the OU Institute for Public Policy Research and Analysis.

In my current work, I use applied empirical methods and causal inference to understand the effect of assigning liability for low probability, high severity events on firm precaution to prevent such events. To further this research agenda, I work with detailed administrative data on California’s electricity distribution infrastructure and tools from atmospheric science to develop a causal empirical framework relating a firm’s precaution to the level of liability it faces.

Research

    Working Papers

    The Precautionary Consequences of Wildfire Liability: Evidence from Power Shutoffs in California
    Across all sectors of the U.S. economy, regulators use liability regulations to encourage firms to take actions that reduce the costs associated with low probability, high severity events such as oil spills and production defects. Despite the widespread use of these regulations, there is limited evidence of their effectiveness in influencing firms’ tradeoff between expected liability cost and incentives for precautions. This study provides causal evidence of firm responses to the entire distribution of potential liability and quantifies the distribution of liability costs between firms and the public by studying power line-ignited fires in California’s electric utility sector. In this setting, when a power line-ignited fire damages a structure, the owner of the power line assumes the cost. Using exogenous variation in the replacement cost of structures that lie downwind of power lines, I find that firms increase their precaution by 130% in response to a $680 million increase in liability. In the short run, the estimates from this study imply that the implemented liability regulation had welfare costs up to $7 billion.

    Can the Low-Carbon Transition Energize Labor Markets? Evidence from Wind Electricity Investments in the U.S.
    with Olivier Deschênes

    Most western countries have made commitments or enacted policies aiming to transform their economies to become carbon-neutral by 2050. Many of the proposed policies to reduce carbon emissions are also promoted as engines of job creation and local economic development. While low-carbon transition policies continue to be debated and proposed, none have been implemented for a long enough period of time to permit an empirical evaluation of their impact.

    This paper uses the natural experiment provided by the rapid deployment of wind electricity projects in the United States over the period 2000-2019 to shed light on whether the low-carbon transition can deliver long-lasting and high-quality jobs. We compile detailed data on the location and operation date of 55,000 wind turbines, combined with county-level data on employment and earnings to estimate the impact of wind projects on employment rates and earnings. Our research design uses two-way fixed effects regression, stacked difference in differences (Cengiz et al. 2019), and the doubly robust estimator proposed by Callaway and Sant’Anna (2021). The empirical analysis points to a small, but durable positive effect of wind electricity investments on local labor market outcomes. Overall, the results suggest that the deployment of 100 GW of wind electricity production capacity over the last two decades created close to 150,000 jobs.

    Publications

    "The Impact of North American Winter Weather Regimes on Electricity Load in the Central United States", npj Climate and Atmospheric Science, 2024.
    with Oliver T. Millin and Jason Furtado
    Extreme wintertime cold in the central United States (US) can drive excessive electricity demand and grid failures, with substantial socioeconomic effects. Predicting cold-induced demand surges is relatively understudied, especially on the subseasonal-to-seasonal (S2S) timescale of two weeks to two months. North American winter weather regimes are atmospheric tools that are based on persistent atmospheric circulation patterns, and have been linked to potential S2S predictability of extreme cold in the central US. We study the relationship between winter weather regimes and daily peak load across 13 balancing authorities in the Southwest Power Pool. Anomalous ridging across Alaska, the West Coast, and Greenland drive increases in demand and extreme demand risk. Conversely, anomalous troughing across the Arctic and North Pacific reduces extreme demand risk. Thus, weather regimes may not only be an important long-lead predictor for North American electricity load, but potentially a useful tool for end users and stakeholders.

    "Causal Effects of Renewable Portfolio Standards on Renewable Investments and Generation: The Role of Heterogeneity and Dynamics", Resource and Energy Economics, 2023.
    with Olivier Deschênes and Gavin McDonald
    [Coverage: NBER Digest]

    "Well setbacks limit California’s oil supply with larger health benefits and employment losses than excise and carbon taxes", Nature Energy, 2023.
    with Ranjit Deshmukh, Paige Weber, Olivier Deschênes, David Lea, Kyle Meng, Danae Hernandez Cortes, Tia Kordell, Ruiwen Lee, Tracey Mangin, Measrainsey Meng, Sandy Sum, Vincent Thivierge, and Anagha Uppal

    "Equitable Low-Carbon Transition Pathways for California’s Oil Extraction", Nature Energy, 2023.
    with Ranjit Deshmukh, Paige Weber, Olivier Deschênes, David Lea, Kyle Meng, Danae Hernandez Cortes, Tia Kordell, Ruiwen Lee, Tracey Mangin, Measrainsey Meng, Sandy Sum, Vincent Thivierge, and Anagha Uppal

    Selected Work in Progress

    The Value of Electricity Transmission in Reducing Renewable Generation Uncertainty
    Using panel data on the universe of power plants in two large U.S.-based power pools, I study how uncertainty in renewable electricity generation affects system costs and electricity transmission. Uncertainty in renewable generation of electricity comes from its intermittent nature (variation across hours due to resource availability) and difficulty in predicting how much electricity supply will be available from renewable sources in future hours (forecast error). The unique context allows me to separately show how uncertainty in local and foreign renewable generation affects system costs when electrical grids are interconnected. This study shows that transmission networks reduce system costs associated with local and foreign uncertainty by increasing allocative efficiency across electricity markets. Between 2017 and 2021, this private trade surplus was $570 million annually or 84% of annual regional spending on transmission networks.

Policy Work

CV

Click here for the most up to date version of my CV.

Contact Me

308 Cate Center Dr
Cate Center 1, Room 335
Norman, OK 73072
christopher.malloy@ou.edu
Twitter: @cmalloy_econ