About

Professor Christopher R. Knittel is the Associate Dean for Climate and Sustainability and the George P. Shultz Professor of Energy Economics in the Sloan School of Management at MIT. He directs the Center for Energy and Environmental Policy Research, established in 1977 as the hub for social science work related to energy and the environment at MIT. He is also the director of MIT’s Climate Policy Center and co-directs the Environmental and Energy Economics Program at the National Bureau of Economic Research, alongside Meredith Fowlie at UC Berkeley. His research studies consumer and firm decision-making and their implications for the benefits and costs of environmental and energy policy. He often interacts with policymakers to discuss his research findings and current research needs in the field. His current work involves studying how the costs of climate change policy vary across households and firms and how these differences influence policy choices. Professor Knittel employs a variety of empirical methods, including large-scale randomized control trials, machine learning techniques, and structural models, to advance understanding in energy economics and environmental policy.

Research topics

• Computer Science
• Economics
• Artificial Intelligence
• Microeconomics
• Engineering
• Econometrics
• Mathematics
• Political Science
• Statistics
• Market economy
• Geography
• Public administration
• Natural resource economics
• Finance
• Management
• Demography
• Business
• Industrial organization
• Monetary economics
• Electrical engineering

Selected publications

• The Differential Impacts of Critical Mineral Prices and Oil Prices on the Economy

  SSRN Electronic Journal · 2026-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Tariffs, Global Value Chains, and the Incidence of Protection: Evidence from US Automobiles

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access
  PublisherDOI

• Challenges to expanding EV adoption and policy responses

  Edward Elgar Publishing eBooks · 2025-06-19 · 9 citations

  book-chapter1st authorCorresponding
  PublisherDOI

• The Role of Tailored Information on Household Heat Pump Demand

  AEA Randomized Controlled Trials · 2025-03-25

  dataset
  PublisherDOI

• An Economic Perspective on the EPA’s Clean Power Plan — Cross-State Coordination Key to Cost-Effective CO₂ Reductions

  WORLD SCIENTIFIC eBooks · 2025-05-01

  book-chapter
  PublisherDOI

• Charging Uncertainty: Real-Time Charging Data and Electric Vehicle Adoption

  SSRN Electronic Journal · 2025-01-01 · 3 citations

  articleOpen access
  PublisherDOI

• Flexible Data Centers and the Grid: Lower Costs, Higher Emissions?

  National Bureau of Economic Research · 2025-07-01 · 3 citations

  reportOpen access1st authorCorresponding

  Data centers are among the fastest-growing electricity consumers, raising concerns about their impact on grid operations and decarbonization goals.Their temporal flexibility-the ability to shift workloads over time-offers a source of demand-side flexibility.We model power systems in three U.S. regions: Mid-Atlantic, Texas, and WECC, under varying flexibility levels.We evaluate flexibility's effects on grid operations, investment, system costs, and emissions.Across all scenarios, flexible data centers reduce costs by shifting load from peak to off-peak hours, flattening net demand, and supporting renewable and baseload resources.This load shifting facilitates renewable integration while improving the utilization of existing baseload capacity.As a result, the emissions impact depends on which effect dominates.Higher renewable penetration increases the emissions-reduction potential of data center flexibility, while lower shares favor baseload generation and may raise emissions.Our findings highlight the importance of aligning data center flexibility with renewable deployment and regional conditions.

  PublisherDOI

• Charging Uncertainty: Real-Time Charging Data and Electric Vehicle Adoption

  National Bureau of Economic Research · 2025-01-01 · 4 citations

  reportOpen access

  Charging infrastructure is critical to electric vehicle (EV) adoption, but for chargers to be most useful, EV drivers need to know in real time where they are and whether they are working and available. We investigate the availability of real-time data from DC fast chargers on six major US Interstates and model the impacts of expanding access to real-time data to all DC fast chargers near highways. On average, between March and August 2024, 32.9% of DC fast charging stations adjacent to those six Interstates provided their real-time status on PlugShare, a major charge-finding app, with gaps of up to 1, 308 miles without real-time data. Further, we survey potential car buyers and EV owners and find low credibility of currently-available real-time data. We incorporate this data into a two-sided model of consumer vehicle choice and charging station build-out adapted from Cole et al. (2023). If universal real-time data is accompanied by improved charger uptime and driver confidence in the accuracy of the real-time data, we predict that the EV share of new vehicle sales would grow by 8.0 percentage points in 2030, expanding the EV fleet by 13.2%, and reducing 2030 carbon emissions by 22.5 mmt, versus baseline projections for 2030.

  PublisherDOI

• The Role of Tailored Information on Household Heat Pump Demand

  AEA Randomized Controlled Trials · 2025-03-25

  dataset
  PublisherDOI

• Planes Overhead: How Airplane Noise Impacts Home Values

  National Bureau of Economic Research · 2025-10-01

  reportOpen access
  PublisherDOI

Frequent coauthors

• Kenneth Gillingham

  128 shared

• Κωνσταντίνος Μεταξόγλου

  Carleton University

  87 shared

• Arthur van Benthem

  83 shared

• Mark R. Jacobsen

  83 shared

• James Sallee

  77 shared

• André Trindade

  59 shared

• Stephen P. Holland

  Yale University

  52 shared

• Jose-Miguel Abito

  Cornell University

  49 shared

Awards & honors

• Professor of the Year Award (2024)
• IJIO Best Empirical Paper Award (2020)