About

Robert K. Kaufmann is a Professor at Boston University in the Department of Earth & Environment. His research focuses on three main areas: global climate change, world oil markets, and land-use changes. In the realm of climate change, he investigates whether humans are causing climate change and how such changes impact natural ecosystems and human well-being. His work on world oil markets combines geological, engineering, and economic determinants to analyze oil supply, demand, and prices, with a particular focus on the influence of market fundamentals and speculation on large price fluctuations. Additionally, he studies the relationship between socioeconomic development and land-use change by linking satellite imagery to ground-based economic activity measures, applying these techniques to regions such as the Pearl River Delta in China and soybean production in the Brazilian Amazon. Beyond his academic pursuits, Kaufmann is a founding partner of First Fuel Software, a company that conducts energy audits of commercial buildings using mathematical and engineering techniques, significantly reducing costs and accelerating energy conservation efforts.

Research topics

• Economics
• Physics
• Environmental science
• Automotive engineering
• Mathematics
• Computer Science
• Business
• Engineering
• Electrical engineering
• Monetary economics
• Environmental economics
• Macroeconomics
• Financial economics
• Atmospheric sciences
• Transport engineering
• Geography
• Geology
• Ecology
• Forestry
• Agroforestry
• Biology
• Algorithm

Selected publications

• Rising Airborne Fraction Hidden by Inaccurate Measures of Land Use/Cover CO2 Emissions

  OpenBU (Boston University) · 2026-03-26

  dataset1st authorCorresponding
  Publisher

• Price Discovery in a Financialized Oil Market

  The Energy Journal · 2026-01-17

  article

  We postulate that financialization expands price discovery for crude oil and test this hypothesis by examining causal relations between daily returns to prices for crude oil and stocks of nine oil companies. We find that daily returns to stocks of oil companies ‘Granger cause’ daily returns to the price of crude oil ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mrow> <mml:mi>Stock</mml:mi> <mml:mspace width="0.25em"/> <mml:mo>→</mml:mo> <mml:mi>Price</mml:mi> </mml:mrow> </mml:math> ), which indicates that stock returns have information about future and spot prices beyond variables that represent market fundamentals and financial conditions. This result suggests that financialization expands price discovery for crude oil beyond market fundamentals. We also find that returns to futures and spot prices for crude oil ‘Granger cause’ returns to oil companies ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mrow> <mml:mi>Price</mml:mi> <mml:mspace width="0.25em"/> <mml:mo>→</mml:mo> <mml:mi>Stock</mml:mi> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> </mml:math> . This extends previous results that returns to oil prices correlate with the profitability of oil companies, which drive returns to oil companies. Furthermore, we find that strength of financialization changes over time due to changes in the returns to holding oil as a commodity, which we proxy by convenience yields. Both the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mrow> <mml:mi>Stock</mml:mi> <mml:mo>→</mml:mo> <mml:mi>Price</mml:mi> </mml:mrow> </mml:math> and the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mrow> <mml:mi>Price</mml:mi> <mml:mo>→</mml:mo> <mml:mi>Stock</mml:mi> </mml:mrow> </mml:math> causal relations weaken when convenience yields are high, which suggests that higher returns to holding crude oil as a commodity weaken the relative importance of financialization. Finally, a <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mrow> <mml:mi>Stock</mml:mi> <mml:mo>↔</mml:mo> <mml:mi>Price</mml:mi> </mml:mrow> </mml:math> bidirectional causal relation may allow institutional investors to influence the transition from oil and may allow the Federal Reserve Board of Governors to dampen inflation with smaller interest rate hikes. JEL Classification: G13 Contingent evaluation, futures pricing, Q4 Energy, Q41 Demand and Supply, Prices.

  PublisherDOI

• Does electric mobility display racial or income disparities? Quantifying inequality in the distribution of electric vehicle adoption and charging infrastructure in the United States

  Applied Energy · 2024 · 19 citations

  • Business
  • Automotive engineering
  • Economics

  Based on high-resolution spatial and temporal analysis, we quantify and evaluate the equality of plug-in electric vehicle adoption and public charging infrastructure deployment in the United States, examining current and historical trends, as well as racial and income-based disparities. Our results show that the current and historical distribution of conventional vehicle ownership and gas stations shows much more equality, in contrast to electric vehicles and charging infrastructure. With regards to the distribution of electric vehicle adoption, the more electrified vehicle technology is adopted, the more significant income inequality becomes, on a national scale. Over the last several years, almost all states ameliorated income and racial/ethnic inequality for plug-in electric vehicle adoption, but that is not the case for charging infrastructure. The income inequality of the distribution of nationwide charging infrastructure is three times larger than that of gas stations. Individual states, as well as some of the largest urbanized areas, demonstrate a wide range of inequality associated with income and race/ethnicity. There is a need to better understand what drives this significant spatial heterogeneity, as it implies that additional strategies tailored to local and regional contexts may be necessary to achieve more equal distribution of infrastructure as electric vehicles become common beyond early adopters. Improving consistency and coordination of development of charging infrastructure across different states/regions would likely benefit inter-state travelers. • Documents historic inequality of electric vehicle infrastructure. • Illustrates significant spatial variation across different cities and states. • Proposes novel metrics such as Racial Gap Index to characterize inequality. • Develops equity strategies tailored to local and regional contexts. • Evidences a need for more coordinated inter-state charging infrastructure across the country.

  PublisherDOI

• Price Discovery in a Financialized Oil Market

  SSRN Electronic Journal · 2024-01-01

  preprintOpen access
  PublisherDOI

• Distributive energy justice: Who lost power in Texas during the 2021 winter storm?

  Energy Research & Social Science · 2024-01-31 · 10 citations

  articleOpen access1st authorCorresponding

  We use suggestions about how energy justice strengthens environmental justice to generate four testable hypotheses about who lost power in Texas during the 2021 winter storm; (1) disruptions to transmission and distribution (T&D) reduce the need to allocate load shed, (2) utilities allocate more load shed to counties with fewer socially valuable facilities, (3) utilities allocate more load shed to counties with low levels of income or wealth, (4) utilities allocate more load shed to counties with a larger percentage of people who identify as a member of an underrepresented group. To test these hypotheses, we estimate statistical models that separate T&D disruptions from load shed, rates at which utilities interrupt and restore power, and the relation between these rates and customer socioeconomic variables. There is a negative relation between the allocation of load shed and T&D disruptions. There is little evidence that utilities allocate load shed away from socially valuable facilities. Results are mixed regarding the third hypotheses. Results generally validate the fourth hypothesis; several utilities allocate more load shed to counties with larger percentages of residents who identify as a member of an underrepresented group and away from counties with larger percentages of residents who identify as White. Furthermore, we demonstrate how bounding out and investigator bias can influence statistical results. Although we do not present any evidence that utilities intentionally use ethnic make-up to allocate load shed, inequitable outcomes are prima facie evidence for changing the way that load shed is allocated, and we sketch an alternative.

  PublisherDOI

• Social and environmental events disrupt the relation between motor gasoline prices and market fundamentals

  Energy Economics · 2023-08-02 · 2 citations

  article1st authorCorresponding
  PublisherDOI

• Evaluating hedge fund activism: Engine Number 1 and ExxonMobil

  Journal of Climate Finance · 2023-08-14 · 5 citations

  article1st authorCorresponding
  PublisherDOI

• Sub-continental-scale carbon stocks of individual trees in African drylands

  Nature · 2023 · 131 citations

  • Environmental science
  • Forestry
  • Agroforestry

  . We make available a linked database of wood mass, foliage mass, root mass and carbon stock of each tree for scientists, policymakers, dryland-restoration practitioners and farmers, who can use it to estimate farmland tree carbon stocks from tablets or laptops.

  PublisherOA PDFDOI

• Energy price volatility affects decisions to purchase energy using capital: Motor vehicles

  Energy Economics · 2023-08-11 · 12 citations

  article1st authorCorresponding
  PublisherDOI

• A learning by doing multiplier accelerates the transition to photovoltaic cells

  Journal of Climate Finance · 2023-07-26

  articleSenior author
  PublisherDOI

Frequent coauthors

• Ranga B. Myneni

  Boston University

  49 shared

• Liming Zhou

  Harbin Engineering University

  32 shared

• Compton J. Tucker

  Goddard Space Flight Center

  29 shared

• Jari Liski

  18 shared

• Pekka E. Kauppi

  University of Helsinki

  17 shared

• Vladislav A. Alexeyev

  17 shared

• Jing Dong

  Shanxi University

  16 shared

• M. K. Hughes

  16 shared