About

Brian Wright is a Distinguished Professor of the Graduate School in the Department of Agricultural and Resource Economics at the University of California, Berkeley. His research interests include the economics of markets for storable commodities, market stabilization, agricultural policy, industrial organization, public finance, invention incentives, intellectual property rights, the economics of research and development, and the economics of conservation and innovation of genetic resources. Wright's background includes a Bachelor of Agricultural Economics with First Class honors from the University of New England in Australia, and an A.M. and Ph.D. in Economics from Harvard University, where he was awarded a Frank Knox Fellowship. He has held faculty positions at Yale University and is a Fellow of the American Agricultural Economics Association. His work encompasses extensive publication in leading economics journals, as well as contributions to books and articles in prominent scientific outlets such as Nature Biotechnology. His research is characterized by a focus on the intersection of agricultural economics, innovation, and resource conservation.

Research topics

• Economics
• Business
• Geology
• Computer science
• Econometrics

Selected publications

• Transitional dynamics of groundwater regulation

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Enhancing Solar Farm Performance Monitoring Using Attention-Based LSTM Models and Satellite Weather Data

  2025-06-08

  article

  Accurate performance monitoring of utility-scale photovoltaic plants is challenging without on-site weather data. Such data is essential for determining the weather-corrected performance ratio (WCPR), a key parameter in assessing the plants' operational status. However, installing and maintaining onsite weather stations is expensive. Additionally, these stations are prone to faulty sensors and communication errors, which limit data availability.This study utilises satellite-derived weather data and machine learning models to estimate weather parameters. The quality of the models is evaluated by comparing the WCPR calculated using on-site data and the estimated data. A minor error of only 2.2% demonstrates the significant potential of this approach to reduce costs and improve the availability of weather data for the operation and maintenance of utility-scale photovoltaic plants.

  PublisherDOI

• A Conversation on Fundamental Data Literacy Concepts for Undergraduate Education

  Harvard Data Science Review · 2025-05-01 · 1 citations

  preprintOpen accessSenior author

  As the demand for data literacy grows, integrating foundational data literacy skills into undergraduate education becomes increasingly essential. This panel presents six core themes for cultivating data literacy among undergraduate students, addressing its interdisciplinary nature. Drawing upon the collective expertise of the group, literature research, case studies, and interviews, the panel explores the need for data literacy across various disciplines and the challenges of integrating it into higher education curricula. The proposed fundamental concepts include understanding data’s role in daily life, distinguishing between inference and prediction, recognizing the potential for misleading data, exploring ethical considerations, and honing communication and storytelling skills with data. Case studies illustrate diverse approaches to implementing data literacy education at the undergraduate level. Despite these efforts, challenges remain in standardizing data literacy education and scaling initiatives across institutions. The panel emphasizes the importance of collaborative efforts among faculty and increased investment in data literacy initiatives to graduate a data-literate population.

  PublisherOA PDFDOI

• Enhancing Search and Rescue: A Data-Driven Approach to Abduction Case Analysis and Predictive Modeling

  2025-05-02

  articleSenior author

  Abductions are a persistent and dangerous issue around the world, forcing search and rescue (SAR) teams to make rapid decisions to effectively allocate limited resources. The goal of this project is to improve SAR operations by identifying the most probable recovery locations and critical case characteristics. This project was completed in collaboration with dbS Productions LLC, who provides SAR teams with research, publications, software, training, and maintains the International Search and Rescue Incident Database, a key resource in lost person behavior research. The project builds on this foundation by developing statistical models to assist SAR teams in identifying high-priority search areas and predicting key case outcomes. The methodology consists of several key steps, from data cleaning, synthetic data generation, ring model generation, and application of Bayesian techniques.Our results indicate that Age and Homicide Status are statistically significant predictors in determining an abducted person’s distance from the Initial Planning Point. Additionally, our synthetic data maintained similar distributions to the original data, addressed class imbalance, and proved to be robust when tested in an analytical setting. We created and tested a number of models that built upon existing SAR models and achieved better results across the board when testing with the MapScore metric. Our Bayesian model demonstrated the best performance, achieving a MapScore of 0.701.

  PublisherDOI

• Protecting Intermediate Innovations When Ideas Are Scarce: Patents or Secrecy?

  Journal of Economics & Management Strategy · 2025-07-22

  articleSenior author

  ABSTRACT Patenting an intermediate research innovation can lead to competition for the development of a final commercial innovation and potentially induce wasteful duplicative R&D efforts. This study examines the effects of different protection strategies and patent life on the incentives to protect an intermediate innovation by considering a two‐stage sequential innovation model. In this model, the success of a patentable final innovation depends on information about prior intermediate innovations and on complementary inspiration received by innovators. Protecting an intermediate innovation through secrecy can be socially superior if the final innovation involves a high cost and the idea essential to its implementation is common. Acquisition of specialized assets under patenting may increase duplication of resources, and secrecy can act as a social control to limit the entry by many firms. If the idea for the final innovation is scarce, on the other hand, patenting can be optimal for both the innovator of an intermediate innovation and society, and the innovator's incentive is well aligned with social welfare. A broad patent scope can facilitate the adjustment of patent life to align private incentives with the social optimum when the idea for the final innovation is scarce.

  PublisherDOI

• Distinguishing Hares and Tortoises in the Field: Inventor Prediction of Patent Value Flows

  SSRN Electronic Journal · 2024-01-01 · 1 citations

  preprintOpen accessSenior author
  PublisherDOI

• DEReliction: A Cybersecurity Vulnerability Assessment Methodology for Distributed Energy Resources

  2024-10-01 · 1 citations

  reportOpen accessSenior author

  With the increasing integration of Distributed Energy Resources (DER) into the electric grid, maintaining grid reliability and resilience requires that these devices remain secure.This paper discusses a cybersecurity vulnerability assessment methodology that incorporates best practices from Sandia National Laboratories, SANS Institute, OWASP Foundation, and other web and Internet of Things (IoT) penetration testing ("pen testing") programs, courses, and frameworks for assessing the security posture of devices.The methodology involves five sequential steps: (1) Collect Public Information, (2) Extract Hardware Details, (3) Inventory Software Components, (4) Identify Vulnerabilities, and (5) Test Vulnerabilities.Each step uncovers potential weaknesses in both hardware and software components of DER devices, considering adversary tactics, techniques, and procedures (TTPs), and potential attack vectors along the way.The results from the execution of this method on multiple residential-and small commercial-scale photovoltaic (PV) inverters reveled hardware and software vulnerabilities, which highlight the benefit of taking a methodical approach to discover vulnerabilities.While the specific vulnerability details are not shared here, a generalized overview of findings underscore the importance of robust security assessments for DER devices.Adoption of an assessment framework of this kind will identify and mitigate cybersecurity threats and bolster the resilience of DER-integrated electric grids.

  PublisherDOI

• Dual anti-HER2/EGFR inhibition synergistically increases therapeutic effects and alters tumor oxygenation in HNSCC

  Scientific Reports · 2024-02-14 · 12 citations

  articleOpen access

  Abstract Epidermal growth factor receptor (EGFR), human epidermal growth factor receptor 2 (HER2), and hypoxia are associated with radioresistance. The goal of this study is to study the synergy of anti-HER2, trastuzumab, and anti-EGFR, cetuximab, and characterize the tumor microenvironment components that may lead to increased radiation sensitivity with dual anti-HER2/EGFR therapy in head and neck squamous cell carcinoma (HNSCC). Positron emission tomography (PET) imaging ([ 89 Zr]-panitumumab and [ 89 Zr]-pertuzumab) was used to characterize EGFR and HER2 in HNSCC cell line tumors. HNSCC cells were treated with trastuzumab, cetuximab, or combination followed by radiation to assess for viability and radiosensitivity (colony forming assay, immunofluorescence, and flow cytometry). In vivo, [ 18 F]-FMISO-PET imaging was used to quantify changes in oxygenation during treatment. Bliss Test of Synergy was used to identify combination treatment synergy. Quantifying EGFR and HER2 receptor expression revealed a 50% increase in heterogeneity of HER2 relative to EGFR. In vitro, dual trastuzumab-cetuximab therapy shows significant decreases in DNA damage response and increased response to radiation therapy (p < 0.05). In vivo, tumors treated with dual anti-HER2/EGFR demonstrated decreased tumor hypoxia, when compared to single agent therapies. Dual trastuzumab-cetuximab demonstrates synergy and can affect tumor oxygenation in HNSCC. Combination trastuzumab-cetuximab modulates the tumor microenvironment through reductions in tumor hypoxia and induces sustained treatment synergy.

  PublisherOA PDFDOI

• Conforming tax avoidance and earnings persistence

  Pacific Accounting Review · 2024-12-12 · 2 citations

  article

  Purpose This study aims to test the effect of conforming tax avoidance on earnings persistence. Design/methodology/approach The authors use multiple linear regression incorporating firm and year-fixed effects to examine the association between conforming tax avoidance and earnings persistence. Additionally, the authors explore the moderating effect of conforming tax avoidance on the association between current earnings and future (one-year) operating cash flow (OCF). To guarantee the strength and reliability of the results, the authors perform several additional tests. Findings The empirical findings reveal a statistically significantly negative association between conforming tax avoidance and earnings persistence. Additionally, the authors observe that conforming tax avoidance significantly and negatively moderates the relationship between current earnings and future OCF. Furthermore, the principal regression outcomes exhibit resilience in a range of robustness checks. Originality/value This research contributes to the accounting literature by offering a novel perspective on understanding one of the potential reasons behind firms exhibiting low earnings quality or persistence. Specifically, the authors attribute this phenomenon to the downward impact of conforming tax management. Furthermore, the results propose that the tax authority should be vigilant toward companies exhibiting low earnings persistence, particularly quasi-private firms and those with low financial constraints, as they may have implemented or be motivated to engage in conforming tax strategies that preceded the observed reduction in earnings persistence.

  PublisherDOI

• Conflicting Goals on the Road to a Sustainable Groundwater Regime

  SSRN Electronic Journal · 2024-01-01 · 1 citations

  preprintOpen access
  PublisherDOI

Recent grants

• Collaborative Research: The Impacts of University Research and Funding Sources in Chemical Sciences: Publishing, Patenting, Commercialization

  NSF · $431k · 2011–2015

Frequent coauthors

• Jeffrey C. Williams

  39 shared

• Philip G. Pardey

  36 shared

• Bonwoo Koo

  National Institute of Agricultural Science and Technology

  29 shared

• Eugenio Bobenrieth

  Pontificia Universidad Católica de Chile

  27 shared

• Wiley J. Youngs

  University of Akron

  19 shared

• Juan Bobenrieth

  University of Bío-Bío

  19 shared

• Matthew J. Panzner

  University of Akron

  18 shared

• G.W. Timco

  15 shared

Education

• AM, PhD, Economics

  Harvard University

  1975

• Bachelor of Agricultural Economics, First Class Honors, Agricultural Economics

  University of New England

  1969

Awards & honors

• Frank Knox Fellowship