Matthew is an Econometrician and Data Scientist who develops techniques at the intersection of machine learning and econometrics to answer Big Data questions related to individual consumption and investment decisions in areas such as health, energy, and consumer finance. He often focuses on the analysis of "Deep Data", large and information-rich data sets derived from many seemingly unrelated sources but linked across individuals to provide novel behavioral insights. He is particularly interested in the role of technology and automation to induce behavior change and help individuals live happier and more sustainable lives. At the same time his research emphasizes solutions for achieving triple-win strategies. These are solutions that not only benefit individual consumers, but are profitable for firms, and have a large positive impact on society at large.
As an Econometrician he is currently exploring the potential of machine learning methods in Economics. He is interested in the estimation of high-dimensional models and the use of deep learning methods to produce interpretable economic insights. He also designs and evaluates large scale field experiments in collaboration with industry leaders to measure the individual and social consequences of individual choices and the extent to which Big Data can be used to improve choices and lead to more accurate and targeted programs and products. His research relies on terabyte sized data sets of individual choices and consumption profiles, to build a comprehensive framework for understanding economic behavior and develop new strategies for achieving triple-win solutions.
Matt's company, EcoMetricx, employs cutting edge AI to manage large scale databases, extract actionable insights from complex customer data, and predict new trends. Their team of experts design unique programs and experiments which maximize revenue and customer satisfaction using economic principles and insights from behavioral science. They build advanced custom causal statistical and machine learning tools to provide quantitative evaluations of customer behavior and forecasts.
Assistant Professor
Stanford University (2007 - 2014)
Associate Professor
Duke University (2014 - 2016)
Professor of Economics and Statistics
University of California-Irvine (2016 - Now)
University College London
B.A. Economics and Philosophy,
First Class Honours (1997 - 2000)
University of Oxford
M.Phil. Economics (2000 - 2002)
Massachusetts Institute of Technology
Ph.D. Economics,
Robert L. Bishop Fellowship (2002 - 2007)
Research
We propose a multi-scale feature fusion approach and design a multi-scale skip-connected Hybrid U-Net for segmenting high-resolution satellite images of Syria to detect building damage of various size.
Book
New data-science textbook explains the "why", rather than the "what" of decision-making.
Interview
UCI School of Social Sciences
Talk
Duke University
Bio
Ana is the Lead Scientist and Founder of Ravena Analytics. Previously, she was a Senior Economist at Amazon, where she used economics and data science to provide insights for key decision-making. Her research leverages open data, econometrics, and data tools to inform economic and social topics, with a special interest in water management and food waste systems.
Ana holds a Ph.D in Economics from Stanford University, where she conducted research in public economics and applied econometrics. She served as a Lecturer at the Economics Department of the University of California, Los Angeles (UCLA).
Links
https://www.linkedin.com/in/ana-gomez-lemmen-meyer/
Papers
▪ Gomez Lemmen Meyer, Ana and Cielo Lutino, Los Angeles County’s SB 1383 Food Recovery Study: An Examination of the Edible Food Recovery Mandate for Tier II businesses
(work in progress)
▪ Gomez Lemmen Meyer, Ana and Stephanie Russo Baca. Water Shortage Sharing in the Lower Rio Chama Watershed: Ecological, Social, and Economic Outcomes (working paper, 2025-01-30)
▪ Gomez Lemmen Meyer, Ana and Stephanie Russo Baca. The Rio Chama Water Shortage Sharing Agreement: Water Curtailment, Watershed Health, and Community Values (working paper, 2025-01-14)
I am currently a Ph.D. student in Economics at the University of California, Irvine. I hold a B.A. in Computer Science and Economics from Occidental College. My primary fields of interest are Econometrics and Industrial Organization, with a particular focus on the intersection of Machine Learning and Economics.
https://github.com/maximianne
www.linkedin.com/in/maximianne-castaneda
Extrapolating Treatment Effects to a Target Population
In the process of researching different methodologies to extrapolate Randomized Controlled Trials (RCTs) results across locations using pooled data, ensuring robust external validity. I am employing econometric and statistical models, including inverse probability of sampling weights, stratification, and calibration weighting, to adjust for selection bias and population differences. These extrapolation methods are evaluated on simulated data with diverse data-generating processes to validate performance before applying to real-world datasets.
Russ is a PhD candidate in economics at UCI broadly interested in public/urban/labor topics, particularly those involving the internet and its infrastructure. His current work explores user responses to abusive online peers and its measurement, as well as quality competition between legacy and fiber-optic broadband internet providers. He has also co-authored papers on public health insurance and youth risky behaviors. Russ holds a B.A. in economics and philosophy from the University of Colorado-Boulder and an M.A. in economics from San Diego State University. Outside of work, he enjoys hiking, fishing, and cooking.
Current/Recent Projects
“Willingness to Play: Online Content Moderation and Abusive Peers” In Progress
“California’s 2020 Medi-Cal Expansion to Young Adults and Coverage among 19-25-Year-Old Noncitizens” (with Brandy J. Lipton) In Progress
"Do Vertical ID Laws Curb Teenage Drinking and Tobacco Use?” (with Joseph J. Sabia) Forthcoming at Contemporary Economic Policy
“High-speed internet access and diffusion of new technologies in non metro areas” (with Kangoh Lee) 2023. Telecommunications Policy 47(9), 102620
