Professor of Economics and Statistics

Matthew C. Harding

University of California-Irvine

About me


Matthew C. Harding - Professor of Economics and Statistics


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.

He received his BA in Economics and Philosophy from the University College London, his M.Phil. in Economics from the University of Oxford, and his Ph.D. in Economics from the Massachusetts Institute of Technology. He comes to UCI following previous faculty positions at Duke University and Stanford University.

Experience

Professor of Economics and Statistics

University of California-Irvine (2016 - Now)


Associate Professor

Duke University (2014 - 2016)


Assistant Professor

Stanford University (2007 - 2014)


Education

Massachusetts Institute of Technology

Ph.D. Economics, Robert L. Bishop Fellowship (2002 - 2007)


University of Oxford

M.Phil. Economics (2000 - 2002)


University College London

B.A. Economics and Philosophy, First Class Honours (1997 - 2000)


View Google Scholar Profile    Download CV

Deep Data Lab

The Deep Data Lab is directed by Professor Matthew C. Harding and is part of the Economics Department at the University of California, Irvine. Our group conducts theoretical and applied research at the intersection of econometrics and machine learning.

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Books
  1. "Modern Business Analytics 1st Edition", with Matt Taddy and Leslie Hendrix, 2022.

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Econometrics, Machine Learning:
  1. "Hybrid U-Net: Semantic segmentation of high-resolution satellite images to detect war destruction", with Shima Nabiee, Jonathan Hersh, and Nader Bagherzadeh, Machine Learning with Applications, 2022.
  2. "Managers vs. Machines: Do Algorithms Replicate Human Intuition in Credit Ratings", with G. Vasconcelos, 2022.
  3. "Predicting Mortality from Credit Reports", with G. De Giorgi and G. Vasconcelos, Financial Planning Review, 4(4), 2021.
  4. "Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Quantile Regression Models", with C. Lamarche and H. Pesaran, Journal of Applied Econometrics, 35(3), 2020.
  5. "A Panel Quantile Approach to Attrition Bias in Big Data: Evidence from a Randomized Experiment", with C. Lamarche, Journal of Econometrics, 211(1), 2019.
  6. "Penalized Estimation of a Quantile Count Model for Panel Data", with C. Lamarche, Annals of Economics and Statistics, 134, 2019.
  7. "Estimation of a Factor-Augmented Linear Panel Data Model with Applications Using Student Achievement Data", with C. Lamarche and C. Muris, submitted, 2019.
  8. "Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Quantile Regression Models", with C. Lamarche and H. Pesaran, Journal of Applied Econometrics, 35(3), 2020.
  9. "Deep Autoencoder for Pattern Identification in High-Dimensional Consumer Purchase Data", with A. Parret and Y. Xue, working paper, 2018.
  10. "Improving Convergence in the Bayesian Mixed Logit Choice Model", with J. Hausman and Y. Xue, working paper, 2018.
  11. "Penalized Quantile Regression with Semiparametric Correlated Effects: An Application with Heterogeneous Preferences", with C. Lamarche, Journal of Applied Econometrics, 32(2), 342-358, 2017.
  12. "Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data", with C. Hu, P. Rai, C. Chen and L. Carin, Machine Learning and Knowledge Discovery in Databases, 9285, 2015.
  13. "Finite Sample Bias Corrections for IV Estimation with Weak and Many Instruments", with J. Hausman, and C. Palmer, Advances in Econometrics, 36, 2016.
  14. "Strong Limit of the Extreme Eigenvalues of a Symmetrized Auto-Cross Covariance Matrix", with Wang, C., B. Jin, Z.D. Bai, K. Nair. Annals of Applied Probability, 2015, 25(6), 3624-3683.
  15. "A Bayesian Semi-Parametric Competing Risk Model with Unobserved Heterogeneity", with Burda, M. and J. Hausman, Journal of Applied Econometrics, 2014.
  16. "Estimating the Number of Factors in Large Dimensional Factor Models", workingpaper, 2014.
  17. "Limiting Spectral Distribution of a Symmetrized Auto-Cross Covariance Matrix", with Jin, B., C. Wang, Z.D. Bai, K. Nair. Annals of Applied Probability, 2014, 24(3), 1199-1225.
  18. "Estimating and Testing a Quantile Regression Model with Interactive Effects", with C. Lamarche, Journal of Econometrics, 2013.ilk
  19. "Panel Probit with Flexible Correlated Effects: Quantifying Technology Spillovers in the Presence of Latent Heterogeneity", with Burda, M. Journal of Applied Econometrics, 2013.
  20. "A Poisson Mixture Model of Discrete Choice", with M. Burda and J. Hausman, Journal of Econometrics, 2012.
  21. "Quantile Regression Estimation of Panel Duration Models with Censored Data", with C.Lamarche, Advances in Econometrics, 2012.
  22. "Least Squares Estimation of a Panel Data Model with Multifactor Error Structure and Endogenous Covariates", with C. Lamarche, Economics Letters, 2011.
  23. "Quantile Regression for Time-Series-Cross-Section Data", with Alexander, M. and C. Lamarche, International Journal of Statistics and Management Science, 2011.
  24. "A Quantile Regression Approach for Estimating Panel Data Models Using Instrumental Variables", with C. Lamarche, Economics Letters 104(3), 2009.
  25. "A Bayesian Mixed Logit Probit Model for Multinomial Choice", with M. Burda and J. Hausman. Journal of Econometrics, 147(2), 232-246, 2008.
  26. "Explaining the Single Factor Bias of Arbitrage Pricing Models in Finite Samples", Economics Letters, 99(1), 2008.
  27. "Using a Laplace Approximation to Estimate the Random Coefficients Logit Model by Non- linear Least Squares", with J. Hausman, International Economic Review 48(4), 2007.

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Health
  1. "Emotional Eating in Adults: The role of Socio-Demographics, Lifestyle Behaviors, and Self-Regulation- Findings from a US National Study", with R. Barak, K. Shuval, Q Li, R Oetjen, J. Drope, A. Yaroch, B. Fennis, submitted, 2020.
  2. "Heterogeneity in the Effects of Food Vouchers on Nutrition Among Low-Income Adults: A Quantile Regression Analysis", with J. White, G. Vasoncelos, M. Carroll, C. Gardner, S. Basu, H. Seligman, American Journal of Health Promotion, 2020.
  3. "Evaluating a USDA pilot program to incentivize the purchase of fresh produce among SNAP beneficiaries in supermarkets", with P. Rummo, D. Noriega, A. Parret, O. Hesterman and B. Elbel, Health Affairs, 2019.
  4. "The Sales Impact of Featuring Healthy Foods, Indulgent Foods, or Both: Findings from a Large-Scale Retail Field Study", with G. Fitzsimons and P. Liu, Journal of the Association for Consumer Research, 2018.
  5. "The intergenerational transmission of obesity: The role of time preferences and self-control", with Michal Stoklosa, Kerem Shuval, Jeffrey Drope, Rusty Tchernis, Mark Pachucki, Amy Yaroch, Economics and Human Biology, 28, 92-106, 2018.
  6. "The Effect of Prices on Nutrition: Comparing the Impact of Product- and Nutrient-Specific Taxes", with M. Lovenheim, Journal of Health Economics, 53, 53-71, 2017.
  7. "No Fat, No Sugar, No Salt... No Problem? Prevalence of "Low-Content" Nutrient Claims and Their Associations with the Nutritional Profile of Food and Beverage Purchases in the United States", with L. Tailie, S. Ng, Y. Xue, and E. Busey, Journal of the Academy of Nutrition and Dietetics, 117(9), 1366-13674, 2017.
  8. "Deal or no deal? The prevalence and nutritional quality of price promotions among US food and beverage purchases", with L. Tailie, S. Ng and Y. Xue, Appetite, 117, 365-372, 2017.
  9. "Does Breastfeeding Duration Decrease Childhood Obesity? An Instrumental Variables Analysis of Births in Oregon in 2009", with S. Basu, M. Bartick, E. Rodriguez, J. White, Pediatric Obesity, 12(4), 304-311, 2017.
  10. "Time Preferences and Physical Activity: Insights from Behavioral Economics", with K. Shuval, J. Drope, M. Stoklosa, A. Yaroch and M. Pachucki, Health Behavior and Policy Review 4(1), 53-59, 2017.
  11. "Economic Preferences and Fast Food Consumption in US adults: Insights from Behavioral Economics", with K. Shuval, M. Stoklosa, M. Pachucki, A. Yaroch, J. Drope, Preventive Medicine 93, 204-210, 2016.
  12. "The Effect of Statutory Rape Laws on Teen Birth Rates", with M. Frakes, American Law and Economics Review, 2015.
  13. "Within-Family Obesity Associations: Evaluation of Parent, Child, and Sibling Relationships", Pachucki, M., M. Lovenheim, and M. Harding. American Journal of Preventive Medicine, 47 (4), 2014.
  14. "The Heterogeneous Geographic and Socioeconomic Incidence of Cigarette Taxes: Evidence from Nielsen HomeScan Data", with E. Leibtag and M. Lovenheim, American Economic Journal: Economic Policy, 2012.
  15. "Quantifying the Impact of Economic Crises on Infant Mortality in Advanced Economies", with M. Alexander and C. Lamarche, Applied Economics, 2010.
  16. "The Deterrent Effect of Expansions in Death-Penalty Eligibility Criteria", with M. Frakes, American Law and Economics Review, 2009.

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Environment and Energy:
  1. "Economic Benefits and Environmental Costs of Time of Use Pricing", with K. Kettler and C. Lamarche, working paper, 2020.
  2. "Does Absolution Promote Sin? A Conservationist's Dilemma", with D. Rapson, Environmental and Resource Economics, 2019.
  3. "Penalized Forecasting in Panel Data Models: Predicting Household Electricity Demand from Smart Meter Data", with C. Lamarche and H. Pesaran, working paper, 2018.
  4. "Household Response to Time-Varying Electricity Pricing", with S. Sexton, Annual Review of Resource Economics, 2017.
  5. "Empowering Consumers through Data and Smart Technology: Experimental Evidence on the Consequences of Time-of-Use Electricity Pricing Policies", with C. Lamarche, Journal of Policy Analysis and Management, 35(4), 906-931, 2016.
  6. "Goal Setting and Energy Conservation", with A. Hsiaw, Journal of Economic Behavior and Organization, 2014.
  7. "Environmental Justice: Evidence from Superfund Cleanup Durations", with M. Burda, Journal of Economic Behavior and Organization, 2014.
  8. "Measurement & Verification for Behavioral Programs: Evaluating Programs That Have Gone Full-Scale", EPRI, Palo Alto, CA: 3002001269, 2014.
  9. "Split Incentives in Residential Energy Consumption", with K. Gillingham and D. Rapson, Energy Journal, 33(2): 37-62, 2012.

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Other works:
  1. "Big Data in Economics", with J. Hersh, IZA World of Labor, 2018.
  2. "Good Data Public Policies", in The Future of Data-Driven Innovation, US Chamber of Commerce, 2014.
  3. "Enforcing Regulation: The Impact of Violating Drinking Water Standards on Infant Health at Birth in the US", SIEPR Stanford University, 2013.
  4. "Agreement beyond Polarization: Spectral Network Analysis of Congressional Roll Call Votes", working paper, 2008.
  5. "Endogenous and Schumpeterian Growth (Chapter 14)", Carlin, W., D. Soskice, and M. Harding in Macroeconomics: Imperfections, Institutions and Policies, OUP, 2006.
  6. "Exogenous Growth Theory (Chapter 13)", Carlin, W., D. Soskice, and M. Harding in Macroeconomics: Imperfections, Institutions and Policies, OUP, 2006.

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News

Research

Hybrid U-Net: Semantic segmentation of high-resolution satellite images to detect war destruction

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

Data Science Textbook

New data-science textbook explains the "why", rather than the "what" of decision-making.

Talk

Big Problems? Big Data.

Duke University

Contact me