The Deep Data Lab is directed by Professor Matthew 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.
The last few years have seen an unprecedented increase in the amount of data available to economists both in academia and the private sector. Researchers can now access massive datasets such as administrative data, consumer transaction data and social media data. Both econometrics and applied research benefits enormously from the Big Data revolution, which is characterized by the Volume, Velocity, and Variety of the data. Traditional econometric tools are often ill-equipped to handle the rigors of modeling on such a large scale. The vastness of the data also presents new opportunities to identify economic models using flexible and nonparametric tools which would not have been possible on smaller datasets. Our lab conducts cutting edge research in high-dimensional modeling, quantile regression, and deep learning.
While new research opportunities are due to the scale or increased frequency of data, we believe that the ultimate Value of Big Data lies in its depth, which is defined by the extent to which seemingly unrelated datasets can be combined and linked to provide new insights. For example, consumer behavior can be better modeled or predicted if we link purchase histories to detailed demographics, medical histories, location information, programs households participate in or policies which affect them. Technology plays a key role in enabling consumers to make informed choices and automate their response to prices whether through smart meters or smartphones. Thus, our lab also conducts applied research using deep data in areas such as consumer choice, public economics, health economics, energy and environmental economics.
We engage in partnerships with leading companies, foundations or agencies to solve challenging real world problems. Please feel free to reach out to us to discuss opportunities for collaboration.