Professor Rennhoff completed his Ph.D. in Economics at the University of Virginia. His research focuses on competition, demand estimation, and firm strategy, particularly in media-related industries, such as cable television and internet service. His research has been published in respected peer-reviewed journals such as American Economics Journal: Microeconomics, Journal of Economic Behavior and Organization, Journal of Economics & Management Strategy, and Information Economics and Policy. He previously served a four-year term as co-editor of the Journal of Media Economics.

Rennhoff teaches several doctoral-level econometrics courses. These courses cover a wide range of topics from panel regression models to maximum likelihood estimation to time series forecasting. He also teaches a doctoral-level course on machine learning which focuses on ways in which machine learning methods, such as random forests, K-means clustering, and LASSO regression, can be used in social science research.

You can visit his university webpage here.

You can visit his Github webpage here.

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