Big Data and Machine Learning

We utilize high frequency and dimensional data to investigate the valuations toward multiple types of environmental amenities based on machine learning techniques integrated with econometric models. Examples include using individual level transaction data to study the impact of environmental amenities on housing preferences and the impact of temperature fluctuations on human behaviors.


Assistant Professor

Environmental and Natural Resource Economics

Selected Publications

Richardson, M., P. Liu, and M. Eggleton (2022) Valuation of Wetland Restoration: Evidence from the Housing Market in Arkansas. Environmental and Resource Economics.

Weir, M. J., and T.W. Sproul (2019) Identifying drivers of genetically modified seafood demand: Evidence from a choice experiment. Sustainability, 11(14): 3934.

Sproul, T. W., and C.P. Michaud (2017) Heterogeneity in loss aversion: evidence from field elicitations. Agricultural Finance Review.