My name is Alex Kappes and I'm currently a postdoctoral researcher in partnership with Washington State University, the Gates Foundation, and the World Organization for Animal Health working to empirically evaluate the global burden of animal diseases in developing countries and associated economies.
My research interests include applied statistical learning (econometrics, supervised and unsupervised machine learning, simulation and posterior analysis, and causal inference), One Health and development, Political Instability and Security, Choice Analysis, technology adoption, innovation, and sustainability. Within these areas I work on topics that contribute to the development of statistical modeling techniques when little information exists; to questions surrounding livestock disease effects on production and welfare; to production technology adoption and innovation in response to policy; and to development and markets in impoverished areas.
I am naturally curious about complex systems and have a passion for developing modeling approaches that provide actionable information for questions regarding these systems. My current work focuses on the development of variable selection techniques in a Bayesian environment for ordinal data, as well as expanding inference on treatment effects by allowing for a latent treatment designation in Bayesian regression trees. I also develop modeling techniques that provide information about the relationship between livestock health and production efficiency for the purpose of improving welfare, as well as for evaluating the overall burden of animal diseases. All project scripts can be viewed here.
Please feel free to contact me with any questions, and again, welcome!