Daniel is a PhD student in the McMaster University School of Computational Science and Engineering, studying under the supervision of Dr. Matheus Grasselli, Professor and Deputy Provost at McMaster University. His research focuses on uncertainty and sensitivity analysis of macroeconomic and climate-economic models, and attempts to determine the economic parameters most responsible for convergence to various economic steady-states through stability analysis, statistical analysis, and machine learning techniques.
Furthermore, he has worked on extensions to the base Goodwin-Keen model, with most of his recent work centered on adding fiscal and monetary policy components to the original framework. He aims to study a series of “green” fiscal and monetary policy measures, with the intention of investigating the effects of climate change and decarbonization on the stability of economic systems.
At Georgetown, Daniel is a member of the team dedicated to building a comprehensive climate-economic model for South Africa. He analyzes data to estimate key economic parameters, and will explore the stability and sensitivity of the model using statistical and machine learning methods.
Keywords: Macroeconomic modelling, Stock-Flow Consistent (SFC) models, dynamical systems, stability analysis, Jacobian analysis, uncertainty analysis, parameter sensitivity, machine learning
Degrees: M.Sc. in Mathematics, McMaster University; (Honours) B.Sc. in Mathematics and Statistics, McMaster University