Andrew Howe is a research fellow in KAPSARC’s Policy and Decision Science program. He is a seasoned quantitative modeler with expertise in the application of mathematics, statistics, and computer science to diverse practical problems in a variety of industries. Andrew’s experience in the energy sector spans both electric utilities and upstream oil and gas, and he is a certified energy risk professional. His current research interests at KAPSARC center around quantitative modeling of collective decision-making processes and big data machine learning for the utilities sector. In addition, Andrew is an active researcher in machine learning, having developed novel algorithms for topics including clustering, classification, simulation, and optimization.
The traditional economic approach to policy analysis is to utilize tools and methods developed within the field of economics and study the economic impact of one or more policies solely from an economic perspective. As a consequence, the “policies” are usually formulated and evaluated only by an assessment of the pure economic optimality of expected outcomes. Moreover, economic models typically treat policy choices as exogenously specified. Once policies are selected according to some exogenous process, then scenario analysis can be performed to simulate the economic impact of those policies.31st May 2017