Title: Stochastic Dynamic Integrated Climate-Economy Models

Abstract: The classical dynamic integrated climate-economy (DICE) model has become the iconic typical reference point for the joint modelling of economic and climate systems, where all model state variables evolve over time deterministically. We reformulate and solve the DICE model as an optimal control dynamic programming problem with six state variables (related to the carbon concentration, temperature, and economic capital) evolving overtime deterministically and affected by two controls (carbon emission mitigation rate and consumption). We then extend the model by adding stochastic shock variables to the economy and temperature, and solve the model under several scenarios as an optimal stochastic control problem.

Bio: Pavel Shevchenko is a Professor in the Department of Actuarial Studies and Business Analytics and Co-Director of the Centre for Risk Analytics at Macquarie Business School, Australia. Prior to joining Macquarie University in August 2016, he worked for Australian Government national science agency (CSIRO Australia) during 1999-2016, holding the position of a Senior Principal Research Scientist during 2012-2016. Since 1999, Prof. Shevchenko has worked in the area of risk analytics, leading research and industry commercial projects on: modelling of operational and credit risks; longevity and mortality, retirement products; option pricing; insurance; modelling commodities and foreign exchange; and the development of relevant numerical methods and software. Prof. Shevchenko has published extensively in academic journals, consulted for major financial institutions, and is a frequent presenter at industry and academic conferences. His publication records include one research monograph, two co-authored research monographs, over 80 journal papers, and over 80 technical reports.