INET Oxford Doctoral student, Donovan Platt, has won the “The Alan Turing Institute Prize for Best Student Methodology Paper” at the 24th Annual Workshop on Economic Science with Heterogeneous Interacting Agents (WEHIA). The award is presented for "contributions to agent-based model calibration”.
The paper, entitled “A Comparison of Economic Agent-Based Model Calibration Methods”, compares a number of prominent agent-based model calibration techniques through a series of computational experiments and finds that a simple Bayesian estimation procedure is able to outperform several sophisticated frequentist alternatives, which have historically dominated the agent-based model calibration literature.
We congratulate Donovan on such a significant award. Read his full paper here.