Multivariate statistical sensitivity analysis of a computer model for pharmaceutical industry market and innovation dynamics

Statistical sensitivity analysis is a useful technique to analyze multivariate stochastic computer model in order to better understand the cause and effect relationships between input parameters and output observations. This paper is based on a pre-existent formal evolutionary economic model that simulates the main aspects of the market and the innovation processes that take place inside the pharmaceutical industry. It belongs to the family of "History-Friendly" models. Our purpose is to reveal the critical input parameters concerning R&D costs, research opportunities, regulatory regime, demand and firm's features in the mechanisms of innovation and market dynamics through the use of multivariate statistical sensitivity analysis. This preliminary work represents a first step in the introduction of a complete analysis with a mixed linear model.