A graphical model approach to simulating economic variables over long horizons

We present an application of statistical graphical models to simulate economic variables for the purpose of risk calculations over long time horizons. We show that this approach is relatively easy to implement, and argue that it is appealing because of the transparent yet flexible means of achieving dimension reduction when many variables must be modelled. Using United Kingdom data as an example, we demonstrate the development of an economic scenario generator that can be used by life insurance companies and pension funds. We compare different algorithms to select a graphical model, based on p-values, AIC, BIC, and deviance. We find them to yield reasonable results and relatively stable structures in our example, suggesting that it would be beneficial for actuaries to include these models in their toolkit.