Statistical Inference in Micro Simulation Models: Incorporating external information

In practical applications of micro simulation models very little is usually known about the properties of the simulated values. This paper argues that we need to apply the same rigorous standards for inference in micro simulation work as in scientific work generally. If not, then micro simulation models will loose in credibility. The paper first discusses how the structure of the model will determine inference and then follow sections on estimation and validation. Differences between inference in static and dynamic models are noted and then the paper focuses on the estimation of behavioral parameters. There are three themes: calibration viewed as estimation subject to external constraints, piece meal vs. system-wide estimation, and simulation based estimation.