New techniques for household microsimulation, and their application to Australia

This thesis suggests techniques to help make multi-purpose dynamic microsimulations of households, with fine spatial resolutions, high sampling densities and short simulation cycles. Techniques suggested are

• simulation by sampling with loaded probabilities

• proportional event alignment

• event alignment using random sampling

• immediate matching by probability-weighting

• immediate “best of n” matching.

Sampling with loaded probabilities, alignment using random sampling and best of n matching are successfully tested in the Cumpston model, a household microsimulation model based on a 1% sample from the 2001 Australian census. Individuals, families, households and dwellings are included. Immigration and emigration are separately simulated, together with internal migration between 57 statistical divisions. Transitions between 8 person types are simulated, and between 9 occupations.

The model projects education, employment, earnings and retirement savings for each individual, and dwelling values, rents and housing loans for each household. The onset and development of diseases for each individual are simulated,