Agent-based microsimulation models of socioeconomic processes require an initial synthetic population derived from census data. This thesis builds upon the Iterative Proportional Fitting (IPF) synthesis procedure, which has well-understood statistical properties and close links with log-linear models. Typical applications of IPF are limited in the number of attributes that can be synthesized per agent. A new method is introduced, implementing IPF with a sparse list-based data structure that allows many more attributes per agent. Additionally, a new approach is used to synthesize the relationships between agents, allowing the formation of household and family agents in addition to individual person agents. Using these methods, a complete population of persons, families, households and dwellings was synthesized for the Greater Toronto Area and Hamilton.