Population census estimation for Spatial Microsimulation

Problem and motivation

Data privacy policies protect inhabitants' sensitive information and make population census data difficult to use in research activities. Especially, privacy policies make data partly inaccessible at small spatial units such as neighborhoods blocks with low-population density. Estimations of inaccessible data not only increase the accuracy of qualitative research but also facilitates applying methods at low-density places that otherwise become impractical to study.

Spatial microsimulation (SMS) refers to "the creation, analysis, and modelling of individual-level data allocated to geographic zones" (Lovelace, 2018). Estimates at small spatial units are required for SMS to increase the certainty of behavioral dynamics in complex phenomena as security, pollution, or health at low-density localities.

Objective

Develop a method to estimate inaccessible population census data to enable more complex applications such as SMS.