Singapore’s population data was obtained through the country’s department of statistics website.

Using historical trends, and assuming the current activity prevails, we were able to establish a reasonable expectation for predicting future population values. Our population projections are based on two projection models: The Monte Carlo simulation model and the Autoregression Integrated Moving Average (ARIMA) models.

Singaporean occupational data is limited in granularity from the government. Thus, we have augmented that by utilizing a staffing pattern derived from other sources to build current estimates for the market.

We start with 2-digit occupation data from the government’s labor force survey (LFS), which is a variant of the International Standard Classification of Occupations (ISCO-08) coding system. This was not granular enough to align with Global Occupations, therefore we utilized industry data from administrative sources as a baseline for more detail. A European-based staffing pattern was applied to then expand our occupational labor estimates from 2-digit to 4-digit ISCO.

When creating the occupation supply projections, we took the expected population growth rate from the models mentioned above and applied that same growth rate across the LMI. Once we had the projections, we mapped the International Standard Classification of Occupations (ISCO-08) to Global Occupations.