The population forecasts contained on this website have been modelled for the City of Melbourne by Geografia. This page provides details of the forecast methodology, key terms and a record of updates.
Forecasts for the City of Melbourne are calculated using an established statistical method that combines three approaches. These have been developed as three modules merged into a single forecast model. The model provides ranged estimates of the number of people by year of age and gender for each small area in the City. The three statistical methods are:
1. Housing Unit Method
Known and mooted dwelling construction activity is combined with estimates of future dwelling construction rates (by dwelling type and location). These estimates are based on information gleaned from the City's strategic planning exercises, assumptions about economic conditions and discussions with the City of Melbourne staff. Household size and occupancy rates by dwelling type, plus an estimate of the number of persons in non-private dwellings allow us to calculate an 'implied population' for the City.
2. Cohort Component Method
The cohort component method is the mainstay of population modelling. It takes the latest known population estimate by age, gender and location and applies birth rates; death rates; and net migration rates (all by age and gender) to these numbers, in this case to 2037. This method explicitly excludes factors such as the number of dwelling commencements. It draws on historical trends and provides a baseline estimate of population growth. The cohort component and housing unit outputs are integrated to generate a final set of projections.
3. Sequential Household Propensity Method
The outputs from the two preceding modules provide the input to a sequential household propensity method. This allocates individuals to different households based on known patterns in the City. So, for example, a specified percentage of 20 year olds in Carlton are likely to live in lone person households. This method draws on the work of Dr Tom Wilson from the University of Queensland's Centre for Population Research.
When working with population figures, there is always a large degree of uncertainty (e.g. the propensity for people of a certain age to move house, or have children). The model accounts for this by using 'stochastic elements'. These are calculation processes that use a range of estimates for input values, rather than a single digit. Household size for townhouses in East Melbourne may be one such stochastic element. Rather than a single number (e.g. 2.5 people per house), it may be between 2.3 and 2.7 and, moreover, this may change over time. Using these ranges is a case of running a 'Monte Carlo' modelling exercise. The model is run thousands of times and each time the household size value is a number between 2.3 and 2.7 based on the probability distribution of the range. Including, rather than ignoring, uncertainty means that the City of Melbourne forecasts are a more realistic estimate of how the City's population will grow and change.
Average household size
The average number of persons in each occupied private dwelling. It does not include people living in non-private dwellings (e.g. prisons and nursing homes).
Estimated Resident Population (ERP)
The population based on place of usual residence.
The movement of people from one place to another. It includes migration between different parts of the City, as well as to and from the City. Migration rates are strongly influenced by age and generally younger adults are more likely to move, including young families. This is particularly noticeable in the City of Melbourne (and primarily in the CBD), which attracts a relatively high proportion of overseas and domestic in-migrants in the 18-40 year age range. Although the City is attractive to some older residents up to 65, the net movement is generally out of the City centre, either to places such as Carlton and South Yarra, or out of the municipality entirely.
The net increase in a population, that is, births minus deaths. It does not include migration.
The proportion of private dwellings that are currently occupied. By necessity these values are estimates based on prior observation by the Australian Bureau of Statistics and other information sources, including, in this case, the City of Melbourne. It is widely recognised that occupancy rates never reach 100%, as some proportion of dwelling units are undergoing renovations, or going through ownership or rental tenancy change over. Additionally a proportion of dwellings are unoccupied investment properties.
Occupied Private Dwellings
Completed, occupied dwellings (i.e. houses, townhouses, flats and student apartments). It does not include temporarily vacant dwellings or non-private dwellings such as short stay apartments or university colleges of residence.
The log below provides a history of updates to the population projections. Projections are updated regularly to account for newly available data and changing demographic trends. This includes data from the ABS, development approvals data from the City of Melbourne.