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National Cities Performance Framework
Data dictionary
Total population Active transport
Annual population growth rate Peak travel delay
Indigenous population Road safety
Population density Knowledge services
Dwelling type Broadband connections
Average household size New businesses
Housing tenure Patent applications
Life expectancy Adult obesity
Share in bottom household income quintile Perceived safety
Languages other than English spoken at home Access to public open space
Age structure Crisis support
Mean detached dwelling price Suicide rate
Mean unit price Air quality
Sector share of employment Volunteering
Disability rate Greenhouse gas emissions per capita
Median annual household income Office building energy efficiency
Local government fragmentation Access to public transport
Median dwelling price to median income ratio Employment growth
Housing construction costs Unemployment rate
Public and community housing Youth unemployment rate
Homelessness Participation rate
Mortgage stress Year 12 completion
Rent stress Certificate level III, IV or diploma
Building approvals per 100,000 Bachelor degree or higher
Share of jobs accessible within 30 minutes Gross regional product
Number of jobs accessible within 30 minutes Indigenous unemployment rate
Public transport
Page 1 Updated June 2020National Cities Performance Framework Total population Description The number of people who live in a city. Rationale Information regarding population size can help users to understand likely pressures on housing, public infrastructure and services. Limitations None Data Source Australian Bureau of Statistics - Regional Population Growth, Australia, 2018-19 (Cat no. 3218.0) Date Published 25 March 2020 Data Source Link http://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/3218.0 Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016) Method Estimates are taken directly from the ABS. Unit Persons Revision Schedule Annual Page 2 Updated June 2020
National Cities Performance Framework Annual population growth rate Description The annual population growth rate of a city. Rationale Information regarding population growth can help users to understand likely pressures on housing, public infrastructure and services. Limitations None Data Source Australian Bureau of Statistics - Regional Population Growth, Australia, 2018-19 (Cat no. 3218.0) Date Published 25 March 2020 Data Source Link http://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/3218.0 Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016) Method Population growth is calculated as a five year average annual rate. The calculation uses a compound annual growth rate formula. The most recent estimated resident population is divided by the population five years earlier, this is then brought to the power of one over five. The product of this is then multiplied by 100 and then 100 is subtracted. Unit Percentage Revision Schedule Annual Page 3 Updated June 2020
National Cities Performance Framework Indigenous population Description The proportion of a city’s population that identify as Aboriginal or Torres Strait Islander. Rationale Aboriginal and Torres Strait Islander peoples are culturally and linguistically diverse. However, common to Aboriginal and Torres Strait Islander communities is a culture that is different to the non- Indigenous culture. Elements of cultural difference may include, but are not limited to: concept of family structure and community obligation, language, connection to country and continuation of traditional knowledge. This in turn has an effect on the areas of concern that Aboriginal and Torres Strait Islander peoples might see as important to their wellbeing (see ABS Frameworks for Australian Social Statistics, 2015). Limitations This indicator is calculated using Aboriginal and / or Torres Strait Islander population estimates by SA2 and LGA, available from the ABS (Cat. no. 3238.0). SA2s with suppressed estimates have not been accounted for and have been given a value of 0. Data Source Australian Bureau of Statistics – Estimates of Aboriginal and Torres Strait Islander Australians, June 2016 (Cat. no. 3238.0.55.001) Date Published 31 August 2018 Data Source Link https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/3238.0.55.001June%202016?OpenDocument Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016) Method To account for the under enumeration of Aboriginal and Torres Strait Islander Australians in the 2016 Census, this indicator used population estimates from the ABS at the GCCSA, SA2 and LGA level. SUA estimates are derived by aggregating SA2 data to the city level. Unit Percentage Revision Schedule Five yearly Page 4 Updated June 2020
National Cities Performance Framework
Population density
Description
Population-weighted density measures attempt to capture the density at which the average city resident
lives. This measure was calculated as a weighted average of the population density of all of the census
meshblocks within the city. This measure is more representative of the lived experience of a city's
residents than a simple average density calculation (i.e. population divided by the land area of the city).
Rationale
Increasing density enables more people and businesses to access the benefits of being in a city, and can,
for example, help spread the costs associated with building and maintaining infrastructure. However,
increasing density also puts increased stress on the existing built and natural environment and can
detract from a city's liveability.
Limitations
Population-weighted density measures are sensitive to the geographic scale of the underlying population
data. This calculation is based on census meshblocks, which represent the most disaggregated scale at
which population data is available for cities. Census meshblock population counts are only published
for census years.
Data Source
BITRE analysis of:
• Australian Bureau of Statistics - Census of Population and Housing: Mesh Block Counts,
Australia, 2016 (Cat. no. 2074.0)
• Australian Bureau of Statistics - Regional Population Growth, Australia, 2018-19 (Cat. no.
3218.0)
Date Published
4 July 2017 (Cat. no. 2074.0) and 25 March 2020 (Cat. no. 3218.0)
Data Source Link
http://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/3218.0;
http://www.abs.gov.au/ausstats/abs@.nsf/mf/2074.0
Data Source Geography
GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016)
Method
Current year population estimates for each meshblock are derived by multiplying each 2016 census
meshblock population count by an SA2-specific scaling factor. The scaling factor is calculated for each
SA2 as the ratio of the Estimated Resident Population count for the current year to the latest census-
based population count (i.e. the sum across all meshblocks in the SA2). This approach essentially scales
up the census-year meshblock population counts so they align with the most recent available population
counts. Density is then calculated for each meshblock by dividing this scaled population estimate by the
land area of the meshblock. The final step involves weighting these meshblock density estimates using
the scaled meshblock population estimates, and aggregating to the city scale using a standard population
weighted formula.
Unit
Persons per square kilometre
Page 5 Updated June 2020National Cities Performance Framework Revision Schedule Annual Dwelling type Description The share of dwellings in a city that are detached houses, semi-detached houses, apartments or other. Rationale This indicator shows the degree of diversity in a city’s housing stock. Understanding this diversity can provide insights into a city’s population density, the dwelling options available to households, and local infrastructure, service and amenity needs. Limitations None Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016) Method Dwelling Structure is extracted from Census Tablebuilder at required geographies. Other includes Caravan; Cabin, houseboat; Improvised home, tent, sleepers out; House or flat attached to a shop, office, etc. Not Stated and Not Applicable are excluded from denominator. Unit Percentage Revision Schedule Five yearly Page 6 Updated June 2020
National Cities Performance Framework Average household size Description The average number of people per occupied dwelling in a city. Rationale Trends in household size convey information about consumption and lifestyle preferences, the size of dwellings and housing affordability. Limitations None Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016) Method For GCCSA and SUA based cities, average household sizes are taken directly from ABS Census products. Western Sydney is derived by dividing counts of persons resident in private dwellings by the number of occupied private dwellings. Persons resident in non-private dwellings are excluded from the calculation. Unit Percentage Revision Schedule Five yearly Page 7 Updated June 2020
National Cities Performance Framework Housing tenure Description The share of occupied private residential dwellings in a city that are owned outright by the occupier, owned with a mortgage, rented, or other. Rationale Housing tenure data can help users understand how changes in housing policy or the housing market will affect a city’s residents. Housing tenure has an impact on labour mobility. Owner occupiers are typically less likely to move locations compared with renters. Housing tenure also tends to be correlated with housing density: a larger share of renters live in higher density housing, and a larger share of owner-occupiers live in detached houses. Limitations None Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016) Method Tenure Type is extracted from Census Tablebuilder at required geographies. Other includes Being purchased under a shared equity scheme; Being occupied rent-free; Being occupied under a life tenure scheme; Other tenure type. Not Stated and Not Applicable are excluded from denominator. Unit Percentage Revision Schedule Five yearly Page 8 Updated June 2020
National Cities Performance Framework
Life expectancy
Description
The number of years a person born today is expected to live, assuming current age-specific death rates
are experienced throughout their lifetime.
Rationale
Life expectancy is a proxy for the health of a city’s population.
Limitations
Life expectancy for the non-capital cities is modelled (see method for details). SA4s where the
constituent SA2s have variable standardised death rates can produce city level life expectancy estimates
which differ from the SA4 life expectancy estimate.
Data Source
BITRE analysis of:
• Australian Bureau of Statistics - Life Tables, States, Territories and Australia (Cat. no.
3302.0.55.001) - 2016-2018 and
• Australian Bureau of Statistics - Deaths, Australia (Cat. no. 3302.0) - 2018
Date Published
30 October 2019 and 26 September 2019
Data Source Link
http://search.abs.gov.au/s/search.html?query=3302.0&collection=abs&form=simple&profile = default
Data Source Geography
GCCSA (Capital cities), SA4 and SA2 (all other cities) (ASGS 2016)
Method
Capital cities have their estimates taken directly from the ABS publication. Life expectancy is estimated
for non-capital cities using a model based on estimated age standardised death rates (ASDRs). The
model uses the relationship between SA4 level life expectancy and ASDRs to estimate the life
expectancy of SUAs and Western Sydney. ASDRs for the city definitions are calculated by using
population weights to combine the SA2s that make up the city definitions. As non-capital cities are
geographic subsets of SA4s, modelled estimates are calculated for the city and the balance of the SA4.
These two estimates are then benchmarked to the original SA4 life expectancy estimate to ensure they
align.
Unit
Years
Revision Schedule
Annual
Page 9 Updated June 2020National Cities Performance Framework Share in bottom household income quintile Description The share of a city’s households in the bottom 20 per cent of the national household income distribution. A figure below 20 per cent indicates that a city has proportionally fewer lower-income households than the national average. Rationale This indicator can help users understand the extent of socio-economic disadvantage in a city. Limitations None Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016) Method Total Household Income (weekly) is extracted from Census Tablebuilder at required geographies. Incomes below and including $33,799 annually are classified as the lowest quintile. Negative and No Income are included in numerator. Partial and Not Stated are excluded from denominator. Unit Percentage Revision Schedule Five yearly Page 10 Updated June 2020
National Cities Performance Framework Languages other than English spoken at home Description The proportion of a city's residents who speak a language other than English at home. Rationale This indicator is a measure of a city's linguistic diversity. Understanding linguistic and, by association, cultural diversity can help target policies that support community integration and cohesion. Limitations This indicator does not measure English language proficiency. A relatively high proportion of residents speaking languages other than English at home does not necessarily imply lower levels of proficiency in English. Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016) Method Persons who speak a language other than English at home are extracted from Census Tablebuilder at required geographies. Not Stated individuals are excluded from the calculation. Unit Percentage Revision Schedule Five yearly Page 11 Updated June 2020
National Cities Performance Framework Age structure Description The proportion of people aged 0 to 14, 15 to 64 and 65 and over. Rationale The age structure of the population can give an indication of which services might be in high demand in a city. For example, cities with a relatively large number of older people are likely to have high demand for aged-care services and retirement homes. Cities with a relatively large number of working-age people may have higher demand for childcare services and schools. Limitations None Data Source Australian Bureau of Statistics - Population by Age and Sex, Regions of Australia, 2017 (Cat no. 3235.0) Date Published 29-Aug-19 Data Source Link http://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/3235.0 Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SA2s to create SUAs (other cities) (ASGS 2016) Method Population age structure is calculated from five year age group estimated resident population. LGAs and SA2s are combined to create city geographies where required. Unit Percentage Revision Schedule Annual Page 12 Updated June 2020
National Cities Performance Framework Mean detached dwelling price Description Mean sold detached dwelling value over the previous 12 months. Rationale This indicator, together with ‘Household income’, can help users understand how affordable housing is in a city (see ‘Dwelling price to income ratio’). Limitations Differences in dwelling prices across cities are driven by a range of factors. These include income levels, amenity, and the flexibility of city planning and zoning systems in responding to changes in housing demand. Data Source CoreLogic (custom data) 2019 Date Published Custom data Data Source Link https://www.corelogic.com.au/ Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016) Method Total value of detached dwellings sales for the previous 12 months is divided by the total number of sales over the same 12 months. Unit $ Revision Schedule Annual Page 13 Updated June 2020
National Cities Performance Framework Mean unit price Description Mean sold unit value over the previous 12 months. Rationale This indicator, together with ‘Household income’, can help users understand how affordable housing is in a city (see ‘Dwelling price to income ratio’). Limitations Differences in dwelling prices across cities are driven by a range of factors. These include income levels, amenity, and the flexibility of city planning and zoning systems in responding to changes in housing demand. Data Source CoreLogic (custom data) 2019 Date Published Custom data Data Source Link https://www.corelogic.com.au/ Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016) Method Total value of unit sales for the previous 12 months is divided by the total number of sales over the same 12 months. Unit $ Revision Schedule Annual Page 14 Updated June 2020
National Cities Performance Framework
Sector share of employment
Description
The proportion of employed persons in a city that work in: goods producing industries, market services
industries and non-market services industries. Goods producing industries include Agriculture, Forestry
and Fishing; Mining; Manufacturing; Utilities; and Construction. Non-market services industries
include Public Administration and Safety; Education and Training; and Health Care and Social
Assistance. Market services comprise all other industries as defined by the ABS.
Rationale
Cities can have different industry specialisations and employment mixes, depending on factors such as
local resource endowments, history and policy choices. As such, cities can have different policy needs
and are affected by economic developments in different ways.
Limitations
Estimates for this indicator are based on the ABS Labour Force Survey and can fluctuate. In particular,
estimates for small cities can be highly variable. Please consider this when interpreting this indicator.
Data Source
BITRE analysis of:
• Australian Bureau of Statistics - Labour Force, Australia, Detailed, Quarterly, Aug 2019 (Cat
no. 6291.0.55.003) and
• Australian Bureau of Statistics - Census of Population and Housing 2016
Date Published
26 September 2019 (Labour Force) and October 2017 (Census)
Data Source Link
https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/6291.0.55.001Sep%202019?OpenDocument
https://auth.censusdata.abs.gov.au/webapi/jsf/login.xhtml
Data Source Geography
GCCSA (Capital cities) and SA4 (Western Sydney and other cities) (ASGS 2016)
Method
GCCSA (Capital cities) results are obtained from the Labour Force Survey. SUA and Western Sydney
are estimated based on SA4 data from the Labour Force Survey. Census data at the SUA and SA2 levels
is used to estimate what proportion of the relevant SA4s results should be apportioned to the SUA
estimates.
Unit
Percentage
Revision Schedule
Annual
Page 15 Updated June 2020National Cities Performance Framework Disability rate Description The proportion of a city’s population with a profound or severe disability. A person has disability if they report they have a limitation, restriction or impairment, which has lasted, or is likely to last, for at least six months and restricts everyday activities. The severity of disability is defined according to the degree of assistance or supervision required in self-care, mobility, and communication. Rationale Disability can impact on a person’s capacity to participate in the economy and engage in the community. People with disability are also at a higher risk of becoming socially disadvantaged. This indicator can provide broad insights into service needs for people with disability in a city. Limitations This indicator provides no information on the type, cause or prevalence of disabilities people have. This indicator does not measure broader concepts of disability such as those found in the Disability Discrimination Act 1992. Data Source PHIDU - Social Health Atlas of Australia Date Published October 2018 Data Source Link http://phidu.torrens.edu.au/social-health-atlases/data Data Source Geography SA3 (ASGS 2016) Method SA3 level estimates are aggregated to the required city level using a person weighted concordance. Unit Percentage Revision Schedule Irregular updates Page 16 Updated June 2020
National Cities Performance Framework Median annual household income Description Median annual household income. A household’s income represents the combined income of all household members aged 15 years and older. Rationale Household income is a broad indicator of standard of living. It can also be compared against cost of living factors, such as housing prices, in different cities to obtain benchmarks for assessing affordability. Limitations This measure does not equivalise income across different household structures and is the gross income of a household regardless of structure. Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGAs (Western Sydney) and SUA (other cities) (ASGS 2016) Method Medians are calculated from Census income brackets. Western Sydney is calculated by combining LGA medians using a dwelling weighting method. Calculation includes Negative Income and Nil Income, but excludes Partial Income Stated, All Incomes Not Stated and Not Applicable. Unit Percentage Revision Schedule Five yearly Page 17 Updated June 2020
National Cities Performance Framework Local government fragmentation Description The number of Local Governments in a city. Rationale Fragmented governance occurs when a city is governed by more than one local government authority. This is common in many of Australia’s largest cities. In some circumstances, fragmentation can hinder a city’s economic performance. While smaller area governments tend to be more responsive to local citizens, larger area governments are better placed to deal with complex city-wide coordination problems and enjoy economies of scale in public administration. Limitations Evidence of the relationship between fragmentation and economic growth is not conclusive and may vary with local conditions. This indicator is less relevant for cities that have one local government area, or none at all. Cities with one local government area include: Bendigo, Cairns, Mackay, Toowoomba and Townsville. Canberra has no local government areas. Data Source ABS - Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures, (Cat. no. 1270.0) Date Published 31-Jul-19 Data Source Link https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/1270.0.55.003July%202019?OpenDocument Data Source Geography Local Government Area (2019) Method The number of LGAs in a city are calculated using ABS standard geography classifications. Unit Local Governments Revision Schedule Annual Page 18 Updated June 2020
National Cities Performance Framework Median dwelling price to median income ratio Description The ratio of the median dwelling price to median annual household income. Rationale Home ownership is an aspiration for many Australians. Purchasing a home is also the largest single expenditure for a typical household. The dwelling price to income ratio is a key measure of housing affordability. Low levels of housing affordability have negative implications for a city’s economic performance by reducing labour market efficiency, undermining social cohesion and exacerbating wealth inequality (Australian Housing and Urban Research Institute). Limitations The median dwelling price does not make housing quality adjustments and does not adjust for outlier house sales. Western Sydney was excluded as neither median dwelling price or household income was available at the specified geography. Data Source Median dwelling prices - Australian Property Monitors (custom data) 2019 Median household income - ANU household income model (custom data) 2019 Date Published Custom data Data Source Link https://www.apm.com.au/ Data Source Geography GCCSA (Capital cities) and SUA (other cities) (ASGS 2016) Method Median dwelling price is divided by the median annual household income. Unit Ratio Revision Schedule Annual Page 19 Updated June 2020
National Cities Performance Framework Housing construction costs Description The average cost per square metre of constructing a new detached house in a city. This indicator presents average costs for a standardised building type: a full-brick detached house with a tiled roof, built on a flat site. Rationale Construction costs are a large component of housing prices, along with the cost of land. Monitoring construction costs enables a better understanding of the factors contributing to house price levels in a city. Limitations Construction costs vary depending on the type of building, the materials used to build it, the workers employed and the cost of complying with regulations. This indicator does not disaggregate contributions to construction costs from materials, labour, taxes, fees and charges, and profit margins. Data for Western Sydney is not available. Data Source Rawlinsons Australian Construction Handbook 2019, Edition 37 Date Published Custom data Data Source Link https://www.rawlhouse.com.au/ Data Source Geography Rawlinsons-defined city geographies Method This indicator uses the Rawlinsons project house series. Unit $ per square metre Revision Schedule Annual Page 20 Updated June 2020
National Cities Performance Framework Public and community housing Description The number of public and community housing dwellings as a share of the city's total dwelling stock. Public and community housing refers to dwellings rented from a state or territory housing authority, a housing co-operative, or a community or church group. Rationale The availability of public and community housing is an important consideration for policies addressing housing affordability issues and socio-economic disadvantage. Limitations Public and community housing may not always be the best solution to addressing housing affordability or socio-economic disadvantage. The appropriate level of public and community housing provision should vary depending on local conditions and levels of socio-economic disadvantage. Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGAs (Western Sydney) and SUA (other cities) (ASGS 2016) Method Tenure and Landlord Type is extracted from Census Tablebuilder at required geographies. Not Stated and Not Applicable are excluded from denominator. Unit Percentage Revision Schedule Five yearly Page 21 Updated June 2020
National Cities Performance Framework Homelessness Description The number of homeless people per 100,000 residents. A person is classified as homeless if they do not have suitable accommodation alternatives and their current living arrangement: • is in a dwelling that is inadequate, or • has no tenure (e.g. squatting), or • has an initial tenure that is short and not extendable, or • does not allow them to have control of, and access to, space for social relations. Rationale This indicator can help users understand the extent of socio-economic disadvantage in a city and inform policy decisions concerning housing and other services for homeless people. Limitations This indicator counts everybody who identifies as homeless and is not reflective of 'rough-sleepers' in a city. Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGAs (Western Sydney) and SUA (other cities) (ASGS 2016) Method Number of homeless for a city is divided by the size of the population and multiplied by 100,000. Unit Persons per 100,000 people Revision Schedule Five yearly Page 22 Updated June 2020
National Cities Performance Framework Mortgage stress Description The proportion of households for which mortgage payments make up 30 per cent or more of household income. This indicator is expressed as a percentage of the total number of households in the city. Rationale Households that spend a large share of their income on mortgage payments have less money to spend on other things. These households are also typically more vulnerable to financial shocks associated with house price falls or interest rate rises, which can increase risks of default or further constrain consumer spending. Having a large number of households in mortgage stress presents broader risks to the local economy. Limitations This indicator does not take into account the size of household income when calculating whether a household is under stress. High income households can afford to spend a high proportion of their income on housing and not affect their ability to afford other essentials. Mortgage stress is calculated using various methodologies by other providers. Please use caution when comparing different measures. Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGAs (Western Sydney) and SUA (other cities) (ASGS 2016) Method Estimates were taken directly from the ABS QuickStats products at the required geography, except in the case of Western Sydney. Western Sydney was calculated by combining estimates from the constituent LGAs. The ABS method of calculation is the number of households where mortgage repayments were 30% or more of an imputed income measure. The number of households are expressed as a proportion of the total number of households in an area (including those households which were renting, and excluding the small proportion of visitor only and other non-classifiable households). The nature of the income imputation means that the reported proportion may significantly overstate the true proportion. Unit Percentage Revision Schedule Five yearly Page 23 Updated June 2020
National Cities Performance Framework Rent stress Description The proportion of households for which rent payments make up 30 per cent or more of household income. This indicator is expressed as a percentage of the total number of households in the city. Rationale Around one in three households rent. Households that cannot afford to pay rent can put pressure on public and community housing. Lack of access to affordable rental housing can exacerbate this problem. Limitations This indicator does not take into account the size of household income when calculating whether a household is under stress. High income households can afford to spend a high proportion of their income on housing and not affect their ability to afford other essentials. Rent stress is calculated using various methodologies by other providers. Please use caution when comparing different measures. Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGAs (Western Sydney) and SUA (other cities) (ASGS 2016) Method Estimates were taken directly from the ABS QuickStats products at the required geography, except in the case of Western Sydney. Western Sydney was calculated by combining estimates from the constituent LGAs. The ABS method of calculation is the number of households where rent payments were 30% or more of an imputed income measure. The number of households are expressed as a proportion of the total number of households in an area (including those households which were not renting, and excluding the small proportion of visitor-only and other non-classifiable households). The nature of the income imputation means that the reported proportion may significantly overstate the true proportion. Unit Percentage Revision Schedule Five yearly Page 24 Updated June 2020
National Cities Performance Framework Building approvals per 100,000 Description The number of new residential dwellings approved for construction per 100,000 persons in the city. Rationale Residential building approvals are a forward indicator of the volume of dwelling investment and the supply of new housing in a city. Expressing dwelling approvals per 100,000 persons helps understand how well housing supply is keeping up with new demand. Limitations There is a lag between the approval of a new dwelling and that dwelling being constructed and entering the housing market. Data Source Australian Bureau of Statistics – Building Approvals, Australia, Nov 2019 (Cat. no. 8731.0) Australian Bureau of Statistics – Regional Population Growth, Australia, 2017-18 (Cat. no. 3218.0) Date Published 8 January 2020 (Building Approvals) and 27 March 2019 (Regional Population Growth) Data Source Link http://www.abs.gov.au/ausstats/abs@.nsf/mf/8731.0 Data Source Geography GCCSA (Capital cities), LGA (Western Sydney) and SUA (other cities) (ASGS 2016) Method The number of new residential dwellings approved for the calendar year is summed. With Estimated Resident Population as at 30 June (divided by 100,000) is the denominator. Unit Dwellings per 100,000 people Revision Schedule Annual Page 25 Updated June 2020
National Cities Performance Framework
Share of jobs accessible within 30 minutes
Description
The share of jobs in a city that can be reached by car in a commute of 30 minutes or less during the
morning peak. This indicator represents a city-wide average - commute times in different parts of a city
are weighted by population size.
Rationale
Better access to jobs makes it simpler to find work or change employers, and can improve the quality of
job matches in a city - one of the determinants of labour productivity. Shorter commute times also give
people more time for leisure outside work.
The share of jobs accessible within 30 minutes is a partial indicator of the efficiency of a city’s transport
infrastructure.
Limitations
The 30 minute job accessibility indicator currently does not adequately estimate traffic dwell time (time
spent idle at traffic lights or intersections). This leads to an over-estimate of total job accessibility,
especially in large cities. The National Cities Performance Framework Dashboard will endeavour to
improve this indicator over time. Please interpret this indicator with caution.
The indicator only includes travel by car and does not provide full information on the effectiveness of a
city's transport network. Jobs outside the city definition are not included in the calculation, even if they
are accessible in 30 minutes (for example jobs in Queanbeyan are excluded from the Canberra
calculation despite being easily accessible). On roads where there is insufficient data for average road
speeds (predominantly suburban roads) the signposted speed is used. The distribution and number of
jobs in the city is sourced from the 2016 ABS Census, which underestimates the total number of jobs
due to Census undercount and question non-response. Data is not available for Western Sydney.
Data Source
BITRE analysis of:
• Australian Bureau of Statistics - Census of Population and Housing 2016
• Australian Bureau of Statistics - Population by Age and Sex, Regions of Australia, 2017 (Cat.
no. 3235.0)
• Here Technologies - NAVMap
Date Published
• Census - 23 October 2017
• Regional Population - 28 Sept 2018
• Here Technologies - Custom data
Data Source Link
• Census
http://ww.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBar
• Regional Population - http://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/3235.0
• Here - https://www.here.com/en
Data Source Geography
SA2 (ASGS 2016) and 2016 Census of Population and Housing Destination Zones
Page 26 Updated June 2020National Cities Performance Framework Method To generate a weighted population centre for individual SA2s, we use working age (15-64) population counts at SA1. This allows us to create centroids in SA2s with non-uniform population distributions and these SA2 centroids are used as origin points to model commuting patterns. 30 minute commutes from individual SA2s are modelled using road network analysis and morning peak average road speeds (provided by Here Technologies). Using this modelled commute, we can assess how many jobs are accessible from each SA2. Individual SA2 job accessibility proportions are then weighted together using working age population estimates. The distribution of jobs within the city definition is estimated using job counts by 2016 Census of Population and Housing Destination Zones. Unit Percentage Revision Schedule Five yearly Number of jobs accessible within 30 minutes Description The number of jobs in a city that can be reached by car in a commute of 30 minutes or less during the morning peak. This indicator represents a city-wide average - commute times in different parts of a city are weighted by population size. Rationale Better access to jobs makes it simpler to find work or change employers, and can improve the quality of job matches in a city - one of the determinants of labour productivity. Shorter commute times also give people more time for leisure outside work. The number of jobs accessible within 30 minutes is a partial indicator of the efficiency of a city’s transport infrastructure. Limitations The 30 minute job accessibility indicator currently does not adequately estimate traffic dwell time (time spent idle at traffic lights or intersections). This leads to an over-estimate of total job accessibility, especially in large cities. The National Cities Performance Framework Dashboard will endeavour to improve this indicator over time. Please interpret this indicator with caution. The indicator only includes travel by car and does not provide full information on the effectiveness of a city's transport network. Jobs outside the city definition are not included in the calculation, even if they are accessible in 30 minutes (for example jobs in Queanbeyan are excluded from the Canberra calculation despite being easily accessible). On roads where there is insufficient data for average road speeds (predominantly suburban roads) the signposted speed is used. The distribution and number of jobs in the city is sourced from the 2016 ABS Census, which underestimates the total number of jobs due to Census undercount and question non-response. Data is not available for Western Sydney. Page 27 Updated June 2020
National Cities Performance Framework
Data Source
BITRE analysis of:
• Australian Bureau of Statistics - Census of Population and Housing 2016
• Australian Bureau of Statistics - Population by Age and Sex, Regions of Australia, 2017 (Cat.
no. 3235.0)
• Here Technologies - NAVMap
Date Published
• Census - 23 October 2017
• Regional Population - 28 September 2018
• Here Technologies - Custom data
Data Source Link
• Census
- http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&re
f=topBar
• Regional Population - http://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/3235.0
• Here - https://www.here.com/en
Data Source Geography
SA2 (ASGS 2016) and 2016 Census of Population and Housing Destination Zones
Method
To generate a weighted population centre for individual SA2s, we use working age (15-64) population
counts at SA1. This allows us to create centroids in SA2s with non-uniform population distributions and
these SA2 centroids are used as origin points to model commuting patterns.
30 minute commutes from individual SA2s are modelled using road network analysis and morning peak
average road speeds (provided by Here Technologies). Using this modelled commute, we can assess
how many jobs are accessible from each SA2.
Individual SA2 job accessibility number are then weighted together using working age population
estimates. The distribution of jobs within the city definition is estimated using job counts by 2016
Census of Population and Housing Destination Zones.
Unit
Jobs
Revision Schedule
Five yearly
Page 28 Updated June 2020National Cities Performance Framework Public transport Description The proportion of journeys to work that are taken using public transport. Rationale Understanding commuting patterns is important for transport planning and identifying opportunities to promote healthy lifestyle choices. The share of people that travel to work by walking, cycling or public transport is affected by commuter preferences, the location of jobs and workers, transport prices and infrastructure. For example, more people will commute by car if driving is a cheap and quick way to get to work. More people will walk to work if jobs are close to where people live. Limitations This indicator does not separately identify the share of work trips that are made by individual modes of public transport - for example, trips by train, bus or ferry. It does not provide direct information on the effectiveness of a city’s transport network. It also does not include transport use for non-work trips. Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGAs (Western Sydney) and SUA (other cities) (ASGS 2016) Method A journey to work is identified as using public transport where the first response is Train, Bus, Ferry, Tram or Taxi. Did not go to work; Method Not stated; Method Not applicable are excluded from the calculation. Worked from home are included. Unit Percentage Revision Schedule Five yearly Page 29 Updated June 2020
National Cities Performance Framework
Active transport
Description
The proportion of journeys to work that are taken by walking or cycling ('active transport')
Rationale
Understanding commuting patterns is important for transport planning and identifying opportunities to
promote healthy lifestyle choices. The share of people that travel to work by walking, cycling or public
transport is affected by commuter preferences, the location of jobs and workers, transport prices and
infrastructure. For example, more people will commute by car if driving is a cheap and quick way to get
to work. More people will walk to work if jobs are close to where people live.
Limitations
This indicator does not include work trips that have substantial active transport component, for example
somebody who walks to a train station. It also does not include non-work active trips.
Data Source
Australian Bureau of Statistics - Census of Population and Housing 2016
Date Published
23 October 2017
Data Source Link
http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r
Data Source Geography
GCCSA (Capital cities), LGAs (Western Sydney) and SUA (other cities) (ASGS 2016)
Method
A journey to work is identified as active where the Census journey to work response is Bike; Bike,
other; or Walked only. Did not go to work; Method Not stated; Method Not applicable are excluded
from the calculation. Worked from home are included.
Unit
Percentage
Revision Schedule
Five yearly
Page 30 Updated June 2020National Cities Performance Framework Peak travel delay Description The percentage increase in the duration of a car trip made during the busiest traffic periods (7am to 10am and 4pm to 7pm) compared with when there is no congestion. This indicator is constructed using data on car trips that would take 30 minutes in a period of traffic free flow (at 2am). Rationale Data on travel delays provides information on how well a city’s road network is meeting peak demand. A reduction in peak travel times could improve access to jobs, one of the determinants of labour productivity. Shorter commute times also give people more time for leisure outside work, making a city more liveable for the people that use its roads. Limitations This indicator measures the proportional increase in car travel times during peak traffic periods. It does not permit comparisons of actual commute times nor does it provide information on travel delays for modes of transport other than car travel. Data are not available for all cities. Data Source TomTom Traffic Index 2018 Date Published 2018 Data Source Link https://www.tomtom.com/en_gb/trafficindex/list?citySize=ALL&continent=OC&country=A U Data Source Geography TomTom defined geography Method Taken directly from TomTom Unit Percentage Revision Schedule Irregular Page 31 Updated June 2020
National Cities Performance Framework Road safety Description Number of road deaths per 100,000 people Rationale The number of road deaths in a city reflects the safety of the city's road network. Limitations This indicator is based on a small number of incidents and can fluctuate between years, especially in small cities. Rates for cities with large national highways, like Albury - Wodonga, may be inflated due to the large number of motorists passing though the city boundaries. Recent data on road fatalities may be revised as new information becomes available. Data Source BITRE - National Crash Database 2017-2018 Australian Bureau of Statistics - Regional Population Growth, Australia, 2017-18 (Cat no. 3218.0) Date Published Custom data (Road deaths) 27 March 2019 (Population) Data Source Link https://www.bitre.gov.au/dashboards/ https://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/3218.0 Data Source Geography GCCSA (Capital cities) and SUA (other cities) (ASGS 2016) Method Road deaths (including pedestrian deaths) and population are calculated for each city for the two most recent years. Averages across the two years are then calculated to smooth out short-term fluctuations in road deaths. These averages are used to calculate a per 100,000 rate. Unit Number of road deaths per 100,000 people Revision Schedule Annual Page 32 Updated June 2020
National Cities Performance Framework
Knowledge services
Description
The proportion of employed persons in a city that work in Knowledge Services industries. Knowledge
Services industries are the Professional, scientific and technical services; Information, media and
telecommunications; and Financial and insurance services.
Rationale
Workers in knowledge-intensive service industries tend to be well educated, well paid and well placed
to succeed in an increasingly competitive and fast changing global economy.
Limitations
None
Data Source
BITRE analysis of:
• Australian Bureau of Statistics - Labour Force, Australia, Detailed, Quarterly, Aug 2019 (Cat
no. 6291.0.55.003) and
• Australian Bureau of Statistics - Census of Population and Housing 2016
Date Published
24 October 2019 (Labour Force) and October 2017 (Census)
Data Source Link
https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/6291.0.55.001Sep%202019?OpenDocument
https://auth.censusdata.abs.gov.au/webapi/jsf/login.xhtml
Data Source Geography
GCCSA (Capital cities), SA4s, SUAs and SA2s (Western Sydney and other cities) (ASGS 2016)
Method
GCCSA (Capital cities) results are obtained from the Labour Force Survey. SUA and Western Sydney
are estimates based on SA4 data from the Labour Force Survey. Census data at the SUA and SA2 levels
is used to estimate what proportion of the relevant SA4s results should be apportioned to the SUA
estimates.
Unit
Percentage
Revision Schedule
Annual
Page 33 Updated June 2020National Cities Performance Framework Broadband connections Description The share of households in a city with an active broadband connection, defined as an access speed of 256 kilobits per second or faster. Rationale The internet plays a pivotal role in how people learn, communicate, innovate and do business. Access to the internet is important for fostering innovation and supporting productivity. Limitations This indicator measures access to the internet based on a relatively low threshold speed. It does not provide information on relative broadband speeds between cities or connection to the NBN. Data Source Australian Bureau of Statistics - Census of Population and Housing 2016 Date Published 23 October 2017 Data Source Link http://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Census?OpenDocument&ref=topBa r Data Source Geography GCCSA (Capital cities), LGAs (Western Sydney) and SUA (other cities) (ASGS 2016) Method Extracted from Census Tablebuilder at required geographies. Not Stated and Not Applicable excluded from the denominator. Unit Percentage Revision Schedule Five yearly Page 34 Updated June 2020
National Cities Performance Framework New businesses Description The business entry rate is the number of new businesses that started actively trading on the business register over the past year as a share of the total number of registered businesses at the start of the year. Rationale Business entry is an indicator of dynamism and economic activity in a city. Strong entrepreneurial activity is associated with a dynamic and innovative local economy. Limitations A business entry can occur for reasons other than the creation of a new business. It may occur, for example, when a business starts to actively remit Goods and Services Tax (GST) and so is counted as an ‘actively trading’ business. Businesses with turnover below $75,000 are not required to register for GST; those that don’t register for GST are not included in counts of new businesses. Data Source Australian Bureau of Statistics - Data by region (Cat. no. 1410.0) 2013-2018 Date Published 17-May-19 Data Source Link http://www.abs.gov.au/ausstats/abs@.nsf/mf/1410.0 Data Source Geography GCCSA (Capital cities), LGAs (Western Sydney) and SA2 (other cities) (ASGS 2016) Method Business entries as at year ending 30 June are the numerator, with total number of businesses for the same point as the denominator. Unit Percentage Revision Schedule Annual Page 35 Updated June 2020
National Cities Performance Framework Patent applications Description This shows the number of patent applications per 100,000 persons in the city. Rationale Intellectual property, including patents, provides a foundation for innovation, which creates knowledge, builds businesses and contributes to economic growth. Patent applications are an indicator of the amount of innovation and research and development occurring in a city. Tracking data on patent applications can help understand how well a city is fostering innovation. Limitations Innovation that occurs in one city will sometimes be recorded in patents registered elsewhere. This can occur when a business with offices in more than one city has all of its patents registered by its head office. In addition, Australian firms sometimes register patents overseas, and this data is not captured in this indicator. Data Source IP Australia - Intellectual Property Government Open Data (IPGOD) 2019 Australian Bureau of Statistics - Regional Population Growth, Australia, 2017-18 (Cat no. 3218.0) Date Published 6 June 2019 (Patent Applications) and 27 March 2019 (Population) Data Source Link https://data.gov.au/dataset/ds-dga-a4210de2-9cbb-4d43-848d-46138fefd271/details?q= https://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/3218.0 Data Source Geography GCCSA (Capital cities), LGAs (Western Sydney) and SA3 (other cities) (ASGS 2016) Method The number of patent applications are summed for each city and divided by the estimated resident population of the city. For patent applications with applicants from more than one geographical area, a share of the application is apportioned evenly to each applicant. Unit Patent applications per 100,000 people Revision Schedule Annual Page 36 Updated June 2020
National Cities Performance Framework Adult obesity Description The share of people aged 18 and over with a body mass index (BMI) greater than 30. A person’s BMI is calculated as their weight (in kilograms) divided by the square of their height (in metres). Rationale Obesity is a risk factor for chronic diseases such as cardiovascular disease, diabetes and cancer (see World Health Organisation: http://www.who.int/topics/obesity/en/). High rates of obesity put added strain on public health services. Being overweight or obese can also affect a person’s quality of life. Limitations BMI is a measure of weight, not fat. Factors like age, gender and muscle mass can affect a person’s BMI independent of body fat. This indicator was converted to the city geography using a population weighted concordance, which does not take into account potential differences in the geographic distribution of this variable. Data Source PHIDU - Social Health Atlas of Australia Date Published October 2018 Data Source Link http://phidu.torrens.edu.au/social-health-atlases/data Data Source Geography SA3 (ASGS 2016) Method SA3 level estimates are aggregated to the required city level using a person weighted concordance. The total population (denominator) is derived by comparing the estimated number and the age standardised rate per 100. Unit Percentage Revision Schedule Irregular updates Page 37 Updated June 2020
National Cities Performance Framework Perceived safety Description The share of people aged 18 years and over who report that they feel safe or very safe walking alone in their local area after dark. Rationale Feeling unsafe in their community can affect people’s health and wellbeing. If people feel unsafe, it can negatively influence their social activities and erode trust within their communities (ABS, Australian Social Trends, 2010). Perceptions of safety are also influenced by factors such as crime rates in a city. Limitations Factors other than crime can influence how safe a person feels in a particular context. This can include age, sex, ethnicity, education, health and economic status (ABS, Australian Social Trends, 2010). This indicator was converted to the city geography using a population weighted concordance, which does not take into account potential differences in the geographic distribution of this variable. Data Source PHIDU - Social Health Atlas of Australia Date Published October 2018 Data Source Link http://phidu.torrens.edu.au/social-health-atlases/data Data Source Geography SA3 (ASGS 2016) Method SA3 level estimates are aggregated to the required city level using a person weighted concordance. The total population (denominator) is derived by comparing the estimated number and the age standardised rate per 100. Unit Percentage Revision Schedule Irregular updates Page 38 Updated June 2020
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