Small Area Social Indicators

OECD Comparable and other selected small area social indicators

This project has developed a suite of indicators across a number of domains which can be used to assess and measure local community (SA2) socio-economic performance. Based on the set of indicators used by the Organisation for Economic Co-operation and Development (OECD), these indicators are accessible to urban researchers via the AURIN Portal.
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Measures and benchmarks of local socio-economic performance are important tools for research and policy surrounding sustainable and effective communities. However, national level indicators obscure the degree of geographic variation within a country, which can give a misleading impression of the status of social equity and wellbeing. The expression of the same indicator at a small area level, along with its value relative to an Australian average, enables us to obtain more realistic insights into the standard OECD domains of social equity and wellbeing, given that daily life for most people occurs within a local area.

The Australian Small Area Social Indicators (ASASI) is informed by the OECD indicators project Society at a Glance*. The final set of indicators in ASASI cover the same domains used by the OECD (general context; self sufficiency; equity; health; and social cohesion), and where possible uses similar indicators. These indicators are provided for Statistical Areas in Australia using the latest available data. Some of the indicators are based on microsimulated data using the latest spatial microsimulation techniques developed at NATSEM. The reference period for the data is from 2006 to 2012.

Datasets used to construct the indicators include:

The indicators produced from these datasets include:

  • Annual median equivalised household disposable income
  • Migration (international arrivals)
  • Family structure
  • Old age support rate (dependency rate)
  • Employment rate
  • Unemployment rate
  • Student performance and/or attendance
  • Income inequality using Gini coefficient
  • Poverty
  • Trust
  • Total health expenditure by area and per capital for SA2s
L1.3 Figure 1

Conceptual model of OECD Comparable Small Area Social Indicators for Australia project

Project Output

  • OECD comparable social indicators for small areas uploaded to the AURIN Portal
  • Metadata for all indicators
  • An online user guide

Project team overview

Dr Lisel O’Dwyer (Main Contact) conducted this work while based at the University of Adelaide and is now located at Flinders University. She has a background in urban studies, public health, ageing and anthrozoology, and has research interests in wellbeing and social inclusion and equity.

Professor Scott Baum is a Professor and a Research Fellow at the Urban Research Program at Griffith University.

Professor Robert Tanton is a Senior Researcher at University of Canberra. He has extensive experience in calculating small area indicators of disadvantage from national survey datasets using spatial microsimulation techniques.

All are involved in social research, particularly in the field of urban studies or processes associated with urban areas and are familiar with the need for better social indicators to inform their work.

Dr Lisel O’Dwyer
08 8201 2985
Professor Scott Baum
07 373 55430
Professor Robert Tanton
02 6201 2769

project partners

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* Definitions of terms: 

  • OECD: Organisation for Economic Cooperation and Development. The OECD has produced seven editions of the report ‘Society at a Glance’ which is a biennial overview of social indicators for all member countries since 2001.
  • HILDA Dataset: The Household, Income and Labour Dynamics in Australia Survey (HILDA) is a household-based panel study which began in 2001 and collects information about economic and subjective well-being, labour market dynamics and family dynamics.

    This data uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this paper, however, are those of the author and should not be attributed to either FaHCSIA or the Melbourne Institute.

  • STINMOD: STINMOD (Static Incomes Model) is NATSEM’s static microsimulation model of Australia’s income tax and transfer system. The first version of STINMOD was released in 1994 and since then, the model is updated each year in line with the latest changes to the Commonwealth Tax and Transfer system.
  • ACARA: Australian Curriculum, Assessment and Reporting Authority (ACARA) is an independent statutory authority which runs NAPLAN (National Assessment Program – Literacy and Numeracy). More information here.
  • Generalised Trust Levels 1-7 (Synthetic Estimates): Generalised Trust has been estimated from Wave 10 of the HILDA dataset. The question used on HILDA was “To what extent do you agree or disagree with the following statements? g) Generally speaking, most people can be trusted” and was ranked on a scale of 1 to 7, with 1 being “Strongly Disagree” and 7 being “Strongly Agree”.
  • Gini Coefficient: A measure of statistical dispersion representing the income distribution of a nation’s residents, and is the most commonly used measure of inequality. It measures  the inequality among values of a frequency distribution such as levels of income on a scale between 0 and 1, where 0 expresses perfect equality (everyone has the same income) and 1 indicates maximal inequality (one person has all the income or consumption, and all others have none).