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ABSTRACT: There is a substantial literature within Australia examining poverty rates for different family types at the national level. This study presents the first Australian estimates of poverty rates for different types of families at a local level. This
paper builds upon the SpatialMSM/08B model, which fuses together data from the 2006 Australian Bureau of Statistics Census
of Population and Housing and the 2002–03 and 2003–04 Surveys of Income and Housing. We examine differences in rates of income
poverty for lone persons, sole parents, couples and couples with children. The results show that people living by themselves
and sole parents have the highest poverty rates. In addition, there are pronounced spatial differences in the poverty rates
of people living in different family situations, although the highest poverty rates for all family types tend to be in Australia’s
rural areas, with poverty clusters in most of the capital cities.
KeywordsPoverty–Family type–Spatial analysis–Microsimulation
Applied Spatial Analysis and Policy 04/2012; 4(3):145-171.
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ABSTRACT: Changing patterns of longevity, fertility and migration in Australia have driven substantial changes in population age structure
and household size and composition. Of the various dimensions of population change, population ageing is expected to present
major challenges to the financing and sustainability of welfare state programs in industrialized countries. One key issue
for many of these countries will be assessing where particular services will be required in the future. This paper outlines
the application of new forecasting techniques that age a spatial microdataset to 2027. Two illustrative examples are provided
to highlight the potential capacities of the new modelling approach for government service delivery planners. For many older
people, ageing in place is important, but is more difficult when the person is single: and so the first illustrative application
focuses on where aged single people will be living in 2027. The second application examines where future childcare places
will be required given the projected growth in the number of children aged 3–4years living in families where all parents
are working. This information will be important for Government planners in deciding the best location for childcare places.
The creation of synthetic small-area household microdata for future years offers great potential for a number of purposes,
such as analysis of the likely future sociodemographic characteristics of individuals and families at the local level and
assessment of the future geographic effect of alternative scenarios such as changes in labour force participation or fertility
rates.
KeywordsPopulation ageing–Spatial microsimulation–Needs-based planning–Small area demographic projections
Journal of Population Research 04/2012; 28(2):203-224.
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ABSTRACT: This paper compares small area estimates of the risk of social exclusion for Australian children aged 0–15 based on data from
the 2001 and 2006 Censuses of Population and Housing conducted by the Australian Bureau of Statistics (ABS). Patterns of persistence
and change in both the composite index and its underlying variables are analysed. The paper extends earlier work which focussed
on 2001 data only. We find an overall tendency for child social exclusion risk to persist in small areas over time, although
we also found some tentative support for a possible narrowing of the risk gap between the highest risk and lowest risk areas
across the 5year period. Children living outside the capital cities were at higher risk of social exclusion than those in
capital cities across both periods, although most capital cities nevertheless contain areas of high risk in both years.
Child Indicators Research 04/2012; 2(2):155-179. · 0.96 Impact Factor
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ABSTRACT: The paper is a collection of three reports on the costs of children in Australian families: 'The estimated costs of children in Australian families in 2005-06'; 'Updated costs of children using Australian budget standards; and 'Costs of children and equivalence scales: a review of methodological issues and Australian estimates'. The research was commissioned by the Ministerial Taskforce on Child Support.
Labor: Demographics & Economics of the Family eJournal. 12/2010;
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Urban Policy and Research 06/2010; 28(2):211-224. · 0.57 Impact Factor
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ABSTRACT: This study examines the socioeconomic status of NSW hospital patients in 1999–2000 and projects likely hospital costs to 2009–2010. It draws upon unique patient based datasets from NSW public and private hospitals that include hospital separations, as well as the associated treatment costs in each of the four years to 1999–2000. First, we examine whether patients of similar age had similar per patient hospital costs by socioeconomic status. Second, we examine whether patients requiring similar treatment had similar per patient hospital costs by considering patients treated for coronary heart disease. Third, we consider the impact that population ageing and changes in treatment propensities are likely to have on hospital usage and costs by 2009–2010, assuming that no changes occur in per unit treatment costs. Finally, we have estimated the additional impact of rising medical costs on these projections.
Economic Papers A journal of applied economics and policy 04/2010; 24(1):1 - 17.
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ABSTRACT: This paper reports on the calculation of poverty rates for small areas in Australia using a spatial microsimulation model. The spatial microsimulation methodology used involves reweighting data from confidentialised unit record files (CURFs) from surveys conducted by the Australian Bureau of Statistics (ABS) to small area census data, also from the ABS. The method is described in this paper, and then maps of poverty using poverty rates derived from this small area estimation method are shown for the eastern coast of Australia and its capital cities. Further analysis of poverty rates in capital cities is then conducted. We find that areas of higher poverty risk can be clearly identified within Sydney, Melbourne, Canberra and Brisbane. We also find that areas of high poverty are frequently ‘buffered’ by areas of moderate poverty. This is not always the case since, in some areas, we find a high poverty area neighbouring a low poverty area but, generally, there appears to be a moderate poverty ‘buffer’ in most capital cities.
Geographical Research 01/2010; 48(1):52 - 64. · 0.59 Impact Factor
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ABSTRACT: This paper examines national and spatial trends in the number and proportion of children with jobless parents during the past decade. At the national level, we found that the number of dependent children living in households where no parent had a job fell from around 756,000 in 1995-96 to around 684,000 in 2005-06. This reflects the increasing employment rates in Australia over this period. The proportion of all dependent children living in jobless households also fell, from 15.6 per cent in 199596 to 13.8 per cent in 2005-06. Despite this progress, however, one in every 7 dependent children in Australia in 2005-06 still lived in a household where no parent had a job. Looking at small areas, we found that in three-quarters of the 1049 small areas considered – covering 80 per cent of all children – the risk of children living in a jobless family fell between 2001 and 2006.
Australian Journal of Labour Economics (AJLE). 01/2010; 13(1):27-47.
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ABSTRACT: Multidimensional measures of disadvantage, such as social exclusion, are increasingly becoming an important focus of research into poverty and disadvantage. This paper describes the development of an Australian regional index of child social exclusion. Using data from the 2001 Census of Population and Housing, we use principal components analysis to produce an aggregate measure of social exclusion risk for children aged 0–15, and for subgroups of children aged 0–4 and 5–15. Initial analysis of the indexes provides some tentative evidence of spatial patterns in the geographical distribution of child social exclusion, including a greater risk of child social exclusion in rural areas of Australia. This article outlines one of the first examples internationally of the construction of a small-area index of social exclusion specifically tailored towards children. Copyright © 2009 John Wiley & Sons, Ltd.
Population Space and Place 03/2009; 16(2):135 - 150. · 1.82 Impact Factor
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ABSTRACT: The effective tax rates and possible work disincentives created by Australia's tax and welfare systems have been receiving extensive policy attention in recent years. Family Tax Benefit-Part A (FTB-A) is one of the key causes of high effective marginal tax rates for many families. This study uses national and spatial microsimulation models to evaluate the national and local impacts of a possible FTB-A reform option, which involves reducing the income test withdrawal rate associated with the FTB-A income test. The modelling suggests that the option would be an effective way to reduce high effective marginal tax rates for around 415,000 parents of FTB-A children, would benefit around 850,000 families, and would deliver additional assistance to middle income families living on the outskirts of our cities. Copyright © 2009 The Economic Society of Australia.
Economic Record 01/2009; 85(s1):48-48. · 0.38 Impact Factor
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ABSTRACT: This article reviews trends in effective marginal tax rates (EMTRs) from 1996-1997 to 2006-2007 for working-age Australians. Although sweeping income tax cuts reduced effective tax rates for many taxpayers, the extension of income-tested welfare payments and tax concessions worked in the opposite direction. The proportion of working-age Australians facing EMTRs of more than 50 per cent increased during the period, from 4.8 to 7.1 per cent, representing some 910,000 Australians. This article also provides the first international comparisons of how the distribution of EMTRs for earners in Australia compares with those prevailing in Europe. Copyright © 2009 The Economic Society of Australia.
Economic Record 01/2009; 85(271):449-461. · 0.38 Impact Factor
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ABSTRACT: In recent months in Australia there has been extended debate about whether the age pension, particularly with regard to single pensioners, is sufficiently high to allow older Australians to attain an acceptable standard of living. This is an important policy consideration given Australia's rapidly ageing population. By using microdata and microsimulation models, this paper examines the national and spatial impacts on the distribution of poverty among older single people of an increase in the single age-pension rate. This paper shows that the cost of increasing the single age-pension to 66 per cent of the couple-age pension rate would be about $A1.3 billion and would benefit about 824,000 single age-pensioners. Further, it is estimated that such an increase would reduce poverty rates for lone older persons from 46.5 per cent to 36.5 per cent, a 10-percentage point reduction. Looking at the spatial distribution of such benefits, the effect of the policy change seems to be generally stronger in capital cities, and in bands of rural areas in New South Wales and Victoria. Copyright (c) 2009 The Economic Society of Australia.
Economic Papers. 01/2009; 28(2):102-120.
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ABSTRACT: While static microsimulation models of the tax-transfer system are now available throughout the developed world, health microsimulation models are much rarer. This is, at least in part, due to the difficulties in creating adequate base micro-datasets upon which the microsimulation models can be constructed. In sharp contrast to tax-transfer modelling, no readily available microdata set typically contains all the health status, health service usage and socio-demographic information required for a sophisticated health microsimulation model. This paper describes three new techniques developed to overcome survey data limitations when constructing \'MediSim\', a microsimulation model of the Australian Pharmaceutical Benefits Scheme. Comparable statistical matching and data imputation techniques may be of relevance to other modellers, as they attempt to overcome similar data deficiencies. The 2001 national health survey (NHS) was the main data source for MediSim. However, the NHS has a number of limitations for use in a microsimulation model. To compensate for this, we statistically matched the NHS with another national survey to create synthetic families and get a complete record for every individual within each family. Further, we used complementary datasets to impute short term health conditions and prescribed drug usage for both short- and long-term health conditions. The application of statistical matching methods and use of complementary data sets significantly improved the usefulness of the NHS as a base dataset for MediSim.
Journal of Artificial Societies and Social Simulation, The 07/2008; 11. · 1.16 Impact Factor
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ABSTRACT: Child support is always a difficult area of public policy, balancing the sometimes competing needs of children, resident and non-resident parents and the state. This article provides a relatively rare insight into some of the processes involved in developing the new Australian Child Support Scheme (CSS), which will commence full operation in July 2008. In particular, this article shows how microsimulation modelling was used by the Ministerial Taskforce on Child Support and the government in the policy reform process. The availability of such sophisticated distributional analysis and modelling allowed the development of a comprehensive picture of how the reforms would affect CSS clients, thereby facilitating the adoption of major policy change. This article also provides a blueprint for policy-makers of how modelling can facilitate their policy development processes.
Australian Journal of Public Administration 11/2007; 66(4):422 - 437. · 0.55 Impact Factor
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ABSTRACT: This study suggests that child poverty in Australia fell by about one-third between 1982 and 1995–96, largely as a result of the very substantial increases in government cash payments to lower income families with children. However, while there were sharp falls in poverty among dependent children, poverty rates among 15 to 18 year-olds who had left the parental home or who were still living at home but not in full-time study increased very sharply. In addition, the after-housing poverty picture did not look so optimistic, apparently due to a compositional shift in the types of families in after-housing poverty.
Economic Record 10/2007; 76(234):236 - 254. · 0.38 Impact Factor
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ABSTRACT: To investigate whether the 'inverse care law' applies to New South Wales (NSW) hospital admissions--especially to older people with high socio-economic status (SES).
Cross-sectional study analysing inequalities in public and private hospital admission rates by SES, defined in terms of age, sex and family income/size at the small geographic area level.
Admissions to NSW public and private hospitals in 1999-2000 (1.8 million admissions against a NSW population of 6.4 million).
Inequalities in hospitalisation rates were expressed as rate ratios across the most and least disadvantaged 20% of the NSW population.
Public hospital admission rates for people aged 0-60 years were 24-35% higher for the most disadvantaged 20% of the NSW population than for the least disadvantaged 20%. For 70+ year-olds the direction of this difference was reversed--being 14% lower for the most disadvantaged 20% of the population (5% higher for public patients). For private hospitals this reversal prevailed for all age groups (23-49% lower). For all hospitals it was 16% and 27% lower for 60-69 and 70+ year-olds respectively, with higher admission rates for top SES 60+ year-olds most pronounced for renal dialysis, chemotherapy, colonoscopies and other diagnostic scopes, rehabilitation and follow-up, and cataract operations.
While the 'inverse care law' did apply to 60+ year-olds, it did not apply either to younger NSW hospital users or to public patients in public hospitals.
Awareness of these SES-level differentials should result in greater equality of access to hospital services, especially by older people.
Australian and New Zealand Journal of Public Health 11/2006; 30(5):467-73. · 1.20 Impact Factor
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ABSTRACT: Changes in hospital admission rates and costs in New South Wales (NSW) between 1996-97 and 2000-01 were examined by age, hospital type and socioeconomic status. A novel method led to a more accurate assessment of hospital patients' socio-economic status than was previously possible. Use of unit record hospitals data and full population Census data allowed very high levels of disaggregation. Considerable increases in the baby boomer and frail aged populations led to higher hospital admission rates over the period. This was driven by the private sector, which saw its admission rates increase by 20 per cent (with the public sector rate declining by 6per cent). Public hospital admission rates by age were found to be up to 40 per cent greater for the poorest 20 per cent of the population than for the richest 20 per cent-with a reversal of the pattern for private hospitals (up to 45 per cent greater for the richest 20 per cent than for the poorest 20 per cent). In a period when total NSW hospital expenditures increased by 21 per cent, we found that 'per admission costs' in the inpatient non-psychiatric sub-sector changed little. Copyright 2006 The University of Melbourne, Melbourne Institute of Applied Economic and Social Research.
Australian Economic Review. 01/2006; 39(4):391-408.
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ABSTRACT: In recent years outlays on the Australian Pharmaceutical Benefits Scheme have increased rapidly, prompting both attempts by government to reduce growth in outlays and renewed interest in the characteristics of the beneficiaries of the Scheme. This article uses a microsimulation model to analyse the distributional impact of Australian Government outlays on the Pharmaceutical Benefits Scheme, by such characteristics as family income, family type, age, sex and lifecycle group. We find that there are pronounced distributional effects by such characteristics as income, age and sex, with both older and poorer Australians receiving far greater PBS benefits than younger and more affluent Australians. Copyright © 2004 Economic Society of Australia..
Economic Record 01/2004; 80(s1):83-83. · 0.38 Impact Factor
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ABSTRACT: Finding ways of curbing government expenditure on the Pharmaceutical Benefits Scheme (PBS) while maintaining social equity and access to 'essential' medicines is at the centre of ongoing public debate. This article describes a microsimulation model of the PBS that simulates current and future use and costs of PBS medicines under existing and different PBS policy settings, and estimates the distributional effects of policy changes. The article outlines future developments that will extend the current model to include health outcomes. Adding health outcomes will enable the debate on PBS sustainability to be advanced beyond the prevailing cost-containment mentality to consider not only the costs of pharmaceutical use but also the benefits that result from the use of these medicines. Copyright 2004 The University of Melbourne, Melbourne Institute of Applied Economic and Social Research.
Australian Economic Review. 01/2004; 37(1):41-61.
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ABSTRACT: Census data can be represented both as lists and as tabulations ofhousehold/individual attributes. List representation of Census data offers greater flexibility, as the exploration of interrelationships between population characteristics is limited only by the quality and scope of the data collected. Unfortunately, the released lists of household/individual attributes (Samples of Anonymised Records, SARs) are spatially referenced only to areas (single or merged districts) with populations of 120 000 or more, whereas released tabulations are available for units as small as single enumeration districts (Small Area Statistics, SAS). Intuitively, it should be possible to derive list-based estimates of enumeration district populations by combining information contained in the SAR and the SAS. In this paper we explore the range of solutions that could be adapted to this problem which, ultimately, is presented as a complex combinatorial optimisation problem. Various techniques of combinatorial optimisation are tested, and preliminary results from the best performing algorithm are evaluated. Through this process, the lack of suitable test statistics for the comparison of observed and expected tabulations of population data is highlighted.
World Institute for Development Economic Research (UNU-WIDER), Working Papers. 01/2004;
