Improving Work Incentives and Incomes for Parents: The National and Geographic Impact of Liberalising the Family Tax Benefit Income Test*

Harding, Ann; Vu, Quoc Ngu; Tanton, Robert; Vidyattama, Yogi

doi:10.1111/j.1475-4932.2009.00588.x

Cited by 23 publications

(25 citation statements)

References 10 publications

(17 reference statements)

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“…By knowing where concentrations of disadvantage are located, policy makers and service providers can allocate resources and target policies better. Recent applications of this spatial microsimulation technique to modelled policy changes can be found in Harding et al (2009b) and Tanton et al (2009a), an approach which allows policy makers to see the spatial effect of proposed policies.…”

Section: Discussionmentioning

confidence: 99%

“…Combining the two sample surveys in this way maximises the sample size available for modelling, and provides the potential for the model to be used in the future with a static microsimulation model of Australia's tax and transfer system, based on the same survey files, to allow for the regional simulation of policy changes (see Harding et al 2009b, for a recent example of this capacity).…”

Section: Spatial Methodologymentioning

confidence: 99%

See 1 more Smart Citation

Poverty at the Local Level: National and Small Area Poverty Estimates by Family Type for Australia in 2006

Miranti

McNamara

Tanton

et al. 2010

Appl. Spatial Analysis

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Spatial Methodologymentioning

confidence: 99%

Poverty at the Local Level: National and Small Area Poverty Estimates by Family Type for Australia in 2006

Miranti

McNamara

Tanton

et al. 2010

Appl. Spatial Analysis

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“…This rapidly growing field now includes simulation of the smallarea effect of changes in income taxes and cash transfers (Chin et al 2005;Harding et al 2009); development of small-area measures of poverty and housing stress (Tanton et al 2009a, b;McNamara et al 2007); small-area modelling of Activities of Daily Living Status and need for different types of care (Lymer et al 2006(Lymer et al , 2008aWilliamson 1996); development of the SimObesity model to examine small-area obesity among children (Procter et al 2008); small-area health-related conditions (Ballas et al 2006b); the socio-economic effects of major job gain or loss at the local level (Ballas et al 2006b) and a number of other applications (Ballas et al 2005a, b;Clarke 1996).…”

Section: Small-area Data and Spatial Microsimulationmentioning

confidence: 99%

Demographic change and the needs-based planning of government services: projecting small area populations using spatial microsimulation

2011

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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 3-4 years 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.

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“…Examples of this work include simulating the small-area impact of changes in income taxes and cash transfers (Chin et al, 2005;Harding et al, 2009;Tanton et al, 2009); development of small-area measures of housing stress ; the need for different types of aged care (Lymer et al, 2008;; and the retirement saving by gender of those who have just retired .…”

Section: Introductionmentioning

confidence: 99%

The Challenges of Combining Two Databases in Small-Area Estimation: An Example Using Spatial Microsimulation of Child Poverty

Vidyattama¹,

Miranti²,

McNamara

et al. 2013

Environ Plan A

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Spatial microsimulation techniques have become an increasingly popular way of fulfilling the need for generating small-area data estimates. However, the technique also poses numerous methodological challenges, including the utilisation of two different databases simultaneously to produce estimates of population characteristics at the local level. An important but neglected question is whether different distributions of key variables within these two databases may affect the validity of the spatial estimation results. This study uses the significant policy issue of small-area estimates of child poverty rates in Australia to examine this question. The different income distributions for families with children in the two databases and the consequent effect on child-poverty estimates are assessed, while the apparent validity of these synthetic small-area poverty rates is gauged.

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Improving Work Incentives and Incomes for Parents: The National and Geographic Impact of Liberalising the Family Tax Benefit Income Test*

Cited by 23 publications

References 10 publications

Poverty at the Local Level: National and Small Area Poverty Estimates by Family Type for Australia in 2006

Poverty at the Local Level: National and Small Area Poverty Estimates by Family Type for Australia in 2006

Demographic change and the needs-based planning of government services: projecting small area populations using spatial microsimulation

The Challenges of Combining Two Databases in Small-Area Estimation: An Example Using Spatial Microsimulation of Child Poverty

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