FaCSIA Presentation, 8-6-06 final

skillfulbuyerUrban and Civil

Nov 16, 2013 (3 years and 6 months ago)

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Population Wellbeing:

Data needs for social

policy


Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Outline of presentation


Outline the purpose and policy context of FaCSIA


Highlight some trends in policy thinking and their
implications for how we collect and use data


Illustrate these principles in relation to some
current policy interests of FaCSIA


BUT…not seeking to attempt to articulate a
coherent framework:


The draft family framework is offered here as a
point of discussion

Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

FaCSIA’s purpose


Improving the lives of Australians

by helping to build the capacity and wellbeing of
individuals, families and communities

Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

FaCSIA’s strategic themes
-

1



Maximising economic and social participation
including through business, community and other
partnerships



Focussing on early intervention, especially for
children and families



Assisting those who are most disadvantaged



Achieving better outcomes for Indigenous
Australians


Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

FaCSIA’s strategic themes
-

2



Responding to intergenerational change



Balancing rights and responsibilities in the design
and delivery of government assistance



Providing and supporting Whole of Government
leadership


Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Policy perspectives
-

1



A focus on disadvantage



A dynamic view of policy issues
-

pathways and
transitions



An interest in influencing behaviour


promoting
personal responsibility and self
-
reliance


Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Policy perspectives
-

2



An appreciation of interactions between different
spheres of policy


social and economic; health
and welfare; employment and wellbeing; work and
family



A recognition of the changing environment


ageing population, different family dynamics,
flexible labour market


Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Some questions about data gaps


What data is missing, that could help us answer policy
questions?



Is the data we have in the right form to answer policy
questions?



Collecting items together from different domains


Linking data from different sources


Understanding dynamics (ie, the time dimension)


System views, and drilling down to capture diversity
and observe effects

Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

FaCSIA’s response to data gaps


Administrative Data Sets


Based on Centrelink payment data


Longitudinal with fortnightly panels


Linkages


internal, related data, survey data



New policy insights


Lone parents with multiple spells on income support


Long term welfare dependence of teenage mothers


Outcomes for children of income support mothers

Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Longitudinal surveys


HILDA


Household, Income and Labour Dynamics in
Australia


LSAC


Longitudinal Study of Australian Children



Longitudinal surveys can also be used understanding
dynamics


i.e., the time dimension.



Multi domain


allowing researchers to explore
interactions between different spheres of policy interest

Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Longitudinal data


Specifically, data from longitudinal surveys can be used to:


i.
Make distinctions between transitory and persistent
characteristics (e.g., poverty or wealth);

ii.
Study flows between states (e.g.,
employed/unemployed);

iii.
Conduct studies of intergenerational consequences
such as poverty and dependence;

iv.
Estimate change surrounding certain events (e.g.,
health status before and after marital separation); and

v.
Estimate more sophisticated behavioural models.

Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Longitudinal data and policy analysis


Longitudinal data can contribute to our understanding of dynamic
policy issues.



For instance, the HILDA survey indicates that in 2001,
13.2%

of
individuals were classified as being ‘in poverty’.



However, the HILDA survey can be used to examine the
persistence

of poverty between 2001 and 2003. For example,
3.4%

of individuals were classified as being poor in
all three years
.



Moreover, nearly one
-
fifth (~20%) of individuals were poor in
at
least one year
.

Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Examples of data gaps


Missing data


Indigenous identified data


Sample views


Families


Data views


Child Care data with outcomes

Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Indigenous identified data


Australia’s biggest social policy challenge


Data to support policy is not strong


Heavy reliance on Indigenous identifiers in
data collected for other purposes


Need to:


Improve Indigenous identification in
survey and administrative data


Collect Indigenous specific data


Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Views of families


Currently, data is collected on families
residing in a single household


What is missing:


Non
-
intact (or separated) families


Dependent children not at home


Dependent elders not at home


Adults ‘living apart together’

Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Linking child care to outcomes


Currently, industry data and usage data


But can’t measure key outcomes


Impact on labour force participation


Impact on child development


Research and Analysis Branch
Population Wellbeing: Data Needs for Social Policy

Conclusion


FaCSIA is making a substantial effort to address current data gaps



Current longitudinal surveys and administrative data provide a rich
source of information that can be used in policy development



There is, however, a case for collecting additional data to respond
to our emerging policy challenges, such as:



Indigenous identified data;


Non
-
intact (or separated families); and


Linking child care data to outcomes.