Working Draft — LGIT framework unpublished. Shared for feedback only. Please do not cite or distribute without permission.

Future Directions

Extending the HILDA × LGIT evidence layer for deeper analysis and broader impact

What We Have Built

56
Series Defined
481
Observations
4
Report Years
6
Year Coverage

The current evidence layer demonstrates what's possible with publicly available HILDA data. The extensions below would significantly expand analytical capabilities and impact.

HILDA Microdata Access

Planned

Apply for HILDA microdata access to enable individual-level regression, panel analysis, and causal inference studies.

Key Steps
  • Submit ethics application to DSS
  • Individual-level K10 trajectory analysis
  • Causal identification via panel methods
  • Subgroup heterogeneity analysis
Expected Outcomes
  • Identify causal mechanisms behind distress persistence
  • Track individual transitions between distress states
  • Control for confounding variables
Effort
High
Impact
Transformative

Historical Backfill (2009-2017)

Ready to Start

Extend the evidence layer backward using earlier HILDA Statistical Reports to establish pre-GFC baseline and long-run trends.

Key Steps
  • Digitize tables from 2009-2017 reports
  • Harmonize variable definitions across periods
  • Establish pre-GFC distress baseline
  • Track 15-year legitimacy trajectory
Expected Outcomes
  • Compare COVID response to GFC response
  • Identify structural breaks in trajectories
  • Longer time series for forecasting
Effort
Medium
Impact
High

Cross-Survey Integration

Planned

Link HILDA evidence with Scanlon Mapping Social Cohesion data to connect individual wellbeing with social trust indicators.

Key Steps
  • Align temporal coverage (2015-2023)
  • Map LGIT constructs across surveys
  • Develop composite legitimacy index
  • Test cross-survey validation
Expected Outcomes
  • Unified Australian legitimacy indicator
  • Individual-collective linkage analysis
  • Stronger LGIT empirical foundation
Effort
Medium
Impact
High

Real-Time Monitoring

Future

Build automated ingestion pipeline for new HILDA releases and supplementary surveys to enable near-real-time tracking.

Key Steps
  • Automated PDF table extraction
  • Annual report ingestion pipeline
  • Supplementary survey integration (COVID modules)
  • Alert system for trend changes
Expected Outcomes
  • Reduce publication lag from months to days
  • Early warning system for legitimacy shifts
  • Continuous evidence layer updates
Effort
High
Impact
Medium

International Comparison

Future

Benchmark Australian trajectories against comparable OECD panel surveys (SOEP, BHPS/UKHLS, PSID).

Key Steps
  • Identify comparable measures in SOEP (Germany)
  • Map to UKHLS (UK) and PSID (US)
  • Harmonize measurement approaches
  • Cross-national legitimacy comparison
Expected Outcomes
  • Australia in global context
  • Identify common vs. country-specific patterns
  • Policy learning across jurisdictions
Effort
Very High
Impact
High

Policy Brief Series

Ready to Start

Translate LGIT findings into actionable policy briefs for government departments, NGOs, and research partners.

Key Steps
  • Executive summaries for policymakers
  • Department-specific briefs (Treasury, DSS, Health)
  • NGO sector guidance documents
  • Media-ready data visualizations
Expected Outcomes
  • Bridge research-policy gap
  • Influence policy discourse
  • Establish IRSA as thought leader
Effort
Low
Impact
High

Suggested Priority Sequence

1
Phase 1Ready to Start
Policy Briefs + Historical Backfill
High impact, ready to execute with current data
2
Phase 2Planned
Cross-Survey Integration
Link HILDA with Scanlon for unified legitimacy view
3
Phase 3Planned
Microdata Application
Enable causal analysis through ethics approval
4
Phase 4Future
Real-Time + International
Scale infrastructure for ongoing monitoring

Collaborate With Us

The LGIT evidence layer is designed to be extended. We welcome collaborations with researchers, policy analysts, and organizations interested in legitimacy measurement.

Research partnerships
Data contributions
International replication