5th Meeting of the INTOSAI Working Group on Key National Indicators

A performance audit on indicators measuring fiscal long term sustainability

Ulrike KATTERL, SAI of Austria

Content

• Scope of the audit

• Sustainability

• S2-Indicator

• Additional costs of an ageing population

• Data coverage and quality

• Date requirements

• ACA recommendations

• Lesson learntUlrike KATTERL, SAI of Austria,

Scope of the audit

• Performance audit on the national budget planning process: Focus on long term budgeting, i.e. fiscal sustainability

• Legal obligations to pursue sustainable public finances: constitutional law; national budget law; EU regulations

• Risk: „Sustainability gap“ which can result from demographic developments

• „S2“ – Indicator to measure long term fiscal sustainability challenges that countries face

Ulrike KATTERL, SAI of Austria,

Sustainability

Sustainability relates to the ability of a government to assume the financial burden of its debt currently and in the future

The sustainability indicators provide a firm basis to identify the size and the main source of risks to public finance sustainability in a long-term perspective

Ulrike KATTERL, SAI of Austria,

S2 indicator

S2 indicator:shows the durable adjustment of the current primary balance required to fulfil the infinite horizon intertemporal budget constraints, including paying for any additional expenditure arising from an ageing population

It can be decomposed into

• a part that relates to the starting fiscal position and

• a part that relates to the additional costs of an ageing population

Ulrike KATTERL, SAI of Austria,

Additional costs of an ageing population

• Public pensions expenditures

• Healthcare expenditures

• Long-term care expenditures

Ulrike KATTERL, SAI of Austria,

Data coverage and quality

Austria transmits data on pensions, health care and long term care to the European Commission (EC). The EC services carry out –based on these data - the so called „ageing projections“.

The audit pursued by the ACA showed that the data coverage and quality can be improved.

This is important as the data coverage and quality determine the significance of the projection results.

Data requirements I

Public pensions expenditures:

• Some expenditures not directly linked to pension benefits (as for rehabilitation, administrative costs, etc.) are not included in the projections. These other pension expenditures make up for approximately 0.9% of GDP.

• Means-tested minimum pensions through social assistance scheme (“Ausgleichszulagen”) are excluded (0.3% of GDP).

• Unclear defining of pension payments for civil servants of the states and municipalities e.g. teachers of the states compared to other civil servants of the states

Ulrike KATTERL, SAI of Austria,

Data requirements II

Health care expenditures:

• No age- and gender- related information regarding outpatient clinic (ambulance); just lump-sum consideration possible

Ulrike KATTERL, SAI of Austria,

Data requirements III

Long-term care expenditures

• No cross-states comparability possible regarding in-kind transfers (nursery homes, etc.)

• Classification problems among care expenditures and social benefits

• Spending on „home care“ difficult to illustrate (compared to institutional care)

ACA Recommendations

• Improve data coverage, notably data generated by the states (data on teachers employed by the states, spending on long-term care, health expenditures)

• Enhance data quality, i.e. improved age-related information (e.g. hospitals)

• Improved cooperation among the federal level and the states to ease the illustration of the fiscal sustainability of the economy as a whole

Lesson learnt

It is difficult to evaluate indicators per se,

however, promising to evaluate the underlying data.

Ulrike KATTERL, SAI of Austria,

Ulrike KATTERL

katterl@rechnungshof.gv.at

Phone: 0043 711 71 - 8620

Ulrike KATTERL, SAI of Austria,