Technical Details
Quantifying the Pensions Gap
Methodology

The methodology employed to quantify the pensions gap is based on bottom up analysis of the following countries: Czech Republic, Germany, Spain, France, Hungary, Ireland, Italy, Lithuania, Poland, Romania, and the UK. In addition the pensions gap has been quantified for Russia and Turkey – countries that Aviva operates within - to allow comparison and analysis against non-EU27 countries.
In each case, a detailed analysis was carried out to quantify the annual retirement income gap and the capital shortfall at retirement to derive a figure for the additional savings required to meet the capital shortfall at retirement.
The heterogeneity of pensions systems across EU member states necessitates some degree of simplification to allow for meaningful cross-country analysis. Three categories were identified:
- State pensions
- Mandatory and voluntary private sector Defined Benefit (DB) pensions
- Mandatory and voluntary private sector Defined Contribution (DC) pensions
Non-pensions products that are solely used to provide retirement income are also included in the analysis under the "private DC pension" category. Only three such examples were identified:
- In Hungary, where voluntary individual retirement accounts are operated by banks and stockbrokers
- In Germany and Spain, where insurance contracts are used specifically to provide retirement income
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Notes: |
Data
The inputs for this analysis are based on a programme of secondary research conducted by Deloitte and review sessions held with country experts across Aviva. Initial analysis covered ten EU Member states covering c 80% of the EU population. Results were then extrapolated to estimate the EU-wide pensions gap.
Base case
The base case assumptions used for the purposes of this analysis are as follows:
| Variable | Assumption |
| Replacement Rates | Low income: 90%; mid income: 65%; high income : 55% |
| Return on Savings | 5% pa |
| Retirement Age | Average age of retirement by country |
Sensitivities used for the purpose of testing alternative scenarios are variations on the base case assumptions.
