This paper develops a social insurance accounting model for a notional defined contribution (NDC) scheme combining retirement and long-term care (LTC) contingencies. The procedure relies on standard double-entry bookkeeping and enables us to compile a “Swedish” type actuarial balance sheet (ABS) following a framework equivalent to an open group approach. This methodology is suitable for reporting the system’s solvency status and can show periodical changes in the system’s financial position by means of an income statement. The information underpinning the actuarial valuation is based on events and transactions that are verifiable at the valuation date, without considering expected future trends. The paper also contains an illustrative example to make it easier for policymakers to understand the main advantages and difficulties of our proposal. The policy conclusions stress the need to properly report social insurance benefits to enhance transparency and sustainability and to improve decision-making because it is in the public interest to do so.

IMPACT For policy-makers, statisticians, public accountants, social security actuaries, public finance economists and other stakeholders, the regulation introduced by the EU regarding the disclosure of an accrued-to-date liability (ADL) table (Table 29) is a valuable first step in reporting pension liabilities. However, the information disclosed is incomplete and does not provide an indicator of solvency or sustainability. In addition, pensioners and those making contributions to pensions have no information regarding the security of their future benefits. In this timely article, the authors present a methodology to easily transform Table 29 into an actuarial balance sheet (ABS) and compile its associated income statement (IS). The ABS can be used to assess the solvency of pension schemes, whereas Table 29 cannot.

This paper studies the representativeness of the Continuous Sample of Working Lives (CSWL), a set of anonymized microdata containing information on individuals from Spanish Social Security records. We examine several CSWL waves (2005–2013) and show that it is not representative for the population with a pension income. We then develop a methodology to draw a large dataset from the CSWL that is much more representative of the retired population in terms of pension type, gender and age. This procedure also makes it possible for users to choose between goodness of fit and subsample size. In order to illustrate the practical significance of our methodology, the paper also contains an application in which we generate a large subsample distribution from the 2010 CSWL. The results are striking: with a very small reduction in the size of the original CSWL, we significantly reduce errors in estimating pension expenditure for 2010, with a p value greater or equal to 0.999.