Intergenerational Solidarity Index

Method

About the Index

The Intergenerational Solidarity Index has been created by interdisciplinary scientist Jamie McQuilkin. It was initially developed as a thesis presented at the University of Iceland in 2015. It was then condensed into a journal article which won the 2018 Intergenerational Justice Prize of the peer-reviewed Intergenerational Justice Review under the title Doing Justice to the Future: a global index of intergenerational solidarity derived from national statistics. In 2020, a significantly revised and updated version of the index was published in Roman Krznaric’s book The Good Ancestor, together with analysis by McQuilkin and Krznaric.

What does it measure?

The index aims to measure the concept intergenerational solidarity. In the sense used here, this is defined as “investments or sacrifices that are intended to increase or sustain the wellbeing of future generations”. This can be said to be a combination of the different kinds of capital – environmental, economic and social – that the current generation chooses to give to the future.

Resilience, adaptability and transformability are also important properties of many kinds of capital which we bequeath to future generations (e.g. housing; ecosystems; social norms), but aggregate measurement of these on a national scale is inherently difficult or impossible, as they are specific to the systems they apply to.

How does it measure this?

The index uses three dimensions of capital transfer – economic, social and environmental – and measures these dimensions by aggregating three indicators in each. For example, the dimension of social capital aggregates indicators of pupil:teacher ratio in primary schools, income-adjusted infant mortality rates, and the sustainability of current birth rates.

The dimensions are then averaged. These are then adjusted against a final indicator, which measures the amount of hydrocarbon each nation produces.

Indicator equations

Indicator (x); all 5-year averages prior to year n1 (y)100 (z)EquationYear (n)Source
EnvironmentalAnnual forest cover change (%)≤0.25%≥0%100-100(2x^\frac{1}{2})2016FAO
Carbon footprint intensity ($ GDP (PPP) per GHa)$0$25000100(\frac{x-y}{z-y})2016Ecological Footprint Network
Renewable and nuclear (% of energy consumption)0%100%\sqrt{\frac{x}{100}}+(x_n-x_{1992})2016U.S. E.I.A.
EconomicWealth inequality Gini coefficient 9060100(\frac{x-y}{z-y})2018Crédit Suisse
Current account balance (%GDP)-10%0%100(\frac{x-y}{z-y})2018IMF
Adjusted Net Savings (%GNI)020%100(\frac{x-y}{z-y})2017World Bank
SocialPrimary pupil: teacher ratio50:110:1100(\frac{x-y}{z-y})^22017UNESCO; national statistical bodies
Difference between expected and actual child mortality based on GDP/c regression>50% more<50% lessx+502017UNICEF; WHO; World Bank; UN DESA
Predicted birth rate per woman; adjusted for child mortalityIf x≤z: 1.05; if x≥z: 4.21.8100(\frac{x-y}{z-y})2017UNICEF; WHO; World Bank; UN DESA
PenaltyFossil hydrocarbon production (Gigajoules/capita)10000100(\frac{x-y}{z-y})^22017U.S. E.I.A.

Notes on indicator calculations

Most indicators are based on data distribution, and this is the primary reason for variable equations between each of them. Scale end-scores are largely not target values, and the intention is that limit values are adjusted as distributions change. The major exception is mortality-adjusted birth rate, where the limits are half and twice approximate replacement rate of 2.1. “Ideal” fertility rates are the subject of much debate; the 100-score of 1.8 is taken as an estimate of a sub-replacement fertility rate that does not excessively unbalance the demographic structure, whilst allowing for a steady reduction in population and thus reduction in environmental impact and increase in resource allocations per person. In addition, due to complexities in gains to forest cover and current account balances, all positives in these indicators are currently treated as a 100 score. 1992 – the year of the Rio summit – is set as a baseline year for planned global energy transition to modern renewable and nuclear energy sources.

Indicators are aggregated arithmetically within dimensions (environmental, economic and social) and then geometrically between dimensions, to recognise the limited or non-substitutability of different kinds of capital whilst allowing for some nations to have a medium or high overall score despite extreme low scores in one indicator. Last, a penalty adjustment is applied according to hydrocarbon production per capita, both due to its constituent effects on intergenerational welfare and ability to allow for disproportionate investments (e.g. through sovereign wealth funds) that would otherwise seem to be in the interests of future generations. The raw index average is multiplied by the pecent score on this indicator to the power of 0.1 (i.e. a score of 1 out 100 would reduce total score by 33%).

Some indicators (especially current account balance) may index intergenerational solidarity in the interests of the citizens of one nation at the expense of those in others. This is also specifically true of those nations with sovereign wealth funds, especially those built on fossil fuel revenues – such funds are inherently long-term projects that benefit mostly or only the citizens of that nation at the expense of the global commons or those countries whose assets are purchased. Our survival and wellbeing as a species will likely depend on broader solidarity than this. However, few current examples exist of systematic international and intergenerational solidarity, and unfortunately some of the policies of the most long-termist of nations in this index can be considered antisocial, antieconomic or antienvironmental in the global context. The purpose of this index is thus limited to attempting to reveal intergenerational solidarity within nations so that we may begin to understand what predicates and motivates this.

Rejected Indicators

Measuring intergenerational solidarity through proxies across many countries is challenging. During the initial construction of the index and its revision, many potential indicators were considered and rejected for various reasons summarised in the table below. The index is intended to incorporate new indicators – if you have suggestions, please get in touch.

IndicatorSourceReason for rejection
Maternity leave laws, after Kasser (2011)ILODespite being used elsewhere, there is little evidence linking this to the wellbeing of children, as opposed to parents.
Education spend (%GDP/c) per primary studentUNESCONot enough data points
School AttendanceUNESCONot enough differentiation in rich countries; statistics heavily skewed by repeat years, late entry etc.
Life ExpectancyWorld BankNot enough differentiation in rich countries; theoretically lacking as it describes current human capital rather than the next generation’s.
Funding for health care as % of GDP/cVariousLack of centralised data on public/private spending splits; theoretically may relate exclusively to disproportionate investment in current generations e.g. healthcare for the elderly
State spending on the old vs. the young after Vanhuysse (2013)VariousNot enough data; may relate more to differences in pension funding mechanisms
Deforestation rateSatellite; Global Forest WatchNo national accounts as of late 2019
Consumption CO2 per capitaFootprint of NationsNot enough data points
Gross Capital formationWorld BankNot as precise as Adjusted Net Savings
Gross SavingsWorld BankNot as precise as Adjusted Net Savings
Central Government DebtWorld BankNot an indicator of short-termism and non-comparable between federal and non-federal countries
Income Inequality (Gini)World BankWealth inequality is more relevant
Research & Development BudgetWorld BankNon-comparable data due to differences in public/private investment
Advertising to ChildrenVariousNot enough data points
Social Discount Rate for public spendingVariousNot enough data points
Household DebtVariousNot enough data points
Pension spending/deficit by central governmentVariousNon-comparable data due to differences in public/private investment; not enough data points
United Nations Voluntary Contributions (%GDP/c)U.N.Inadequate data; U.N. funding is generally progressive (even after corrections for GDP)
Child WellbeingUNICEFNot enough data points
Status of tobaccoVariousToo much variation in policies
Soil erosion/land degradationFAONot enough time-series data points (1991 only); doubts about accuracy; much reflects semi-natural change (e.g. desertification)