We developed the first global dataset of living wages and developed a model to account for the impact of wages (money) on human capital, called the Health Utility of Income (HUI). Thanks to this dataset and method, companies can benchmark globally employees’ wages levels against the living wage baseline and assess their contribution to human capital with the HUI. This work has been supported by Novartis.
This work has been updated and is now available through two new whitepapers available on this page.
Download the latest version of the Living Wages Global Dataset through this article.
Human capital includes multiples aspects related to people including health, knowledge, skills and income. The World Bank formally measures it as the present value of the future earnings of the labor force. Income, as part of the employment conditions and environment, has also been recognized by the World Health Organization (WHO) as one among various social determinants of health. The WHO showed in particular that income inequalities within a country correlate strongly with the quality of life and life expectancy. Put simply, our level of income influences how well and long we live.
Income levels are highly unequal in our world. While inequalities are inevitable and even beneficial in specific context, the current level of wage inequalities negatively impacts our society and our capacity to grow our economy in the future. This is illustrated by the inequalities at global scale: 82% of the wealth created in the last year (2017) went to the top 1%, while the bottom 50% saw no increase at all (Oxfam, 2018). Actually, 42 individuals now own the same wealth as the bottom 3.7 billion people (Credit Suisse, Oxfam 2018).
Moving from these observations to analysis and action requires an understanding of what is a sustainable income. This is defined by the living wage (LW) concept which enables evaluating the quality of received income. It can be defined as the wage required to satisfy basic needs i.e. a decent living. LW is higher than the poverty wages. It is also higher than the legal minimum wages in many cases. As no living wages dataset exists for all countries, we developed it in this project (see associated downloads at the top of the article), using different data sources and models to fill the data gaps.
Receiving a wage below a living wage threshold will ultimately lead to a reduced quality of life and life expectancy, also called health inequities. On the contrary, receiving a wage above the living wage threshold will positively influences the life quality and expectancy. Some authors, in the US (NAS, 2015) and in France (INSEE, 2018), have shown that differences in life expectancy can reach up to 13 years between the low- and high-income population group. This difference in life expectancy is influenced by many socio-economic factors as well as behavioural, genetic and environmental factors. In practice, we observe a high variability between different countries of health inequities, linked to income inequalities.
The Health Utility of Income (HUI) factor provides a measure of the health inequities (measured in DALYs/capita) linked to income inequalities (i.e. difference between the poorest and the richest), expressed per year of activity (work). The HUI factors are provided per country.
In practice, the utility of income is a log function that is maximum at the living wage level and that decreases when the income increases until roughly four times the living wage (LW). Above four times the LW, the utility drops to 0 (empiric analysis). In order to simplify this function, a linear function can be used (slope =HUI / 4xLW). By calculating this factor (expressed in DALY/unit of income) and multiplying it by difference between the wage/income received and the living wage, we can estimate how much life quality/expectancy someone gain/lose due to its level of income in a specific country. It can be monetized by using a monetary value of DALYs, a version of which is called the Statistical Value of Life.
To obtain more details on how to use those HUI in the context of (human capital) impact valuation, please contact the author: sv@valuingnature.ch.
By sharing the whitepaper and the datasets (both living wages and HUI, see at the top of the article), we hope to support other organisations to replicate such analysis and develop further the model.