Vionnet, S. (2020). A worldwide living wage dataset for benchmarking compensation practices in global value chains. Technical Paper. Valuing Nature, DSM, Kering, Philips, WageIndicator Foundation, Amsterdam.

Vionnet, S. (2020). A worldwide living wage dataset for benchmarking compensation practices in global value chains. Technical Paper. Valuing Nature, DSM, Kering, Philips, WageIndicator Foundation, Amsterdam.

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ABSTRACT

This whitepaper is the result of a collaboration between DSM, Kering, Philips, the WageIndicator Foundation and Valuing Nature. Its objective is to develop a worldwide living wage dataset to support benchmarking of compensation practices with living wages, in global value chains. It targets in particular the private sector and multinational companies that have complex operations and supply chains covering many countries. Many companies, such as DSM, Philips and Kering, are starting to use this benchmarking activity as input for their sustainability and compensation strategies.

The following points provide the key take-aways of the project:

  • A global dataset of living wages has been developed that covers 185 countries and additional regions and cities, with a strong focus on China, India and Brazil.
  • An innovative approach has been used combining primary data collection (thanks to the WageIndicator Foundation work), secondary data collection and modelling; 57% of the national living wage estimates is based on primary data collected.
  • Variability of living wage estimates depends on both a) methodological value-based decisions about the calculation of the living wage, and b) actual data or variability of cost of living within a given country. The family composition and number of workers per family are two of the main parameters accounting for most of the living wage estimates variability.
  • The selection of the living wage benchmark, within the different options that exist, needs to be informed by the context of the company it applies to. We can define a maturity curve, moving from compliance (legal minimum wage) to living wage that covers different family situations. The most common benchmarks are the typical and standard family. For more advanced use, we argue that there is a living wage definition that could ensure even less risk for the workers' families, and implies using in its definition only one working adult per family and a number of kids based on the national fertility rate and rounded up to the next whole number. The choice of living wage benchmark is still a matter of debate in the living wage field.
  • Finally, we point out some limitations in the current practices of living wage calculations based on the Anker & Anker 2017 methodology, which is often used as a reference. These limitations include retirement pension considerations, differences in socio-economic conditions and alignment of living standards among countries, social security and redistribution as well as
    informality linked to taxation. Those limitations are starting to be addressed in the latest estimates from WageIndicator Foundation for instance.
  • We hope that this work will encourage companies to benchmark their wage practices and align or surpass the living wage thresholds for their employees and workers in their operations and value chains. The author of this paper will provide the national estimates derived from this work upon request, to support any company in benchmarking their wage practices. 

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