Living wages 


Achieving the Sustainable Development Goals by 2030 depends critically on all workers around the world earning a living wage, not only because labor earnings is the main –if not only- source of income for most people in the world, but also because thriving businesses and societies depend on citizens that are free from exploitation and destitution.

The living wage concept refers to a salary that would allow a typical worker family to live a modest, but decent life, including access to a nutritious diet and minimally acceptable housing. A living wage should also be sufficient to allow the family to live together, rather than some family members having to migrate and live apart to complement family incomes.

SDSN Bolivia believes that objective, standardized, and widely accepted living wage benchmark estimates are the first step in a long-term process towards achieving wages that will help workers escape poverty. We have therefore partnered with the Global Living Wage Coalition ( to help calculate, publish and update living wage benchmark estimates for different locations around the world using the Anker Living Wage Methodology.

SDSN Bolivia is proud to be part of the Anker Living Wage Research Network. Over the next several years, we will not only be carrying out living wage benchmark studies throughout Latin America, but SDSN Bolivia is also responsible for systematically updating living wage benchmark estimates around the world. These up-to-date and widely accepted benchmarks are important to help stakeholders throughout the global supply chains negotiate a fair distribution of the value generated for the final consumers, ensuring that everybody involved earn at least a living wage.

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Inequalitrees – A Novel Look at Socio-Economic Inequalities using Machine Learning Techniques and Integrated Data Sources

SDSN Bolivia, together with the University of Trento in Italy, the ifo Institute in Germany, and the Institute for Human Development in India won a 4-year, 1.5 million Euro grant from the Fondazione Compagnia di San Paolo to investigate the levels, drivers and spatial distribution of unfair socio-economic inequalities within and between countries, focusing on Bolivia, Germany, India and Italy.

We adopt a multidimensional, interdisciplinary and cross-national approach, by analyzing inequality of opportunity and poverty in three key individual outcomes (education, income and health) in four countries (Bolivia, Germany, India, Italy), and integrating contributions from economics, sociology, geography, and computer science. We will look not only at how different socio-economic conditions shape life opportunities across the countries, but we will also map in detail within-country variations in socioeconomic inequalities. A key innovative feature of our project consists in the application of cutting-edge machine learning techniques to integrate and analyze large scale datasets from various sources, including national and international surveys, administrative and register data, as well as innovative data extracted from satellite images. The combination of various data sources and the application of machine learning and spatial regression methods promise significant progress in understanding the environmental and institutional features that countervail the existence of unfair socio-economic inequalities.

For more information, please visit the project website: