Following the successful publication of the Global Living Wage Dataset in 2020 and the Global Living Wage Dataset 2022, we decided to update and improve the dataset for the reference year 2023. More than 300 hundred organizations worldwide requested our dataset last year, allowing us to deliver an important impact in this field.
Given the investment required to deliver this new dataset, we decided to price it at 1,500 USD/organization. However, feel free to reach out to discuss special conditions (e.g. for non-profit, research, etc).
We continue to observe that the lack of availability of a comprehensive and global dataset on living wages is limiting the adoption of impact valuation methods and increasing the barrier of entry to start developing strategies on the topic of living wages (in particular related to the realization of benchmarks for international payroll).
Our objective is to fill this gap and allow any organization to get started on the topic using our dataset, as an entry product. For more advanced and granular data, we recommend checking the dataset from the WageIndicator Foundation.
This Global Living Wage Dataset dataset relies on public cost of living data drawn from Numbeo from which we built a living wage model. We completed the dataset on countries where direct cost of living data was unavailable by developing a linear regression model based on purchasing power parity data. The methodology is described directly in the dataset file.
This approach allows us to publish:
Living wage estimates for 218 countries and territories (103 with primary data, clearly identified in the dataset)
Living wage estimates for 360 cities (all based on primary data)
4 types of living wages to chose from: typical family, standard family, single individual, single working parent family
Differentiation for rural and urban living wages at country level
Fully transparent methodology provided in the dataset file (XLS), considering Anker&Anker 2017 as the international standard
Cost of the Global Living Wage Dataset: 1,500 USD
The following figures are high-level summary from the Global Living Wage Dataset.
The next figure shows the Global Living Wage Dataset on a global map and color-coded for the typical family living wage type for rural conditions. As expected, North America, Europe and Australia show the highest living wages on average while Latin America, Middle-East and Asia show the lowest values.
The choice of living wage type (among the four types made available in the dataset) influences greatly the living wage value, although regional characteristics are even more important at determining the living wage value. Single-working parent living wages show the highest values, while standard and typical family living wage values are very close to each other. Single individual shows the lowest value of the set.
The type of economy and income group classification of countries (using the World Bank classification) is a good predictor of the value of the living wage. In general, cost of living is relatively correlated to price and income levels. However, we observe some inverse relation for rural living wages' estimates which are higher for low-income countries. This might be explained by the lack of existing services or infrastructures, which makes it more expensive to access the same level of living standard. This effect is also observed for urban living wages for low-income countries when compared to lower middle income, although to a lesser extent.