A wealth of data exists that can help us to understand poverty and there are multiple ways to analyse this data to reveal different aspects of poverty, inequality and how it impacts on people.
A common entry point is to measure economic poverty using data on consumption or income. This data is usually collected through household surveys and can be analysed with respect to absolute or relative poverty thresholds. At the international level, the World Bank has established $1.90/day as the absolute threshold for extreme poverty based on what it estimates is necessary for survival in a low income country. Anyone with consumption or income below this is considered to live in extreme poverty. Other, higher, absolute thresholds exist, which are considered more appropriate in relatively higher income country contexts. Relative poverty is understood as an income or consumption that is significantly lower than the population average.
Useful links on Economic Poverty are further available here»
Beyond the economic sphere, it is also important to measure the broader deprivations people may face. This includes access to health and education, meeting physical needs for housing and water as well as rights and freedoms. The Multidimensional Poverty Index uses household survey data that measures a range of outcomes across three dimensions of health, education and living standards, to compile a single index of poverty. The Sustainable Development Goals draw on a wide variety of data sources to provide a dashboard of 142 different indicators which measure different aspects of poverty. Several wellbeing dashboards and indices have also been developed, which measure a comprehensive range of outputs, including mental health and social support, which determine the quality of people's lives.
Useful links on Multidimensional Poverty are further available here»
Limitations of Poverty Data
Internationally comparable data on economic and multidimensional aspects of poverty have their limitations. The surveys that collect much of this data are conducted at the household level and therefore do not allow for disaggregation within households, enabling us to identify individual differences by variables like gender, age and so on. These surveys can also miss particularly marginalised and excluded groups, such as those people incarcerated, and are only conducted every few years and so are generally several years out of date for any given country at a point in time. As such, it is important to draw on a range of different data and measures to understand how poverty manifests itself in a place. Administrative data for example can provide insights on service users and their outcomes. Community generated data, quantitative and qualitative can provide important insights from the lived experiences of those living in poverty. A breadth of data and measures should be analysed for a more thorough and context specific understanding of poverty.