A study by Aston University researchers suggests that conventional wisdom about poverty
In their new study, scientists claim that theirThe new model, which uses computer algorithms to synthesize massive amounts of spending and economic data, could help governments around the world predict future poverty levels and plan mitigation measures.
“No one has ever used a machine beforelearning to decode multidimensional poverty, said lead researcher Dr. Amit Chattopadhyay of the University of Aston's College of Engineering and Physical Sciences. "It completely changes the way people should look at poverty."
The established poverty measures are aimed at defining a monetary threshold below which a person or household is defined as “poor”. The origins of these definitions are in the 19th and early 20th centuries.
The World Bank currently sets the international poverty line at $1.90 a day, with about 10% of the world's population - about 700 million people - living on less.
In a new study, researchersanalyzed data from India over 30 years, dividing spending into three broad categories: “staple foods” such as cereals, “other food” including meat, and “non-food items” that cover other costs such as housing and transportation expenses. The model is applicable to any country.
Recognizing the interdependence between the threecategories—increasing spending in one area usually means cutting spending in another—this allows for a more holistic measure of poverty that can be tailored to individual country circumstances. The researchers combined data sets on income, assets and product markets from the World Bank and other sources to create a mathematical model that was able to not only accurately predict past poverty levels in both India and the United States, but also ;and predict future levels based on certain economic assumptions.
Taking into account the elasticity of demand andsupply in the market, the model revises the number of people traditionally considered "poor" into a more practical "middle class". It can be scaled to reflect conditions in the sub-regions of a country, or even scaled down to a single city or area depending on the data available.
“The current understanding of poverty is verysubjective because 'poverty' will mean different things in different countries and regions,” Dr. Chattopadhyay added. “With this model, we finally have a multidimensional poverty index that reflects the actual experiences of people wherever they live, and is largely independent of the social class they are perceived to belong to.” , belong."
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