One of the challenges as a math professor is to connect mathematical definitions, properties, and rules to real applications. Some applications are models to estimate poverty. I am thankful to CAORC-AIIS India seminar to reflect on this subject.
Defining and measuring poverty is complex and it is imperative to develop clear and rigorous efforts to quantify it, to ensure that no one is left behind, but also identifying the sustainable projects that play an important role to reduce the levels of poverty is key. Two considerations were used when creating this project: Include some research aspects and reflect about the usefulness of mathematical models. At the end of each term the students connected two sections of Math123 about linear equations and the weighted average.
Two models were used to measure poverty. The Poverty Line and the Multidimensional Poverty Index. Both models measure levels of deprivation encountered by a person, household, or a community. Deprivation can be measured in terms of a lack of resources for example, income, or capabilities skills, knowledge, technology, and assets. The World Health Organization defines poverty as when individual or household income is below what is needed for sustenance.
The World Bank identifies extreme poverty when per capita income is below the international poverty, which is currently set at $1.90 per day.
The United Nations defines extreme poverty as “a condition characterized by severe deprivation of basic human needs, including food, safe drinking water, sanitation facilities, health, shelter, education and information. It depends not only on income but also on access to services.”
Data sets used to compare poverty conditions in different countries are compiled at the next table. The students calculated the Multidimensional Poverty Index (in red). Also, the students reflected that “all the models are wrong, but some are useful”, a lesson I personally learned by the author, Dr. G.P. Box. See below the comparison for poverty conditions when using the USA’s Poverty Line and the Multidimensional Poverty Index for 2016.
USA’s Poverty Line and the Multidimensional Poverty Index for 2016.
The 2020 COARC-AIIS seminar gave me a unique lens to learn how India is supporting sustainability projects in some communities to reduce poverty and to reflect if poverty must be experienced/observed to be understood. Below are some photos taken during the CAORC-American Institute of Indian Studies Faculty Development Seminar: Exploring Urban Sustainability through India's Cities (Delhi - Lucknow - Japur). https://www.caorc.org/faculty-development-india
The Multidimensional Poverty Index considers 3 dimensions and 10 indicators as shown below.
About 120 million additional people are living in poverty because of the pandemic, with the total expected to rise to about 150 million by the end of 2021. The pandemic impact is higher in some regions than others. The next information is provided by the U.S. Census Bureau. Income, Poverty, and Health Insurance Coverage in the United States: 2021, and the worldbank.org. See below the global poverty’s regression.
COVID-19 pandemic has reversed the gains in global poverty for the first time in a generation.
Exploring the work of CAORC and AIIS with Sandria Freitag, Associate Teaching Professor in the Department of History at NC State University and leader of the CAORC-AIIS faculty development seminars; Maria del Carmen Paniagua, Associate Professor in the Math Department in Ivy Tech-Community College-Bloomington, Indiana; Mukila Maitha, Associate Professor of Geography, Department Chair, and Coordinator of both the Geographic Information Systems (GIS) and Drone Technology Program at Harper College; and Amar Sawhney, Professor of Architecture, Building Construction, and Interior Design and Miami Dade College alongside Jessica Barnes, senior lecturer in Geography at Northern Arizona University. AIIS - Summer 2021 Podcast
Dr. Paniagua, with support from Dr. Tavy Aherne at Indiana University, attended the Midwest Institute for International/Intercultural Education (MIIIE) Virtual 26 Annual Conference on November 5-6, 2021. She also made a presentation and shared some results on a newly developed math module.
Read more on this LinkedIn post.
Many thanks, also, to Dr. Martin Wolfger, Theo Sypris, and Fran Kubicek for their enthusiastic support of this project.
