Americas fastest growing Petrostate, multi-dimensional poverty and hopeful signals for addressing poverty

Introduction

Today’s column introduces multi-dimensional measures of poverty in Guyana. I share the view that the best starting point for this topic, is through an introduction of the United Nations Human Development Report, UN, HDR and its Index HDI

As the UNDP states, the HDI is a “summary measure for assessing long-term progress in three basic dimensions of human development: a long and healthy life, access to knowledge and a decent standard of living.

Guyana’s HDI

Guyana’s HDI value for 2021 is cited as 0.714. This puts Guyana in the High, human development category. This also positions Guyana at 108 out of 191 countries and territories the UNDP assesses annually. Further, between 1990 and 2021, Guyana’s HDI value improved from 0.509 to 0.714, an improvement of 40.3 percent.

Undergirding this outcome, between 1990 and 2021, Guyana’s life expectancy at birth changed by 3.3 years; mean years of schooling changed by 3.3 years; and, expected years of schooling changed by 2.8 years. Guyana’s gross national income, GNI per capita, improved by about 996.3 percent between 1990 and 2021.

                The HDI is graded as follows:

                                        Low (< 0.550)

                                        Medium (0.550-0.699)

                                        High (0.700-0.799)

                                        Very high (≥ 0.800)

 

Multidimensional  Poverty Indices [MPIs]

As a rule, a number of indicators seek to capture in a summary figure poverty for a given population. Typically, this figure considers 1] the proportion of the population that is deemed poor, and 2] the ‘breadth’ of poverty experienced by ‘poor’ households. The approach is a response to critiques of dominant money and consumption-based poverty measures, poverty should capture non-monetary deprivations.

The Global Multidimensional Poverty Index (MPI) was developed in 2010 by the Oxford Poverty and Human Development Initiative, (OPHI) and the UNDP and uses health, education and standard of living indicators to determine the incidence and intensity of poverty experienced by a population.[5][6] It has since been used to measure acute poverty across over 100 developing countries.

UNDP Multidimensional Poverty Index 2023

The UNDP in its 2023 Report on multi-dimensional poverty in Guyana starts by raising the query, what is the global Multi-dimensional Poverty Index? In response it reminds us that the number 1 Sustainable Development Goal 1 is aimed at ending poverty both in all in all its forms, as well as everywhere.  Consequently, the global Multi-dimensional Poverty Index (MPI) focuses on measuring acute multi-dimensional poverty across more than 100 developing countries.

Further, it does so by measuring each person’s overlapping deprivations across 10 indicators in the same three equally weighted dimensions: of the HDI indicated above. That is, health, education and standard of living.

•             The health dimensions are based on two indicators, namely nutrition and child mortality. And the education is based on two also namely, years schooling and attendance. While standard of living is based on six indicators and therefore ten in all, namely

•             Nutrition

•             Child mortality

•             Years of schooling

•             School attendance

•             Cooking fuel

•             Sanitation

•             Drinking water

•             Electricity

•             Housing

•             Assets 

 

 All the indicators used to construct an MPI are from household surveys where 1]. each indicator is equally weighted within its dimension [so the health and education indicators are weighted 1/6 each] and 2] the standard of living indicators [weighted at 1/18 each]. Consequently, the MPI is the product of the headcount or incidence of multidimensional poverty (proportion of people who are multidimensionally poor) and the intensity of multidimensional poverty (average share of weighted deprivations, or average deprivation score, among multidimensionally poor people) and is therefore sensitive to changes in both components. A deprivation score of 1/3 (one-third of the weighted indicators) is used to distinguish between the multidimensionally poor and nonpoor. If the deprivation score is 1/3 or greater, the household (and everyone in it) is classified as multidimensionally poor. Individuals with a deprivation score greater than or equal to 1/5 but less than 1/3 are classified as vulnerable to multidimensional poverty. Finally, individuals with a deprivation score greater than or equal to 1/2 live in severe multidimensional poverty. The MPI ranges from 0 to 1, and higher values imply higher multidimensional poverty.

 The MPI complements the international US$2.15 a day poverty rate by identifying who is multidimensionally poor and also shows the composition of multidimensional poverty.

The most recent survey data that were publicly available for Guyana’s MPI estimation refer to 2019/2020. Based on these estimates, 1.8 percent of the population in Guyana (15 thousand people in 2021) is multidimensionally poor while an additional 6.5 percent is classified as vulnerable to multidimensional poverty (52 thousand people in 2021).

The intensity of deprivations in Guyana, which is the average deprivation score among people living in multidimensional poverty, is 39.3 percent. The MPI value, which is the share of the population that is multidimensionally poor adjusted by the intensity of the deprivations, is 0.007. In comparison, Belize and Suriname are 0.017 and 0.011 respectively.

Further, the headcount measure arrived at is 1.8 percent; the intensity of deprivation is 39.3; the vulnerability to multi-dimensional poverty is 6.5 percent and severe multi-dimensional poverty is 0.2 percent. And for the three components of multi-dimensional poverty; namely, health, education and standard of living their respective scores are 30.4, 22.4 and 47.0 percent.

Conclusion

Tis column wraps-up my consideration of poverty measurement, theorizing and policy prescription in Guyana, both by way of headcount-based survey methods going back to the 1990s, and their later transition to multi-dimensional methodologies not fixated on monetary variables.

Next week I elaborate on the policy approaches I recommend for persistent poverty in the Americas newest and fastest rising Petrostate.