BoS to measure poverty levels using multidimensional method

The Bureau of Statistics (BoS) is now better positioned to measure poverty levels in Guyana using the Multidimensional Poverty Index (MPI), with the training of several staff members.
This recently concluded hands-on capacity building exercise conducted at the Bureau’s headquarters in Georgetown was facilitated by the United Nations Development Programme (UNDP) and will see Guyana utilising this method for the first time.

Previously, measurement of poverty levels in Guyana by the Bureau was primarily done using the Consumption Expenditure method, which utilises data on household expenditure. Other agencies have also used the income method which relies on household income data. However, incomes are often understated and therefore not the most reliable metric for poverty measurement.
According to facilitator of the training exercise and the UNDP Multidimensional Poverty Specialist, Renata Pardo, the MPI method is a complementary one which examines other dimensions to poverty which are not covered by monetary measures.
These include school attendance, educational achievement, barriers of access to health services, unemployment, food insecurity and overcrowding in homes, among others.
While Guyana has a Multidimensional Poverty Index calculated at a global stage, the specialist explained that there are dimensions of poverty that are unique to each country. Ensuring that the participants of the training have a greater understanding of those dimensions was therefore a main aspect of the exercise.
This will now allow for the design and computation of the country’s first Multidimensional Poverty Index at a national level.
Meanwhile, Chief Statistician, Errol La Cruez highlighted the important role of the Bureau of Statistics in providing accurate, quality, and timely data and analysis that is vital for policy and decision makers to construct plans and interventions that reduce poverty, promote development and improve people’s quality of life.
Therefore, this training and the subsequent measurement of poverty using the MPI would be very useful to all stakeholders in identifying areas for development and tracking progress in this regard.