Battling Extreme Poverty in Bangladesh Part 1: The Measurement Problem

In 2010, the world reached its target for Millennium Development Goal 1 (MDG 1) five years ahead of schedule. MDG 1 aimed to halve by 2015 the proportion of people living in extreme poverty and hunger at the global level. According to the MDG Report 2013, many developing countries have reached their respective goals. Bangladesh is one of the 38 countries on this list.

MDG 1 uses the dollar-a-day standard (PPP) to measure extreme poverty, targeting those who survive on less than $1.25 per day. According to Bangladesh’s MDG Progress Report 2011, the percentage of the population living below this standard fell from 68.8 percent in 1992 to 49.6 percent in 2005.  The proportion living below the country’s own national poverty line of 2,122 kcal food consumption declined from 56.6 percent in 1992 to 31.5 percent in 2010.

However, these numbers may well be overrating Bangladesh’s success. They divert attention from a simultaneous increase in income inequality. The share of the poorest quintile in Bangladesh’s national income decreased from 6.5 percent in 1992 to 5.5 percent in 2010.The actual number of people living below the $1.25 poverty line has also increased from 40 million in 1981 to 77 million in 2005. Are the MDG poverty measurements misleading? Have antipoverty programs left certain groups behind? This article is part of a three-piece series that takes a deeper look at extreme poverty programming in Bangladesh. The series explores three main dimensions of these programs. They are: (i) the measurement problem; (ii) the government strategy problem; and (iii) the program sustainability problem.

Poverty measurement is an important, but somewhat overlooked problem in the development world. Measurement criteria determine to whom policies and programs target their services. Also, extreme poverty programs tend to be expensive. As many of these families suffer from complex challenges and vulnerabilities, they require comprehensive support packages and constant monitoring. Inappropriate measurement strategies lead to mistargeting, which not only deprives the poorest families, it also leads to a tremendous waste of program resources.

Poverty measurements for the MDG specifically suffer from two problems, that of universality and linearity. International poverty lines such as the dollar-a-day standard ease cross-national comparison. This universal measure allows researchers to compare the achievements of countries that are both institutionally diverse and geographically distant from each other. However, these very contextual differences also challenge the utility of a universal poverty line in accurately measuring poverty within a particular country. For example, differences in prices and inflation affect how far $1.25 would stretch for families in different circumstances and over time.

In Bangladesh, the Bangladesh Bureau for Statistics (BBS) initially drew two poverty lines based on caloric intake, at 1,805 calories and 1600 calories, which reflected the 85 percent and 75 percent of the absolute poverty line of 2,122 calories. However, Bangladesh’s national poverty line underestimates the actual level of poverty in two ways. In addition to hunger, poor households also suffer from chronic malnutrition. Therefore, BBS later implemented the Cost of Basic Needs (CBN) approach, which considers the quality of food intake and measures extreme poverty based on a necessary food basket of 11 items per household member. The MDGs measure extreme poverty by the former and not the latter.

In Bangladesh, national poverty lines also suffer from the problem of linearity; they assume that poverty is one-dimensional and derives from income-deprivation alone. However, poverty is multidimensional; it encompasses temporal and structural components. On the temporal front, a family’s poverty status can vary over time. Therefore, linear classifications erroneously identify these families as poor at one time and not at another. Many of Bangladesh’s poorest families suffer from chronic poverty, a long-term, often inter-generational form of poverty that Hulme and Shepherd identify as lasting for five years or more. These households may slide in and out of extreme poverty based on their attempts to overcome their conditions. Therefore, they fall into the extreme poverty bracket at certain times, but not at others. Linear poverty lines cannot capture poverty’s dynamic nature; therefore, they risk overlooking the chronic poor.

Poverty also encompasses a structural dimension. Extreme poverty is not only a problem of income; it is also a problem of access. The extreme poor lack access to many basic needs, including shelter, nutritious food, safe drinking water, sanitation, regular employment, health care, and education. During illness or emergencies, they have no access to health care. Many cannot seek or maintain regular employment due to ill-health or insufficient skills. They lack the capital and market access for entrepreneurial activities.

These multiple vulnerabilities set the extreme poor aside from other groups. Geof Wood argues that the more dimensions that deprive an individual, the lower their likelihood to escape poverty. In Bangladesh, the geographically marginalized lack access to capital and markets. Families from the southern coastal belts have trouble maintaining productive assets and growing food due to sea-level rise, natural calamities, and residual saline waters. Disabled and elderly populations often cannot engage in any income generating activity. Orphans and distressed children often suffer from psychological issues and access to basic schooling; many of these children end up on the streets.

Each sub group of the extreme poor faced different structural problems. Therefore, accurate identification of the poorest groups would require that studies identify the factors that put certain families in the corner of the market – that is, their specific disadvantage. For example, what skills and resources did they possess? What structural constraints did they face? For example, was the problem logistical? Were they disabled? Were they located in a char without regular market access? Did they lack the education and skills for successful entrepreneurship?

Poverty measurements also determine whom anti-poverty programs identify as their program beneficiaries. In Bangladesh, multiple poverty lines pose an additional problem of overlapping program identification criteria. Some development organizations had started to use structural measures to identify program beneficiaries. For example, the Targeting Ultra Poverty program of the development organization Brac uses a number of inclusion and exclusion criteria to identify participating households, such as ownership of less than 10 decimals of land, lack of productive assets, non-school going children and the absence of an active male member in the households, among others.

However, different organizations used their own definitions and classifications for poverty. A study by the NGO Brac found that many mid-level program staff identified extreme poverty based on their particular organization’s definitions, often based on the organization’s targeting methods for their own product. These structural factors can help create a new poverty measurement standard for Bangladesh. However, that would require lengthy and expensive research on the efficiency of these targeting methods. Development practitioners would rather spend these funds on actual programming purposes.

On the one hand, Bangladesh’s accomplishment in extreme poverty reduction deserves applause. However, the fact still remains that existing empirical data may obfuscate the exact degree of this achievement.  Because measurement standards also affect the targeting practices of programs, such mis-measurement may also hamper poverty reduction in the long run. Even by existing national poverty lines, over 30 percent of the population still suffers from hunger and malnutrition. Designing appropriate and relevant poverty measures is instrumental to identifying those left behind and addressing their vulnerabilities in a sustainable manner.