Map of world poverty by country, showing percentage of population living on less than $1.25 per day. Information is based on different years (2000-2006) for different countries. Data is missing for countries colored grey.
World map showing life expectancy.
World map showing the HDI (Human Development Index)
World map of income inequality Gini coefficients by country (as %). Based on World Bank data ranging from 1992 to 2020.[1]
  •   Above 50
  •   Between 45 and 50
  •   Between 40 and 45
  •   Between 35 and 40
  •   Between 30 and 35
  •   Below 30
  •   No data
The percentage of the world's population living on less than $1 per day has halved in 20 years. Most of this improvement has occurred in East and South Asia. The graph shows the 1981–2001 period.
Life expectancy has been increasing and converging for most of the world. Sub-Saharan Africa has recently seen a decline, partly related to the AIDS epidemic. The graph shows the 1950–2005 period.

Poverty is measured in different ways by different bodies, both governmental and nongovernmental. Measurements can be absolute, which references a single standard, or relative, which is dependent on context. Poverty is widely understood to be multidimensional, comprising social, natural and economic factors situated within wider socio-political processes. The capabilities approach argues that capturing the perceptions of poor people is fundamental to understanding poverty.[2]

The main poverty line used in the OECD and the European Union is a relative poverty measure based on 60% of the median household income. The United States uses an absolute poverty measure based on the U.S. Department of Agriculture's "economy food plan", adjusted for inflation. The World Bank also defines poverty in absolute terms. It defines extreme poverty as living on less than US$1.90 per day.[3] (PPP), and moderate poverty as less than $3.10 a day.

It has been estimated that in 2008, 1.4 billion people had consumption levels below US$1.25 a day and 2.7 billion lived on less than $2 a day.

Absolute vs relative poverty

When measured, poverty may be absolute or relative. Absolute poverty refers to a set standard which is consistent over time and between countries. An example of an absolute measurement would be the percentage of the population eating less food than is required to sustain the human body (approximately 2000–2500 calories per day).

Another interpretation by the European Anti-Poverty Network reads:

[Absolute poverty] is when people lack the basic necessities for survival. For instance they may be starving, lack clean water, proper housing, sufficient clothing or medicines and be struggling to stay alive. This is most common in developing countries but some people in the European Union (EU), for instance homeless people or the Roma in some settlements, still experience this type of extreme poverty. [4]

Relative poverty, in contrast, views poverty as socially defined and dependent on social context. One relative measurement would be to compare the total wealth of the poorest one-third of the population with the total wealth of the richest 1% of the population. In this case, the number of people counted as poor could increase while their income rises. There are several different income inequality metrics; one example is the Gini coefficient.

Although absolute poverty is more common in developing countries, poverty and inequality exist across the world.

Measurements

The main poverty line used in the OECD and the European Union is a relative poverty measure based on "economic distance", a level of income usually set at 60% of the median household income.[4]

The United States, in contrast, uses an absolute poverty measure. The US poverty line was created in 1963–64 and was based on the dollar costs of the U.S. Department of Agriculture's "economy food plan" multiplied by a factor of three. The multiplier was based on research showing that food costs then accounted for about one-third of money income. This one-time calculation has since been annually updated for inflation.[5]

The U.S. line has been critiqued as being either too high or too low. For instance, The Heritage Foundation, a conservative U.S. think tank, objects to the fact that, according to the U.S. Census Bureau, 46% of those defined as being in poverty in the U.S. own their own home (with the average poor person's home having three bedrooms, with one and a half baths, and a garage).[6] Others, such as economist Ellen Frank, argue that the poverty measure is too low as families spend much less of their total budget on food than they did when the measure was established in the 1950s. Further, federal poverty statistics do not account for the widely varying regional differences in non-food costs such as housing, transport, and utilities.[7]

Both absolute and relative poverty measures are usually based on a person's yearly income and frequently take no account of total wealth. Some people argue that this ignores a key component of economic well-being. Major developments and research in this area suggest that standard one dimensional measures of poverty, based mainly on wealth or calorie consumption, are seriously deficient. This is because poverty often involves being deprived on several fronts, which do not necessarily correlate well with wealth. Access to basic needs is an example of a measurement that does not include wealth. Access to basic needs that may be used in the measurement of poverty are clean water, food, shelter, and clothing.[8][9] It has been established that people may have enough income to satisfy basic needs, but not use it wisely. Similarly, extremely poor people may not be deprived if sufficiently strong social networks, or social service systems exist.[10] For deeper discussions, see also the Wikipedia article on Multidimensional poverty.

Indicators

Indicator income

Benefits:

  1. Easy to measure (normally less incomes than expenditure)
  2. Measures degree control over finance of household
  3. Cheaper collecting of data

.. Help in the allocation of resources by the government

Disadvantages:

  1. Probably income will be underreported
  2. May be affected by short-term fluctuations (for example, the seasonal works), so reporting period might not catch right information
  3. Some parts of income are hard to survey (self-home production or self-employment income)
  4. Link between income and welfare can be confusing[11]

Indicator expenditure

Benefits:

  1. Report actual material standard of living.
  2. For long term measuring is better and more precisely
  3. Less understated so expenditures are easier to recall

Disadvantages:

  1. Consumption of household could be unevenly (for example borrowing money)
  2. Consumption choices couldn't be rational. People who spend less, could save or live humbly
  3. Data could be damaged, because of untruly information
  4. Difficult to measure durable goods in some period of research.[11]

Non-monetary indicators

Some economists, such as Guy Pfeffermann, say that other non-monetary indicators of "absolute poverty" are also improving. Life expectancy has greatly increased in the developing world since World War II and is starting to close the gap to the developed world where the improvement has been smaller. Even in Sub-Saharan Africa, the least developed region, life expectancy increased from 30 years before World War II to a peak of about 50 years — before the HIV pandemic and other diseases started to force it down to the current level of 47 years. Child mortality has decreased in every developing region of the world.[12] The proportion of the world's population living in countries where per-capita food supplies are less than 2,200 calories (9,200 kilojoules) per day decreased from 56% in the mid-1960s to below 10% by the 1990s. Between 1950 and 1999, global literacy increased from 52% to 81% of the world. Women made up much of the gap: Female literacy as a percentage of male literacy has increased from 59% in 1970 to 80% in 2000. The percentage of children not in the labor force has also risen to over 90% in 2000 from 76% in 1960. There are similar trends for electric power, cars, radios, and telephones per capita, as well as the proportion of the population with access to clean water.[13]

Other Measures of Household Welfare

Even if income and expenses are measured perfectly, none of these measures show well-being objectively. For example, it includes leisure, public goods, health care, education and even peace and security. One criterion is the consumption of calories per person. According to this criterion, we can see what percentage of the population suffers from hunger. Although the average limit is around 2,100 calories, it still varies from person to person. It depends on age, gender, etc. What percentage of income do we spend on food consumption? Research shows that the more developed a country, the smaller the budget we spend on food. The disadvantage of this scale is that people differ relatively in the quality of food and it is consumption per person. Measuring results rather than inputs. Rather than the amount of food, we should focus on the anthropometric state (underweight, etc.). This measurement really shows the quality of the household. However, it cannot be used for comparisons between states or continents, because nationalities differ in scale. The last idea of how to assess poverty is up to the decision among citizens. In Vietnam, for example, some villages are judged by the people themselves, who need help out of poverty. Although this simple solution works somewhere, it is very often distorted by various influences. In short, there is as yet no ideal measure for the well-being of the population. This is not an argument to end the measurement, but rather a warning to minimize errors and take into account as many factors as possible.[11]

Definitions

The World Bank defines poverty in absolute terms. The bank defines extreme poverty as living on less than US$1.90 per day.[3] (PPP), and moderate poverty as less than $3.10 a day. It has been estimated that in 2008, 1.4 billion people had consumption levels below US$1.25 a day and 2.7 billion lived on less than $2 a day. The proportion of the developing world's population living in extreme economic poverty has fallen from 28 percent in 1990 to 21 percent in 2001. Much of the improvement has occurred in East and South Asia. In Sub-Saharan Africa GDP/capita shrank with 14 percent, and extreme poverty increased from 41 percent in 1981 to 46 percent in 2001. Other regions have seen little or no change. In the early 1990s the transition economies of Europe and Central Asia experienced a sharp drop in income. Poverty rates rose to 6 percent at the end of the decade before beginning to recede.[14] There are criticisms of these measurements.[15]

Common Poverty metrics

Headcount index

Headcount index (Po) is a widely-used measure, which simply indicates the proportion of the poor population. Although it does not indicate how poor the poor are.

Formula: , where Np is the number of poor and N is the total population.

Example: If 10 people are poor in a survey that samples 1000 people, then Po = 10/1000 = 0.01 = 1%

Its often helpful to rewrite:

, Here, I(·) is an indicator function that takes on a value of 1 if the bracketed expression is true, and 0 otherwise. So if expenditure (yi) is less than the poverty line (z), then I(·) equals 1 and the household would be counted as poor.

This index is easy to understand, but has few disadvantages. It does not show the poverty rate. In addition, the headcount index does not show how poor the poor are. Moreover, this estimate is made on households and not on individuals.[16]

Poverty gap index (P1)

The Poverty gap index is the mean distance below the poverty line as a proportion of the poverty line where the mean is taken over the whole population, counting the non-poor as having zero poverty gap.

Using the index function, we have: , where define the poverty gap (Gi) as the poverty line (z) less actual income (yi) for poor individuals; the gap is considered to be zero for everyone else.

Could be rewrite:

The poverty gap index denotes the extent to which individuals fall below the poverty line (poverty gap) as a proportion of the poverty line. By summing these poverty gaps we derive the minimum cost of eliminating poverty.[17]

This method is only reasonable if the transfers could be made perfectly efficiently, which is unlikely.[16]

Squared Poverty Gap Index (Poverty severity index, P2)

The squared poverty gap index is conducted by averaging the squares of the poverty gaps relative to the poverty line. This measure emphasizes extreme poverty and gives it a greater weight than less poverty. One of its benefits is the possibility of variation in the weight of income level of the poorest part of society. The Poverty severity index can also be disaggregated for population subgroups.[17]

Sen index

The Sen index connects the number of poor with the size of their poverty and the distribution of poverty in the sample.[16]

Sen-Shorrocks-Thon Index

The Sen-Shorrocks-Thon index (sometimes referred to as SST index) is an improved version of the Sen index.[16]

The Sen-Shorrocks-Thon index takes into perspective measures of the proportion of poor people, the extent of their poverty and the distribution of welfare among the poor. This index enables us to decompose poverty into three components and answer these questions: Are there more poor? Is their depth of poverty worsening? Is there higher inequality among the poor?[17]

Asset-based measures

Other point of view defines poverty and in terms of assets. These asset-based measures may consider the real financial asset holdings, access to the credit market and poverty related to a household’s wealth. An example of those may be income net worth measures, asset-poverty and financial vulnerability.

Being asset poor does not imply being income poor and vice versa. For example, the importance of being asset wealthy is lower in countries with secure employment as it ensures stable living standards, while in other countries it may be needed as a cushion against uncertainties and shocks. [18]

High-frequency poverty measures

Real-time information on poverty and people’s well-being has not been yet well developed. There has already been and incentive to conduct a few pilot projects with the help of mobile phones by the World Bank in South Soudan,[19] Peru or Tanzania.[20]

Supplemental and Official Measures in the USA

The Official Poverty Measure takes into account the individual’s of family’s pretax cash income and a size and age varied set of thresholds but is not effected by in-kind programs (e.g. housing and energy programs, nutrition assistance), tax credits or the regional differences in living costs.[21]

In order of better understanding of the economic well-being of American families and easier interpretation of effectiveness of federal policies, the Supplemental Poverty Measure (SPM) was developed by the Census Bureau and the U.S. Bureau of Labor Statistics in 2010. In the next few years several new methodological improvements were made to SPM. The SPM does take into consideration family resources and expenses not included in the OPM and the geographical conditions.[21]

The demographic profile of the poverty population differs under the SPM and OPM measures. Comparatively, the poverty rate of children is lower in terms of SPM and a higher poverty rate is conducted among the elderly (older than 65). The poverty rate of the working-age population fluctuates from year to year between the two poverty measures. The Supplemental Poverty Measure highlights medical and work-related expenses compared to the Official Poverty Measure and gives policymakers clearer picture of the outcome of government programs.[22]

Case Studies

Measuring poverty is a complex and comprehensive task requiring various methods and approaches. Case studies can provide insights into real-world examples and examples of how poverty is measured and addressed. This section examines four case studies showcasing the diverse techniques for measuring poverty, including the Multidimensional Poverty Index (MPI) in Mexico, the Community-Led Total Sanitation (PAMSIMAS) approach in Indonesia, and the National Rural Employment Guarantee Act (NREGA) in India. Examining these case studies can provide a deeper understanding of how poverty is assessed and addressed globally.

Multidimensional Poverty Index (MPI)

The Multidimensional Poverty Index (MPI) in Mexico is a comprehensive approach to assessing poverty that considers a variety of indicators beyond just income. Mexico was the first country to introduce an official multidimensional poverty measure, an index which, in addition to considering the lack of economic resources, includes other dimensions that social policy must address. The National Council developed the MPI in Mexico for the Evaluation of Social Development Policy (CONEVAL), which is the agency responsible for evaluating poverty and social policy in Mexico.[23]

The MPI in Mexico measures poverty on eight poverty indicators: income, education lag, access to healthcare services, access to social security, access to food, housing quality, and space, access to basic housing requirements, and degree of social cohesion. The measurement considers income and six dimensions in a social rights approach. It is complemented by the inclusion of social cohesion, recognising the importance of contextual and relational factors, which may be analysed in terms of their impact on society and vice-versa.[23]

The MPI considers various factors contributing to poverty and deprivation, offering a more complex understanding of poverty than traditional income-based measurements. The Mexican government uses it to track progress in eradicating poverty over time and target social services and policies to those most in need. Every two years, the national and state governments in Mexico measure poverty. Municipalities measure poverty every five years.

Mexico's MPI has been a helpful instrument for assessing poverty and promoting social progress. Nonetheless, it has its drawbacks and critics, just like any method of measuring poverty. Several opponents contend that the MPI understates the severity of the poverty and marginalisation of particularly marginalised groups, such as indigenous peoples and residents of rural areas. Nonetheless, the Multidimensional Poverty Measure in Mexico is a valuable model for other countries trying to develop comprehensive and multidimensional perspectives to measuring poverty.

Community-Based Drinking Water Supply and Sanitation Program

Community-based Drinking Water Supply and Sanitation Program or Penyediaan Air Minum dan Sanitasi Berbasis Masyarakat (PAMSIMAS) approach in Indonesia is an excellent example of measuring poverty since it acknowledges how poor sanitation impacts general health conditions and their social and economic aspects. [24] The PAMSIMAS approach motivates individuals to participate in community development by integrating themselves into identifying and fixing their sanitation problems. As a result, the PAMSIMAS approach offers a comprehensive approach to reducing poverty, considering income and assets and the more extensive social and environmental variables contributing to measuring poverty.

This approach is founded on the idea that local communities are more suited to identify and handle their sanitation requirements than traditional top-down approaches to development. This method involves working with communities to identify practices that lead to poor sanitation, such as open defecation, and promote awareness of the necessity of sanitation. In addition to technical assistance to strengthen the community's role through capacity building, planning, procurement, and management, including community monitoring with a web-based and mobile monitoring system, the project offers grants directly to communities for local water and sanitation infrastructure. Facilitators and districts are also given access to training and consulting services to help them develop better sanitation and hygiene habits. Then, the facilitators assist communities in creating options for further development.[25]

The PAMSIMAS approach in Indonesia has successfully reduced open defecation and improved access to sanitation facilities in rural areas. According to the World Bank,[24] the percentage of communities targeted for available defecation-free status increased significantly from 0% to 58%, and roughly 81% of those schools improved their sanitation and hygiene initiatives. For instance, the institutional sustainability of the PAMSIMAS approach also became more assertive, with 97% of districts replicating it outside of the project's target neighborhoods and 86% of communities increasing their spending on ensuring everyone has access to clean water and sanitation.

National Rural Employment Guarantee Act (NREGA)

In 2005, India launched a national-anti poverty program, Mahatma Gandhi National Rural Employment Guarantee Act (NREGA). It is a flagship program of the Indian government to provide employment opportunities to rural households in the country. The scheme was launched in 2005, and it guarantees 100 days of wage employment to every rural household that demands work.[26]

The NREGA is a demand-driven program, meaning that households must apply for work under the scheme. The government is then obligated to employ within 15 days of the application. The scheme offers a minimum wage for workers, set by the central government, and varies from state to state.

The NREGA is intended to give rural households work opportunities during the slow agricultural season when those opportunities are few. The program attempts to decrease poverty and raise rural income by hiring rural households. The program also intends to encourage sustainable development in rural areas by creating job opportunities in forestry, water conservation, and infrastructure building.

Nonetheless, the NREGA has been widely recognised as an effective tool for poverty reduction and rural development in India. In 2020, the scheme was extended to cover 116 districts affected by the COVID-19 pandemic, providing much-needed employment opportunities to vulnerable households in rural areas.[27]

In conclusion, the NREGA is a significant social welfare program in India that provides employment opportunities to rural households, promotes social inclusion and contributes to rural development. While the scheme has challenges, its positive impact on poverty reduction and rural development must be considered.

Common survey problems

These surveys interpret data that has some common problems:

Random sample: All research is based on randomly selecting people into a sample, and each should have the same chance of being selected. Unfortunately, it is not easy for the sample not to be biased, because some groups of people are simply difficult to trace.

Sampling: We can see inequalities from experience and from surveys themselves. Surveys show us only an estimated formula. Another thing we should be interested in is how the sampling was performed. In areas with dense population, there is usually under-sampling.

Goods Coverage and Valuation: To cover and refine the information, we should ask the sample more generally. Not only the issues of income and expenditure are enough, but also own consumption from the family farm. It is necessary to gather information on housing and components of durable consumption.

Variability and the Time Period of Measurement: Income, consumption and other factors change over time. In less developed countries, therefore, the focus is only on consumption, which is more stable from income.

Comparisons across Households at Similar Consumption Levels: Comparisons between households are difficult because households differ not only in the size of income and expenditure, but also in the environment, leisure, quality of the environment, etc.[11]

Stats

Even if poverty may be lessening for the world as a whole, it continues to be an enormous problem:

  • One third of deaths — some 18 million people a year or 50,000 per day — are due to poverty-related causes. That's 270 million people since 1990, the majority women and children, roughly equal to the population of the US.
  • Every year nearly 11 million children die before their fifth birthday.
  • In 2001, 1.1 billion people had consumption levels below $1 a day and 2.7 billion lived on less than $2 a day.
  • 800 million people go to bed hungry every day.[28]

Other factors

The World Bank's Voices of the Poor initiative,[29] based on research with over 20,000 poor people in 23 countries, identifies a range of factors that poor people consider elements of poverty. Most important are those necessary for material well-being, especially food. Many others relate to social rather than material issues.

  • precarious livelihoods
  • excluded locations
  • gender relationships

Future Directions

Future directions in measuring poverty are constantly changing as new discussions and trends take hold in the field of study. In developing the matrices, multidimensional poverty measurements and including subjective well-being indicators are prominent areas.

For example, multidimensional metrics are recognised to consider various perspectives to fully understand the poverty, for example, the approach takes into accounts of various factors such as health, education, access to basic services, social and economic empowerment, and environmental conditions.[30] Governments can create policies and implementations based on this comprehensive manner in studying the underlying causes of poverty.

In cooperation with United Nations Development Programme, the Oxford Poverty and Human Development Initiative (OPHI) developed the Multidimensional Poverty Index (MPI) in 2010. The index employs a collective indicators including health, education, and standard of living, using ten indicators such as nutrition, years of schooling, and access to clean water and electricity.

Another area of emerging debate is the incorporation of subjective measures which are designed to record people's perceptions of their own well-being, which can offer valuable information into the impact of poverty on people's lives in way other than material deprivation. An example of subjective poverty measurement is the Participatory Wealth Ranking (PWR) approach that uses the ratings of local reference groups concerning the relative poverty status of households in their community. [31]

References

  1. ↑ "Gini index (World Bank estimate)". data.worldbank.org. Retrieved 2022-04-23.
  2. ↑ Sen, Amartya (1999). Development as Freedom. OUP. ISBN 0-19-289330-0.
  3. 1 2 "New Data Show 1.4 Billion Live On Less Than US$1.25 A Day, But Progress Against Poverty Remains Strong". worldbank.org/. The World Bank. Retrieved 13 March 2015.
  4. 1 2 "Poverty and Inequality in the European Union - the Poverty Site". Archived from the original on 2007-11-23. Retrieved 2011-10-10.
  5. ↑ US Department of Human Services, FAQ Poverty Guidelines and Poverty
  6. ↑ Rector, Robert E. and Johnson, Kirk A., Understanding Poverty in America, Executive Summary, Heritage Foundation, January 15, 2004, No. 1713
  7. ↑ Frank, Ellen, "Dr. Dollar: How Is Poverty Defined in Government Statistics?" Dollars & Sense magazine, January/February 2006. Accessed April 13, 2008
  8. ↑ "Measuring Poverty - Poverty is defined by deprivation, and can be measured with economic or social indicators". boundless.com. Archived from the original on 2 April 2015. Retrieved 12 March 2015.
  9. ↑ Pogge, Thomas. "Measuring Poverty". thomaspogge.com/. Archived from the original on 29 January 2016. Retrieved 12 March 2015.
  10. ↑ Thorbecke, E., 2008. Multidimensional Poverty: Conceptual and Measurement Issues. In: Kakwani, N., Silber, J. (Eds.), The Many Dimensions of Poverty. Palgrave Macmillan, New York, pp. 3–20
  11. 1 2 3 4 "Handbook on Poverty and Inequality" (PDF).
  12. ↑ The Eight Losers of Globalization Archived 2008-05-01 at the Wayback Machine by Guy Pfeffermann. Pfeffermann, former Chief Economist of the International Finance Corporation, is the CEO of Global Business School Network. This is a non-profit organization supporting business and management education in the developing world. 2002.
    It is an area where not only is there little or no consensus among disciplines, but where economists themselves have widely differing views. So, what can one say with a fair degree of certainty about growth and inequality in developing countries? Life expectancy at birth — the most basic and robust of all social indicators — has increased very considerably around the world.
  13. ↑ www.sciencedirect.org
  14. ↑ Worldbank.org reference
  15. ↑ TFF, 1999
  16. 1 2 3 4 "Poverty Manual, Chapter 4" (PDF).
  17. 1 2 3 Handbook on Poverty and Inequality. The World Bank. 2009-03-27. doi:10.1596/978-0-8213-7613-3. ISBN 978-0-8213-7613-3.
  18. ↑ Brandolini, Andrea; Magri, Silvia; Smeeding, Timothy M. (2009). "Asset-Based Measurement of Poverty". SSRN Electronic Journal. doi:10.2139/ssrn.1537822. ISSN 1556-5068.
  19. ↑ Pape, Utz; Parisotto1, Luca (January 2019). "Estimating Poverty in a Fragile Context – The High Frequency Survey in South Sudan" (PDF). World Bank Group.{{cite web}}: CS1 maint: numeric names: authors list (link)
  20. ↑ National Bureau of Statistics. "Tanzania - High Frequency Welfare Monitoring Phone Survey 2021". doi:10.48529/fbpn-x230. TZA_2021_HFWMPS_v01_M. Retrieved 2023-03-31 – via microdata.worldbank.org.
  21. 1 2 Bureau, US Census. "What's the Difference Between the Supplemental and Official Poverty Measures?". The United States Census Bureau. Retrieved 2023-04-02.
  22. ↑ "The Supplemental Poverty Measure: Its Core Concepts, Development, and Use".
  23. 1 2 Consejo Nacional de Evaluacion de la Politica de Desarrollo Social, (CONVEAL) (2010). "Multidimensional Measurement of poverty in Mexico: an economic wellbeing and social rights approach".
  24. 1 2 "Indonesia: Expanding Access to Clean Water for the Rural Poor". World Bank. Retrieved 2023-04-06.
  25. ↑ "Second Review of Community-Led Total Sanitation in the East Asia and Pacific Region (December 2015)" (PDF) (Regional Report). UNICEF EAPRO East Asia and Pacific Regional Office. 2016.
  26. ↑ Impact of Mahatma Gandhi National Rural Employment Guarantee Scheme on child labour. New Delhi: International Labour Office, International Programme on the Elimination of Child Labour, ILO DWT for South Asia and Country Office for India. 2013. ISBN 978-92-2-127188-8. OCLC 1368766663.
  27. ↑ Vasudevan, Gayathri; Singh, Shanu; Gupta, Gaurav; Jalajakshi, C. K. (2020-09-08). "MGNREGA in the Times of COVID-19 and Beyond: Can India do More with Less?". The Indian Journal of Labour Economics. 63 (3): 799–814. doi:10.1007/s41027-020-00247-0. ISSN 0971-7927. PMC 7478243. PMID 32921943.
  28. ↑ "millenniumcampaign.org". Archived from the original on 2006-12-09. Retrieved 2007-01-14.
  29. ↑ "Voices of the Poor". worldbank.org. The World Bank. Retrieved 13 March 2015.
  30. ↑ Alkire, Sabina; Santos, Maria Emma (2014-07-01). "Measuring Acute Poverty in the Developing World: Robustness and Scope of the Multidimensional Poverty Index". World Development. 59: 251–274. doi:10.1016/j.worlddev.2014.01.026. hdl:11336/2085. ISSN 0305-750X.
  31. ↑ Zeller, Manfred; Feulefack, Joseph; Neef, Andreas (2006). "How Accurate is Participatory Wealth Ranking (PWR) in Targeting the Poor? A Case Study from Bangladesh".
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