Indicator: 1.2.2

0.a. Goal

Goal 1: End poverty in all its forms everywhere

0.b. Target

Target 1.2: By 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions

0.c. Indicator

Indicator 1.2.2: Proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions

0.d. Series

Not applicable

0.e. Metadata update

2023-03-31

0.f. Related indicators

Not applicable

0.g. International organisations(s) responsible for global monitoring

The World Bank, United Nations Children’s Fund (UNICEF), United Nations Development Programme (UNDP)

1.a. Organisation

The World Bank, United Nations Children’s Fund (UNICEF), United Nations Development Programme (UNDP)

2.a. Definition and concepts

Definition:

The following five series are used to monitor the SDG 1.2.2.

1) Official multidimensional poverty headcount, by sex, and age (% of population)

The percentage of people who are multidimensionally poor

2) Average share of weighted deprivations (intensity) for total population

The average share of weighted dimensions in which poor people are deprived among total population

3) Official multidimensional poverty headcount (% of total households)

The percentage of households who are multidimensionally poor

4) Average share of weighted deprivations (intensity) for total households

The average share of weighted dimensions in which poor people are deprived among total households

5) Multidimensional deprivation for children (% of population under 18)

The percentage of children who are simultaneously deprived in multiple material dimensions

Concepts:

The design of a measure of multidimensional poverty is different in each country, but regardless of the exact methodology selected, it still follows a similar process to define the features of the measure, which include: i) the purpose of the measure; ii) the unit of identification (most frequently either the household or the individuals); iii) the dimensions and respective indicators that delimit which deprivations should be measured; iv) the methodology for developing the measure (including deprivation cut-offs, weights, and poverty cut-offs).

The most commonly used method is the Alkire Foster (AF) methodology which identifies dimensions, typically health, education and living standards and several indicators in each dimension. The unit of analysis could be either the individual or the household. The individuals or households are considered as multidimensionally poor if they are deprived in multiple dimensions, exceeding certain thresholds.

EU Member States, Island, Norway, Albania, Kosovo, North Macedonia, Montenegro and Turkey have a different approach to measure the multidimensional poverty using the concept of "people at risk of poverty or social exclusion" (AROPE) calculated by EUROSTAT using the data from EU statistics on income and living conditions (EU-SILC). AROPE consists of three components, and individuals are considered as "at risk of poverty or social exclusion" if they are "at risk of poverty" or "severely materially and socially deprived" or "living in a household with a very low work intensity". ^[1]

There is a multidimensional poverty measure specifically designed for children. A child is considered multidimensionally poor if s/he is simultaneously deprived in multiple dimensions. It identifies the dimensions of poverty and the indicators under each dimension, and has a similar structure to the AF methodology. However, it is different in that it focuses on the life-cycle of children, creating different sets of dimensions and indicators for different age groups (e.g., for ages 0-4, 5-11, 12-14, 15-17 years), and conducts analyses separately for each age group. In the global SDG database, the multidimensional poverty headcount (%) for the overall 0-17 age group has been used for countries reporting individual measures of child multidimensional poverty.

For more information please see Eurostat’s definitions https://ec.europa.eu/eurostat/statistics-explained/index.php?title=EU_statistics_on_income_and_living_conditions_(EU-SILC)_methodology_-_people_at_risk_of_poverty_or_social_exclusion. ↑

2.b. Unit of measure

Percent (%)

2.c. Classifications

Not applicable

3.a. Data sources

Data sources used for calculating indicators differ from survey to survey in each country. For details, please refer to the official documentation through the links listed at the end.

3.b. Data collection method

Data collection methods used for calculating indicators differ from survey to survey in each country. For details, please refer to the official documentation through the links listed at the end.

3.c. Data collection calendar

The timing of the data collection differs from survey to survey in each country. For details, please refer to the official documentation through the links listed at the end.

3.d. Data release calendar

EU countries and some Latin American countries conduct the survey and produce multidimensional indicators every year, but most of the developing countries have published multidimensional measurement only once or a few times in the last 10 years. For these countries, it is difficult to state definitely when the next data is available.

3.e. Data providers

Following is the list of national data providers responsible for producing the data at the national level.

Table 1: List of national data providers

Country	Source
Afghanistan	National Statistics and Information Authority (NSIA)
Albania	EUROSTAT
Angola	National Statistics Institute (INE) of Angola
Armenia	Statistical Committee of Republic of Armenia
Austria	EUROSTAT
Belgium	EUROSTAT
Bhutan	National Statistics Bureau
Bulgaria	EUROSTAT
Burundi	Burundi Institute of Statistics and Economic Studies
Chile	Ministerio de Desarrollo Social
Colombia	National Administrative Department of Statistics (DANE)
Costa Rica	The National Institute of Statistics and Census of Costa Rica
Croatia	EUROSTAT
Cyprus	EUROSTAT
Czechia	EUROSTAT
Denmark	EUROSTAT
Dominican Republic	Ministry of Economy, Planning and Development
Ecuador	National Institute of Statistics and Census (INEC), Ministry of Social Development Coordination and National Secretary of Planning and Development
Egypt	The Ministry of Social Solidarity (MoSS), the Central Agency for Public Mobilization and Statistics (CAPMAS)
El Salvador	Secretaría Técnica y de Planificación Presidencia
Estonia	EUROSTAT
Finland	EUROSTAT
France	EUROSTAT
Germany	EUROSTAT
Ghana	Ghana Statistical Service, National Development Planning Commission
Greece	EUROSTAT
Guatemala	Ministry of Social Development
Guinea	INSTITUT NATIONAL DE LA STATISTIQUE
Guinea Bissau	La Direction Generale du Plan, Instituto Nacional de Estatística (INE)
Hungary	EUROSTAT
Iceland	EUROSTAT
Ireland	EUROSTAT
Italy	EUROSTAT
Kosovo	EUROSTAT
Latvia	EUROSTAT
Lesotho	Bureau of Statistics
Lithuania	EUROSTAT
Luxembourg	EUROSTAT
Malawi	National Statistical Office
Malaysia	Department of Statistics Malaysia
Maldives	National Bureau of Statistics (NBS)
Mali	Institut National de la Statistique (INSTAT), La Cellule Technique de Coordination du Cadre Stratégique de Lutte contre la Pauvreté (CT-CSCLP)
Malta	EUROSTAT
Mexico	Consejo Nacional de Evaluacion de la Politica de Desarrollo Social (CONEVAL)
Montenegro	EUROSTAT
Morocco	The High Commission of Planning
Mozambique	Ministry of Economics and Finance - Directorate of Economic and Financial Studies
Namibia	Namibia Statistics Agency (NSA)
Nepal	National Planning Commission
Netherlands	EUROSTAT
Nigeria	National Bureau of Statistics
North Macedonia	EUROSTAT
Norway	EUROSTAT
Pakistan	Ministry of Planning Development & Reform
Palestine	The Palestinian Central Bureau of Statistics (PCBS)
Panama	(2017) Ministry of Social Development (2018) Ministry of Economy and Finance
Philippines	Philippine Statistics Authority
Poland	EUROSTAT
Romania	EUROSTAT
Rwanda	National Institute of Statistics of Rwanda
Saint Lucia	The Central Statistical Office of Saint Lucia
São Tomé and Príncipe	Ministry of Economy and International Cooperation
Serbia	EUROSTAT
Seychelles	National Bureau of Statistics
Slovakia	EUROSTAT
Slovenia	EUROSTAT
South Africa	Statistics South Africa
Spain	EUROSTAT
Sri Lanka	Department of Census and Statistics
Sweden	EUROSTAT
Thailand	National Economic and Social Development Council (NESDC)
Turkey	EUROSTAT
Uganda	Uganda Bureau of Statistics
Vietnam	General Statistics Office
Zambia	Ministry of National Development Planning
Zimbabwe	Zimbabwe National Statistics Agency (ZIMSTAT)

3.f. Data compilers

The World Bank, United Nations Children’s Fund (UNICEF), and United Nations Development Programme (UNDP)

3.g. Institutional mandate

The UN Statistical Commission has adopted Guidelines on Data Flows and Global Data Reporting for the SDGs, which aim to establish efficient and transparent mechanisms for reporting on SDG data from national to international levels. The guidelines define a framework for national and international agencies to work together to improve the transmission and validation of SDG data at the global level.

The Statistical Commission sets these guidelines under the overarching Fundamental Principles of Official Statistics and the Principles Governing International Statistical Activities, emphasizing in particular the principles of transparency, collaboration and communication, and professional and ethical standards.

The guidelines mandate that SDG indicators be based on data produced and owned by national statistical systems, and that national statistical offices (NSOs) play a central coordinating role in the reporting process. The guidelines outline the roles and responsibilities of entities involved in the compilation of SDG data for global reporting, including NSOs, other national institutions, and international organizations.

At the national level, the NSO, as coordinator of the National Statistical System, is expected to identify a national data provider for each indicator and liaise between national entities and international custodian agencies. For SDG Indicator 1.2.2, the data provider would be the national entity that is leading the development and monitoring of a measure of national multidimensional poverty recognized as official by the government.

At the global level, custodian agencies are mandated to compile national SDG indicator data, to harmonize it to ensure quality, international comparability and the computation of regional aggregates, and to report (upload) the data to the Global SDG Indicator Database. In many instances, custodian agencies also support the methodological development of indicators and provide technical assistance to under-resourced national statistical systems. Custodian agencies are expected to publish a timeline of data collection activities, to ensure transparency and sufficient time for NSOs and national data providers to respond to requests for SDG data.

SDG 1.2.2 is different from other SDG indicators in two important ways. Firstly, it is nationally defined and not a uniform measure across countries, and therefore it is not internationally comparable. Secondly, its custodians are NSOs and not international agencies. Because of these characteristics, UNDP, UNICEF and the World Bank collaborate as special partner agencies to provide a platform for compiling national SDG 1.2.2 data and reporting it to the global SDG database, a function typically performed by custodian agencies. While the special partner agencies strive to ensure that reported data is official and of good quality, they do not perform any harmonization or other processing of the data. The Guidelines on Data Flows and Global Data Reporting for the SDGs also require that national metadata be submitted at the same time as SDG data, to ensure accuracy and international comparability. The variety of methodologies for SDG Indicator 1.2.2 increases the relevance of national metadata as an instrument to ensure high quality and the accuracy of reported data. The three agencies also have extensive portfolios of technical assistance and capacity support to countries for the development of their national measures of multidimensional poverty.

4.a. Rationale

Poverty has traditionally been defined as the lack of money. However, the poor themselves consider their experience of poverty much more broadly. A person who is poor can suffer multiple disadvantages at the same time – for example, they may have poor health or malnutrition, a lack of clean water or electricity, poor quality of work or little schooling. Focusing on one factor alone, such as income, is not enough to capture the true reality of poverty. Therefore, multidimensional poverty measures described above have been developed to create a more comprehensive picture by looking at multiple dimensions such as health, education, living standards. Official multidimensional poverty headcount (% population), official multidimensional poverty headcount (% of total households) and multidimensional deprivation for children (% of population under 18) are all about the headcount ratio trying to capture how many people, households, or children in the entire pool are regarded as multidimensionally poor. On the other hand, average share of weighted deprivation tries to capture the depth of multidimensional poverty. For instance, if there are 18 indicators to capture different dimensions of poverty, the person who is deprived in 5 indicators, and the person who is deprived in 15 indicators are considered to be both multidimensionally poor. However, the 'intensity' of the poverty is different between these two people, which is captured by the average share of weighted deprivation.

4.b. Comment and limitations

The compiled data of SDG 1.2.2 is not intended to be comparable across countries due to national definitions. For instance, key parameters to calculate the measure such as the number of indicators, the weight allocated to each indicator etc, are tailored to the country specific context.

4.c. Method of computation

The measurement of poverty involves two crucial steps: (1) identification – identifying who is poor, and (2) aggregation – compiling the individual’s information into a summary measure. There are different ways to perform these two steps. All measures currently being estimated by countries or multilateral organizations use the counting approach. Therefore, what follows relates only to counting approaches, even if other non-counting methodologies have been developed by experts.

The identification and aggregation of the multidimensionally poor involves the following steps:

Define the set of relevant dimensions of poverty, and for each of these define a set of indicators.
For each dimension, determine the criteria to assess deprivation based on the indicators.
For each indicator, define a satisfaction threshold, such that a person (or household) with an achievement below the threshold will be identified as deprived in that indicator.
For each indicator, compare each person’s (or household’s) achievement with the satisfaction threshold and create a variable that assumes, for example, the value 1 if the person is deprived in that indicator and 0 otherwise, and then classify them as either deprived or not in that indicator.
For each individual (or household), sum up the number of deprivations. In the summation, each indicator can be weighted differently or equally. Typically, if there are more indicators in one dimension than in others, indicator weights are adjusted to ensure equal weights across dimensions, but this need not be the case.
Define a poverty cut-off, such that a person exceeding the cut-off will be identified and counted (aggregated) as poor.
Aggregate up across individuals (or households) to obtain a measurement of multidimensional poverty for the country or region of interest.

To illustrate this method, suppose a hypothetical society with five people, where multidimensional poverty is measured based on four indicators: per capita household income, years of schooling, access to sanitation, and access to source of water. The deprivation thresholds for these indicators are, respectively: 400 monetary units (e.g. dollars, pesos, shillings), 5 years of schooling for adults, having access to improved sanitation, and having access to improved sources of water. In this example, the four indicators are weighted equally^[2], and the multidimensional poverty cut-off is two out of the four indicators. That is, the person would be considered poor if she is deprived in at least two out of the four indicators. Table 2 presents the individuals’ achievements in each of the four relevant indicators, and the deprivation cut-offs are shown in the bottom row. The achievements falling below the deprivation thresholds are highlighted in red. Table 3 shows the deprivation status of all individuals in the four indicators. Column (5) shows the sum of deprivations. Comparing this sum with the poverty cut-off (as mentioned above, two out of four) the individuals can be classified as poor and non-poor, as shown in column (6).

Table 2. Individual achievements in the variables selected to define multidimensional poverty

Individual	Income (in dollars)	Schooling (in years of education)	Improved Sanitation	Improved Water
1	100	3	No	No
2	200	2	No	Yes
3	350	5	Yes	Yes
4	500	4	Yes	No
5	600	6	Yes	Yes
Deprivation cut-offs	400	5	Yes	Yes

Note: Please note that the water and sanitation indicators are binary variables where a value of 1 corresponds to having access to an improved sanitation or water source, and is 0 otherwise.

Table 3: Deprivation status, deprivation score and poverty status

Individual	Deprived in…				Sum of Deprivations	Poor (at least two out of four)
Individual	Income	Schooling	Sanitation	Water	Sum of Deprivations	Poor (at least two out of four)
	(1)	(2)	(3)	(4)	(5)	(6)
1	1	1	1	1	4	Yes
2	1	1	1	0	3	Yes
3	1	0	0	0	1	No
4	0	1	0	1	2	Yes
5	0	0	0	0	0	No

The last step involves aggregating the information across individuals. The most common summary measure is the headcount ratio or incidence of poverty. The headcount ratio is the proportion of the total population classed as poor. In the example above, the incidence of multidimensional poverty is 60 percent ( $= \frac{3}{5} \times 100$ ). All empirical examples discussed in this section use the headcount ratio as the core measure of multidimensional poverty. On one hand, this measure is very intuitive and can be disaggregated by population sub-groups. On the other hand, it cannot be broken down by the contributions of each different indicator and it is not sensitive to the number of deprivations experienced by the poor. Because of these limitations, some methodologies propose other summary measures in addition to the headcount ratio. For the purpose of reporting on SDG Indicator 1.2.2, countries only need to compute the headcount ratio.

Unmet Basic Needs

The measures of Unmet Basic Needs (UBN), which proliferated in Latin America in the 1980s, are a direct application of the counting approach.^[3] These measures often use census data to produce detailed maps of poverty and can also be estimated using household surveys. They identify the poor using the counting approach as described above, following all the steps mentioned, and aggregate the information across households and people using incidence ratios. Most generally, the share of households or individuals with unmet basic needs is presented for different poverty cut-offs – that is, the proportion of households and people with one or more unmet basic need, the proportion of households and people with two or more unmet basic needs, and so on. The basic needs considered in these measures usually include (Feres and Mancero, 2001): access to housing that meets minimum housing standards, access to basic services that guarantee minimum sanitary conditions, access to basic education, and economic capacity to achieve minimum consumption levels. When these measures are estimated using census data, they can be highly disaggregated geographically, which makes it possible to construct detailed maps of poverty at district, municipality and even census ratio levels. Because of this property, maps of unmet basic needs have sometimes been used to allocate resources across areas.

Multidimensional Poverty Measurement in Mexico

The counting approach has been used to assess the number of people that are deprived simultaneously in income and in some non-monetary dimensions.^[4] Early applications can be found in Ireland, and more recently, in the United Kingdom for measuring child poverty.^[5] But the first country to develop an official and permanent measure of multidimensional poverty in the developing world was Mexico. The National Council for Evaluation of Social Development Policy (CONEVAL) led that process. In Mexico, multidimensional poverty is measured in the space of economic well-being and social rights, at the individual level:

“A person is considered to be multidimensionally poor when the exercise of at least one of her social rights is not guaranteed and if she also has an income that is insufficient to buy the goods and services required to fully satisfy her needs.” (CONEVAL, 2010)

Table 4: Dimensions and indicators of the measure of multidimensional poverty of Mexico

Type of Dimension	Dimension	Indicator
Economic well-being	Economic well-being	Income per capita
Social rights	Education	Educational gap (meeting a minimum level of education for their age cohort)
	Health	Enrolled in the Social Health Protection System
	Social security	Access to social security
	Housing	Quality and spaces of dwelling (floor, roof, walls, and overcrowding)
	Services in the dwelling	Access to basic services in dwelling (water, drainage, electricity, cooking fuel)
	Food	Food security

All persons whose income per capita is insufficient to cover necessary goods and services are considered deprived in economic well-being. For social rights, each of the six indicators in Table is generated as a binary variable, with 1 representing deprivation, and 0 otherwise. In the cases in which there is more than one indicator, that is, for housing and access to services in the dwelling, the individual is classified as deprived if she fails to meet the threshold for any single indicator within the dimension. The social deprivation index is then defined as the sum of these six indicators associated with social deprivation. The six dimensions are equally weighted, as all human rights are considered equally important. The social deprivation index thus takes a value between zero (the person is not deprived in any of the six social rights indicators) and six (the individual is deprived in all of them).

The classification of the population according to this method is illustrated in Figure 1. The vertical axis represents the space of economic well-being, measured by per capita household income. The horizontal axis represents the space of social rights. In this axis, individuals at the origin have a social deprivation index of six, individuals placed more to the right have fewer deprivations. The deprivation cutoff in the space of social rights is one, and individuals to the left of this threshold or on this threshold are considered to be deprived in social rights. People are divided into four groups (CONEVAL 2010, p. 32):

Multidimensionally poor. People with an income below the economic well-being threshold and with one or more unfulfilled social rights.
Vulnerable due to social deprivation. Socially deprived people with an income higher than the economic well-being threshold.
Vulnerable due to income. Population with no social deprivations and with an income below the economic well-being threshold.
Not multidimensionally poor and not vulnerable. Population with an income higher than the economic well-being threshold and with no social deprivations.

Figure 1: Identification of the multidimensionally poor in Mexico

Source: Adapted of CONEVAL (2010).

Among the multidimensionally poor, those in extreme poverty are also identified, by considering a lower economic well-being threshold (the minimum economic well-being threshold)^[6] and a higher deprivation threshold of three of more social deprivations.

In terms of aggregation, Mexico produces several categories of summary measures. The core measure is the headcount ratio, that is, the proportion of people who are multidimensionally poor (i.e. the proportion of people in group I in Figure 1). In addition, other headcount measures are also reported, such as the proportion of people deprived in economic well-being, the proportion deprived in each of the social rights, and the proportion showing one or more social deprivations. The depth of poverty is computed separately with respect to economic well-being and social deprivations. The depth of poverty in terms of economic well-being is the average gap between the well-being threshold and the income of poor people.^[7] This measure is reported for groups I and III in Figure 1. The depth of poverty in terms of social deprivations is the average proportion of deprivations among those suffering at least one deprivation. This measure is reported for groups I and II in Figure 1. Finally, the intensity of poverty corresponds to the product of the headcount ratio and the depth of poverty.^[8] This measure is computed for the multidimensionally poor (group I) and the socially deprived (group II).

In 2015, Vietnam launched their official multidimensional poverty index, following an approach similar to the one adopted in Mexico but using the household as the unit of analysis. A multidimensionally poor household is a household (1) whose monthly average income per capita is at or below income-based poverty line, OR (2) whose monthly average income per capita is above income-based poverty line but below minimum living standard AND is deprived on at least 3 indices for measuring deprivation of access to basic social services. Ten indicators are included in the list of basic social services. These are (1) adult education, (2) child school attendance, (3) accessibility to health care services, (4) health insurance, (5) quality of house, (6) housing area per capita, (7) drinking water supply, (8) hygienic toilet/latrine, (9) use of telecommunication services, and (10) assets for information accessibility.^{^[9]}

At Risk of Poverty or Social Exclusion

The “at-risk-of-poverty or social exclusion” rate, AROPE, is the main indicator to monitor the EU 2030 target on poverty and social exclusion, aiming at reducing the number of people at risk of poverty or social exclusion by at least 15 million, out of them, at least 5 million should be children. It also was the headline indicator to monitor the EU 2020 Strategy poverty target. It is defined as the proportion of people (or number of persons) that are either at risk of (monetary) poverty, or are living in a household with very low work intensity, or are severely materially and socially deprived. In other words, AROPE considers three dimensions/indicators, and the individual is at risk of poverty or social exclusion if she is deprived in at least one of those components.

An individual is at-risk-of-poverty if:

She has an equivalized disposable income (after social transfers) below the at-risk-of-poverty threshold, which is defined as the 60 percent of the national median equivalized disposable income after social transfers.
Lives in a household with very low work intensity, defined as “people from 0-64 years living in households where the adults (those aged 18-64, but excluding students aged 18-24 and people who are retired according to their self-defined current economic status or who receive any pension (except survivors pension), as well as people in the age bracket 60-64 who are inactive and living in a household where the main income is pensions) worked a working time equal or less than 20% of their total combined work-time potential during the previous year”.
Is severely materially and socially deprived, that is if she or her household cannot afford at least seven of the following 13 items^[10]:

List of items at household level:

Capacity to face unexpected expenses
Capacity to afford paying for one week annual holiday away from home
Capacity to being confronted with payment arrears (on mortgage or rental payments, utility bills, hire purchase instalments or other loan payments)
Capacity to afford a meal with meat, chicken, fish or vegetarian equivalent every second day
Ability to keep home adequately
Have access to a car/van for personal use
Replacing worn-out furniture

List of items at individual level:

Having internet connection
Replacing worn-out clothes by some new ones
Having two pairs of properly fitting shoes (including a pair of all-weather shoes)
Spending a small amount of money each week on him/herself
Having regular leisure activities
Getting together with friends/family for a drink/meal at least once a month

The information on the individuals at risk of poverty and social exclusion is aggregated in the form of an incidence rate, the proportion of individuals in the total population that are identified as being at risk of poverty or social exclusion. People are included only once even if they are in more than one situation (AROPE components mentioned above).

The construction of AROPE follows the same steps outlined above that are used in the UBN or mixed (CONEVAL) experiences. In addition, as in the two other highlighted cases, the three dimensions are equally weighted. However, while CONEVAL takes as deprived in social rights as those suffering from at least one deprivation in any indicator within this dimension, AROPE requires that within material and social deprivation at least seven deprivation items out of 13 are needed for establishing severe material and social deprivation.

Alkire-Foster Approach to Multidimensional Poverty

Alkire and Foster presented a family of multidimensional poverty measures based on the counting approach, which has captured global attention and is being widely adopted by countries. The first and most well-known application is the UNDP-OPHI Multidimensional Poverty Index (MPI) at the global level, which has been published since 2011. Since then, many countries have followed their guidance in what is known as “the MPI approach.”

The Alkire-Foster family of measures follows the five steps of counting approaches described above and the two stages of identification and aggregation: (1) there is a first cut-off for each deprivation-specific threshold, and (2) there is second cut-off at the aggregation stage to determine whether the person (or household) is multidimensionally poor based on the deprivation score. Differential weights are sometimes used at the aggregation stage, but they are not mandatory. This results in an estimate of the incidence or prevalence of poverty, which is usually referred as H.

An innovation introduced by the Alkire-Foster family of measures is that it is possible to account simultaneously for both the incidence of poverty (H), as well as its intensity (A).^[11] The intensity of poverty – also called breadth of poverty – is defined as the average proportion of the relevant multidimensional poverty indicators (weighted or not) in which the poor are deprived. When using categorical variables, it is possible to estimate an adjusted headcount ratio ( $M_{0}$ or MPI), where

$M_{0} = H \times A$ .

The adjusted headcount ratio, just like the other measures described in this note, can be disaggregated by population subgroups (e.g. geographic area, ethnicity), and it can be broken down by dimension or indicator. For more details on the methodology, see Alkire et al. (2015).

The Alkire-Foster approach can be seen as a general framework to measure multidimensional poverty that can be tailored to very different contexts. Many of the existing permanent national statistics of multidimensional poverty are based on the global MPI, but with substantial modifications in terms of dimensions, indicators, and thresholds.^[12] Since 2018, the World Bank regularly presents multidimensional poverty measures across countries using the headcount ratio (H), as is done by UNDP-OPHI measure, albeit with differences in the selection of parameters, some of the indicators, and sources of data. In addition to the headcount ratio, the 2018 Poverty and Shared Prosperity report, where the World Bank introduced this multidimensional measure, presents estimates of global poverty using the adjusted headcount ratio of the Alkire-Foster family as well as the distribution-sensitive multidimensional poverty measure, proposed in Datt (2018).

Child Poverty

Children experience and suffer poverty differently than adults (UNICEF, 2019). Their needs are also different, for example in terms of nutrition or education. However, children are often invisible in poverty estimates. That is why the SDG 1.2.2 explicitly mentions children and why countries should establish a child-specific measure of poverty. The European Conference of Statisticians (2020) recommends that countries “develop child-specific and life-cycle adapted multidimensional poverty measures” (Recommendation 29).

If child-specific poverty measures are not developed, there is a risk of misinterpreting the evolving situation of children and consequently misinterpreting the impact of policies and external shocks. It is possible that while the situation of children in a given household deteriorates, that household becomes “non-poor” due to indicators that matter only for adults. In such a case, despite the fact that these children are worse-off than they were before, they would no longer be counted as poor.

Over 70 low- and middle-income countries which have carried out child poverty analyses based on a child-specific measure of child poverty use the child as the unit of analysis. These countries are in all regions of the developing world, (e.g. Argentina, Armenia, Brazil, Egypt, Ethiopia, Mexico, Sierra Leone, Uganda, and Zambia), as well as in the European Union.

Estimating multidimensional child poverty follows the same steps as the other examples mentioned above: the relevant dimensions are identified, criteria to assess deprivation in each dimension are established, and deprived children in each dimension are identified. A threshold is then specified concerning the minimum number of dimensions in which a child must be deprived to be considered poor, and children above or below this threshold are then counted. Moreover, the percentage (and number) of children deprived in exactly one, exactly two, exactly three, et cetera, deprivations are reported and analyzed, as well as the overlaps or simultaneous deprivations. This makes it possible to measure the incidence, the breadth, and the severity of poverty in a simple and integrated way.

For child poverty, the selection of dimensions should be based on child rights. However, not all rights constitute child poverty, as explained in the Guidelines on Human Rights and Poverty from the Office of the High Commissioner for Human Rights. According to the Conference of European Statisticians: “Deprivation measures need to be based upon a clear and explicit theory or normative definition of poverty in order to ensure that each indicator is a valid measure, i.e. that it measures poverty and not some other related (or unrelated) concept such as wellbeing [sic] or happiness” (Recommendation 28 (a), emphasis added).

As in the case of CONEVAL (explicitly) and UBN (implicitly), no differential weights should be applied across dimensions because they are rights. All rights are equally important and cannot be substituted. This is not just emanating from the human rights approach, but it is also the case with capabilities approach, as stated by Dixon and Nussbaum (2012): “A Capabilities Approach is generally committed to the equal protection of rights for all up to a certain threshold. Any trade-off that leaves some people below this threshold will thus be a clear failure of basic justice under a Capabilities Approach” (Children’s Rights and a Capabilities Approach: The Question of Special Priority, p. 554, Public Law and Legal Theory Working Paper No. 384.)

Decanq and Lugo (2013) explore and explain various approaches to setting weights. ↑

This approach was proposed in several publications before being adopted widely in Latin America. See, among others: ILO (1978), Morris (1978) and Streeten et al. (1981). ↑

⁴

Early examples of analyses using this approach include, for instance, Beccaria and Minujín (1985), Minujin, A. (1995), and Erikson, R (1989). ↑

⁵

In Ireland, since 1997 “consistent poverty” is defined as the proportion of people who are both income-poor and cannot afford at least two of the set of items considered essential for a basic standard of living (previously 8, now 11 items are considered as essential). Since 2010, the United Kingdom applies a similar definition for one of its four policy targets on child poverty, combining low income and material deprivation (The Child Poverty Unit, 2014). ↑

⁶

The economic well-being threshold was defined with reference to a basket of basic goods and services. The minimum economic well-being threshold is the minimum required income to acquire enough food to ensure adequate nutrition. ↑

⁷

Foster, Greer and Thorbecke (1976). ↑

⁸

Following Alkire and Foster (2007). ↑

⁹

Vietnam General Statistics Office. https://www.gso.gov.vn/en/metadata/2019/10/explanation-of-terminology-content-and-methodology-of-some-statistical-indicators-on-living-standard/ ↑

¹⁰

In 2021, the AROPE indicator was modified in line with the new EU 2030 target so that the severe material deprivation component includes social deprivation. The low work intensity component was also revised to better account for the social exclusion situation of those in the working age. During 2010-2020, under the EU 2020 target, the households were regarded as severely materially deprived if she can not afford at least four of the following nine items; 1) to pay the rent, mortgage or utility bills, 2) to keep the home adequately warm, 3) to face unexpected expenses, 4) to eat meat or proteins regularly, 5) to go on holiday, 6) a television set, 7) a washing machine, 8) a car, 9) a telephone. ↑

¹¹

The formula developed by Datt and featured in the 2018 Poverty and Shared Prosperity report by the World Bank (2018), also allows for a combination of incidence and breadth of poverty. There are several other formulae which allow this combination. ↑

¹²

For information on these measures, visit the website of the Multidimensional Poverty Peer Network (MPPN), www.mppn.org. The MPPN was launched in 2013 to provide support to policy makers who are implementing a Multidimensional Poverty Index (MPI) or are exploring the possibility of developing multidimensional measures of poverty. ↑

4.d. Validation

The data has been validated by a three-stage approach to ensure its accuracy. First, the data is entered by World Bank staff assigned to each country, typically in consultation with the country NSO and/or country official documents. That data is sent to UNICEF and UNDP country officers for the validation. After integrating inputs from these three agencies, the data is sent to the SDGs focal point for each country for their final approval. For countries where the World Bank does not have any country offices, such as for OECD and EU countries, the World Bank collected the information based on data source available online, and sent it directly to the official counterparts of each country for verification.

4.e. Adjustments

Not applicable

4.f. Treatment of missing values (i) at country level and (ii) at regional level

• At country level

The treatment of missing values differs from survey to survey. For details, please refer to the official documentation through the links listed at the end.

• At regional and global levels

No estimation by international agencies has been implemented for missing values in this data.

4.g. Regional aggregations

Since the data for indicator 1.2.2 are based on the national definitions of poverty – and consequently the indicators and thresholds used to produce them are different, as described in the “comments and limitations” section, data are not comparable across countries. Thus, regional and global aggregates are not produced.

4.h. Methods and guidance available to countries for the compilation of the data at the national level

A successful measure of multidimensional poverty should be rigorous, institutionalized, sustainable, and useful. Such a measure generates credible and relevant information, and it is established as an official permanent statistic alongside traditional ones such as the income or expenditure poverty headcount and poverty gaps. As with other indicators, it is important that a clear and transparent system be in place for the regular updating of the measurement. This implies that the responsibility for these updates is assigned to an official entity and that associated costs are incorporated in the government’s budget. Ideally, a multidimensional poverty measure could be used actively to guide policy-making (e.g. policies coordination, targeting, and policy evaluation).

To make such a measure institutional and useful, it is fundamental for the government to own the process. Having the support of high-level representatives within the government, such as the president or prime minister, or ministers, grants additional legitimacy to the process and may facilitate the adoption of the measure by other levels of government and stakeholders. In addition, a high-level official may be able to bring other relevant actors into the design process and work on the institutionalization of the measure. The active participation of different ministries in the discussions and decisions throughout the process of design, namely the selection of indicators, respective cut-offs, and weights, is essential to ensure that the final measure meets the needs of policy makers in a specific country context.

To make a measure long-lasting, rather than specific to a particular administration, it is useful to build consensus and a shared sense of legitimacy around the measure that transcends individual political actors. This requires that the process of developing the measure is perceived as credible, transparent, and non-partisan. Engaging key stakeholders, such as academics, opinion leaders, the opposition, and civil society representatives throughout the process is highly desirable. This should include wide consultations with the public, for example through nationally representative surveys to capture the national consensus about the minima required to satisfy different dimensions. In addition, it is important to have a well-designed communication strategy to explain the concept and the process to these different actors, allowing for channels for them to participate in the discussions about the design of the measure. Some countries have opted for involving a poverty committee that gathers experts and representatives from different sectors of society in the decision process of designing the measure.

More specifically, the design of a measure of multidimensional poverty generally involves a technical process, complemented and supported by a political process. If both technical and political committees are set up, it is useful to agree on: (1) a plan of activities and timeline; (2) a schedule of regular interactions to ensure good communication; and (3) a documentation system that keeps track of all decisions and respective rationales. However, political interference in the technical process should be avoided, as recommended by the UNSD National Quality Assurance Frameworks Manual for Official Statistics.

4.i. Quality management

The data has been validated by a three-stage approach to assure its accuracy. First, the data is entered by World Bank staff assigned to each country, typically in consultation with the country NSO and/or country official documents. That data is sent to UNICEF and UNDP country officers for the validation. After integrating inputs from these three agencies, the data is sent to the SDGs focal point for each country for their final approval. For countries where the World Bank does not have any country offices, such as for OECD and EU countries, the World Bank collected the information based on data source available online, and sent it directly to the official counterparts of each country for verification.

4.j. Quality assurance

Initially, the data has been input by poverty economists, which has been checked carefully together with the metadata information by the central team for monitoring SDGs 1.2.2 in the World Bank. Then data has been sent to the UNDP and UNICEF for further verification.

4.k. Quality assessment

As the custodians of the data are countries, the partner agencies do not conduct any quality assessment on the data itself other than ensuring that the data corresponds to those numbers officially published.

5. Data availability and disaggregation

Level of disaggregation:

Official multidimensional poverty headcount (% population) is disaggregated by sex and age. The age band for official multidimensional poverty headcount for children is mostly 0-17, but some countries have different age definition for children, such as 0-15 in El Salvador. Geographically it is disaggregated by urban and rural areas.

Years of Reporting:

Years of reporting in the SDG 1.2.2 indicators are those when the source survey has been conducted except for the AROPE. When the survey year is split into two years, the first year has been reported. In AROPE, the reference period for all dimensions along with the indicators is disseminated as well as variables related to the materially deprived items in question in the survey year, except for age, income, variables on arrears, work intensity of the household, country of birth. As far as age is concerned, depending on the EU-SILC question, age can refer to two different moments in time: (i) age at the end of the income reference period; (ii) age at the date of interview. The age at the end of the income reference period is considered as the main age (e.g. it is used to define the statistical population, sample person, etc.). For income, the income reference period is a fixed 12-month period (such as the previous calendar or tax year). Variables on arrears refer to the last 12 months, while work intensity of the household refers to the number of months that all working age household members have been working during the income reference year.

Data Availability:

So far, 78 countries' multidimensional poverty measurements were reported and confirmed by SDG focal points. However, the availability of the multidimensional poverty indicator over time differs greatly from country to country. The following table 5 shows the years in which data is available for a country (the coloured boxes). The star mark indicates that data on multidimensional deprivation for children is available.

Table 5: Headcount data availability for countries

Country

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

Afghanistan

Albania

Angola

PH *

Armenia

PH *

Austria

Belgium

Bhutan

Bulgaria

Burundi

PH *

Chile

Colombia

Costa Rica

Croatia

Cyprus

Czechia

Denmark

Dominican Republic

Ecuador

Egypt

El Salvador

Estonia

Finland

France

Germany

Ghana

Greece

Guatemala

Guinea

Guinea Bissau

PH *

Honduras

Hungary

Iceland

Ireland

Italy

Kosovo

Latvia

Lesotho

Lithuania

Luxembourg

Malawi

Malaysia

Maldives

Mali

Malta

Mexico

Montenegro

Morocco

Mozambique

Namibia

Nepal

Netherlands

Nigeria

North Macedonia

Norway

Pakistan

Palestine

Panama

Paraguay

Philippines

Poland

Romania

Rwanda

Saint Lucia

São Tomé and Príncipe

Serbia

Seychelles

Slovakia

Slovenia

South Africa

Spain

Sri Lanka

Sweden

Thailand

Turkey

Uganda

Vietnam

Zambia

Zimbabwe

PH	Poverty headcount data available
*	Multidimensional deprivation for children available

6. Comparability/deviation from international standards

Comparability:

As it was mentioned in section 4, the compiled data of SDG 1.2.2 are not intended to be comparable across countries due to national definitions. It is quite common that countries use a different number of dimensions and a variety of indicators depending on the country context. As SDG 1.2.2 explicitly says multidimensional poverty should be estimated in each country according to national definitions, this lack of comparability is not an issue.

Sources of discrepancies:

Given there is no custodian agency to estimate internationally comparable levels of multidimensional poverty, there are no, stricto sensu, challenges in terms of discrepancies. Nevertheless, sometimes agencies do calculate multidimensional poverty, using common and comparable dimensions, indicators, and thresholds for different types of reports or analyses. In these cases, it has to be remembered that these are not official (i.e. government sanctioned and approved) estimates. Most importantly, they should not be used to replace nationally owned estimates.

7. References and Documentation

Country	Reference
Afghanistan	(2016) Official publication: Afghanistan Multidimensional Poverty Index 2016-2017 (2019) Official publication: Income and Expenditure & Labor Force Survey 2019-2020
Albania	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Angola	Official publication: Childhood in Angola - A Multidimensional Analysis of Child Poverty/ Pobreza Multidimensional em Angola
Armenia	(2010-2017) Official publication: Social Snapshot and Poverty in Armenia: Statistical and analytical report, 2018 Methodological documentation: The Many Faces of Deprivation: A Multidimensional Approach to Poverty in Armenia (2018) Official publication: Social Snapshot and Poverty in Armenia, 2019 Methodological documentation: The Many Faces of Deprivation: A Multidimensional Approach to Poverty in Armenia (2019) Official publication: Social Snapshot and Poverty in Armenia, 2021 Methodological documentation: The Many Faces of Deprivation: A Multidimensional Approach to Poverty in Armenia
Austria	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Belgium	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Bhutan	(2010) Official publication: CHILD POVERTY IN BHUTAN: Insights from Multidimensional Child Poverty Index and Qualitative Interviews with Poor Children (2012, 2017) Official publication: Bhutan Multidimensional Poverty Index 2017
Bulgaria	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Burundi	Official publication: Rapport de l’enquête modulaire sur les conditions de vie des ménages 2013/2014 / La Pauvreté des Enfants au Burundi
Chile	(2011 and 2013) Official publication: Informe de desarrollo social 2015 (2015 and 2017) Official publication: http://observatorio.ministeriodesarrollosocial.gob.cl/storage/docs/casen/2017/Resultados_pobreza_Casen_2017.pdf
Colombia	(2010) Official publication: Pobreza multidimensional en Colombia (2011-2020) Official publication: Pobreza Multidimensional
Costa Rica	Official publication: Encuesta Nacional de Hogares Julio 2022 RESULTADOS GENERALES
Croatia	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Cyprus	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Czechia	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Denmark	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Dominican Republic	(2010-2016) Official publication: The Multidimensional Poverty Index for Latin America (MPI-LA): an application for the Dominican Republic 2000-2016. (2017-2019) Official publication: Sistema de Indicadores Sociales de la República Dominicana SISDOM 19
Ecuador	Official publication: National Employment, Underemployment and Unemployment Survey (ENEMDU) 2019
Egypt	Official publication: Understanding Multidimensional Poverty in Egypt
El Salvador	Official publication: INFORME EL SALVADOR 2019 Methodological documentation: EHMP 2016 El Salvador/ Informe MMP 2017.
Estonia	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Finland	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
France	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Germany	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Ghana	(2010) Official publication: Non-Monetary Poverty in Ghana (2011, 2016, 2018) Official publication: Ghana Multidimensional Poverty Index (MPI) report 2020 (2017) Official publication: Multi-Dimensional Child Poverty in Ghana
Greece	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Guatemala	Official publication: https://www.mintrabajo.gob.gt/images/Servicios/DGT/ComisionNacionalSalario/InformacionGeneral/MIDES/Estad%C3%ADsticas_Indic%C3%A9_de_Pobreza_Multidimensional_2014.xlsx
Guinea	Official publication : RECENSEMENT GENERAL DE LA POPULATION ET DE L’HABITATION
Guinea Bissau	(2010, 2014) Official publication: PAUVRETE MULTIDIMENSIONNELLE ET PRIVATIONS MULTIPLES DES ENFANTS EN GUINEE-BISSAU
Honduras	Official publication : Multidimensional Poverty Index 2012- 2016
Hungary	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Iceland	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Ireland	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Italy	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Kosovo	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Latvia	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Lesotho	Official publication: Child Poverty in Lesotho: Understanding the Extent of Multiple Overlapping Deprivation
Lithuania	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Luxembourg	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Malawi	(2013) Official publication: Child Poverty in Malawi (2016) Official publication: Child Poverty in Malawi
Malaysia	(2014, 2016) Official publication: Mid-term Review of the Eleventh Malaysia Plan, 2016–2020: New Priorities and Emphases: (2019) Official publication: https://newss.statistics.gov.my/newss-portalx/ep/epFreeDownloadContentSearch.seam?cid=158397
Maldives	Official publication: National Multidimensional Poverty in Maldives 2020
Mali	(2015) Official publication : Privation multidimensionnelle et pauvreté des enfants au Mali (2016) Official publication : La pauvreté à plusieurs dimensions au Mali
Malta	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Mexico	(2010, 2012, 2014) Official publication: https://www.coneval.org.mx/Medicion/MP/Paginas/Pobreza-2018.aspx Methodological documentation: https://www.coneval.org.mx/Informes/Coordinacion/Publicaciones%20oficiales/MEDICION_MULTIDIMENSIONAL_SEGUNDA_EDICION.pdf (2016, 2018, 2020) Official publication: https://www.coneval.org.mx/Medicion/MP/Paginas/Pobreza_2020.aspx Methodological documentation: https://www.coneval.org.mx/InformesPublicaciones/InformesPublicaciones/Documents/Metodologia-medicion-multidimensional-3er-edicion.pdf
Montenegro	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Morocco	(2011) Official publication: Principaux résultats de l’Enquête nationale sur l’anthropométrie 2011 (2014) Official publication: Principaux résultats de la cartographie de la pauvreté multidimensionnelle 2004 - 2014 : Paysage territorial et dynamique
Mozambique	Official publication: Poverty and Well-being in Mozambique: Fourth National Poverty Assessment (IOF 2014/2015)
Namibia	Official publication: Namibia Multidimensional Poverty Index (MPI) report 2021
Nepal	(2011) Official publication: Nepal Multidimensional Poverty Index 2018 (2014,2019) Official publication: Nepal Multidimensional Poverty Index
Netherlands	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Nigeria	(2017) Official publication: National Human Development Report 2018 (2021) Official publication: Nigeria Multidimensional Poverty Index
North Macedonia	(2010) Official publication: Survey on Income and Living Conditions, 2012 (2011-2013) Official publication: Survey on Income and Living Conditions, 2013 (2014-2016) Official publication: Survey on Income and Living Conditions, 2016 (2017) Official publication: Survey on Income and Living Conditions, 2017 (2018) Official publication: http://makstat.stat.gov.mk/PXWeb/pxweb/en/MakStat/MakStat__ZivotenStandard__LaekenIndikatorSiromastija/425_ZivStd_Mk_LaekenAROPE_ml.px/?rxid=46ee0f64-2992-4b45-a2d9-c Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Methodological documentation: Laeken Poverty Indicators
Norway	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Pakistan	Official publication: Multidimensional Poverty in Pakistan
Palestine	Official publication: Multi-dimensional Poverty Profile in Palestine, 2017
Panama	(2017) Official publication: Panama Multidimensional Poverty Index (2018) Official publication: Multidimensional Poverty Index of Boys, Girlsand Adolescents in Panama - IPM-NNA
Paraguay	Official publication: Multidimensional poverty index
Philippines	Official document: Philippine Statistics Authority press release Methodological documentation: Technical notes on the estimation of the MPI based on the initial methodology
Poland	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Romania	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Rwanda	Official publication: Rwanda Multidimensional Poverty Index Report, 2018
Saint Lucia	Official publication: Saint Lucia National Report of Living Conditions 2016
São Tomé and Príncipe	Official publication: Analyse de la situation des enfants et des femmes à São Tomé-et-Principe en 2015
Serbia	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Seychelles	Official publication: https://www.nbs.gov.sc/downloads/social-statistics/multidimensional-poverty-index/2018
Slovakia	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Slovenia	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
South Africa	(2011) Official publication: The South African MPI (2016) Official publication: Overcoming Poverty and Inequality in South Africa
Spain	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Sri Lanka	(2016) Official publication: Global Multidimensional Poverty for Sri Lanka (2019) Official publication: Multidimensional Poverty in Sri Lanka
Sweden	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Thailand	(2015) Official publication: Thailand Child Poverty Report (2017) Official publication: http://social.nesdc.go.th/social/Portals/0/Documents/%e0%b8%a3%e0%b8%a7%e0%b8%a1%20NMPI%2007102019%20(1630)_2305.pdf Methodological documentation: http://www.nso.go.th/sites/2014en/Pages/survey/Social/Household/The-2017-Household-Socio-Economic-Survey.aspx
Turkey	Official publication: People at risk of poverty or social exclusion by age and sex – EU 2030 target Sustainable development in the European Union
Uganda	Official publication: Multidimensional Poverty Index Report
Vietnam	Official publication: https://www.gso.gov.vn/en/px-web/?pxid=E1144&theme=Health%2C%20Culture%2C%20Sport%20and%20Living%20standard
Zambia	Official publication: Child Poverty in Zambia
Zimbabwe	Official publication: Child Poverty in Zimbabwe

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The Child Poverty Unit (2014). Child Poverty Act 2010, http://www.legislation.gov.uk/ukpga/2010/9/contents,

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SDMX Metadata Concepts