This article focuses on Multidimensional poverty index (MPI)—the alternative approach to poverty measurement. While the official monetary approach is based on a comparison of income with a certain poverty line (until 2021 in Russia it was based on the minimum subsistence level, since 2021 it has been calculated as a share of median income of the population), the MPI also includes deprivations that poor people may face. The text contains the description of the index calculation methodology, the results of its computation on Russian data (Statistical Survey of Income and Participation in Social Programs-2017), and the description of vulnerable groups of population in accordance with the MPI. Population groups that are identified as being at risk of poverty (according to the index) are similar to the vulnerable population based on the absolute monetary poverty approach. However, the index widens the list of such groups, covering older people and people with disabilities.

poverty, multidimensional poverty approach, poverty measurement, poverty profiles.

Overcoming poverty is still the core task for social policy, both in Russia and abroad. Hence the issues concerning poverty measurement are of high importance. All the existing approaches to poverty measurement can be divided into monetary (or welfare) and non-monetary ones. The first one is based on the sums of money that a household or an individual has, while the latter focuses on other criteria.

The monetary approach methodology is adopted by the World Bank (2022), Eurostat (2021b), and OECD (2019). When this methodology is used, the core question is what are the criteria of being poor, i.e., what is the poverty line? Three possible answers to this question have formed three different monetary approaches to poverty: absolute, relative, and subjective.

The absolute monetary approach employs the idea that those who cannot afford the minimal set of goods and services, those deemed necessary to survive, are poor. This approach has a rich history; the first attempts to implement it were made at the end of the 19^th century by S. Rowntree and C. Booth in London and, later, in York (Laderchi et al., 2003). This poses the question: which goods and services are necessary and how do we evaluate their price? Usually, the set of such goods includes certain foods and durables. The list of food products can be formed in different ways: the necessary calorie intake or the consumption rate of fats and proteins can be considered. Some calculations can also include the requirements for vitamins and mineral consumption (see, for example, Allan, 2016). The main disadvantage of the absolute approach is that poverty becomes similar to survival.

In the case of the relative approach, income is compared with the consumption standard typical for a certain society. The median income is supposed to be the indicator of such level of consumption, while the poverty line is set at 60% of median income. Sometimes the criteria set at 40% or 50% of the median are also used. The approach is highly dependent on income distribution among the population.

The critics of absolute and relative approaches resulted in the development of the so-called subjective approach. Its core idea is to define the poverty line in accordance with the perception of the people. For the first time, this methodology­ was adopted by P. Streeten (Wagle, 2002). The same idea was employed in Gallup Institute and Eurobarometer studies (Ovcharova, 2009).

Monetary approaches provide a useful tool for poverty analysis; however, with the development of poverty studies, it became evident that poverty is not only about lack of money. This idea was developed in non-monetary approaches. They usually describe poverty in terms of deprivations (lack of necessary resources) or social exclusion. The deprivation approach is based on the idea that poor people have no access to certain goods, services, or practices that are widespread in society. The notion of social exclusion appeared in France in the 1960s. Later, the concept of social exclusion was developed further to include limitations in consumption, civil rights, etc. (Ovcharova, 2009). As well as with monetary approaches, the core issue is to identify the poverty line: the list of deprivations and the number of them for someone to be considered poor. In some cases, such a list of deprivations can be formed by the researcher. Such an approach was implemented by P. Townsend (1979) and T. Atkinson (World Bank, 2017). The attempt to form the list of deprivations in accordance with public opinion was made by Mack and Lansley (1985). Only the deprivations that were perceived as connected with poverty by 90% of the population were included in the list (Ovcharova, 2009).

Previous studies have demonstrated that the adoption of different approaches gives a high variation in poverty level evaluations (Laderchi et al., 2003). Each of the approaches has its advantages and disadvantages. The absolute one provides the ability to evaluate the number of people who cannot afford the minimum neces­sary set of goods and services, however, it doesn’t enable to assess the number of people who have standards of living that are lower than in society in general. This problem can be solved by the relative approach, but its critics emphasize that any evaluation of poverty should include criteria other than mere income level, and other deprivations that poor people face should be considered. The latter are included in subjective and non-monetary methodologies; however, they also appear to be an imperfect solution as they raise the question regarding specific deprivations that determine poverty. There is no perfect poverty measure. Its most complex vision can be acquired by combining the aforementioned approaches. While monetary indicators of poverty are constantly tracked by scholars and policymakers, less attention is paid to non-monetary ones.

To combine the advantages of all the approaches described above a complex index has been developed, which is called the Multidimensional Poverty Index (MPI). Nowadays, it is seen as a valuable tool not only to assess the poverty level, but also to develop social policy measures. In 2019, UNDP in cooperation with Oxford University released the step-by-step guide for developing the national MPI. The guide introduced the complex approach combining the development and assessment of the index and the measures for its popularization. Index decomposition and the ability to evaluate deprivations that are most typical for the poor population are core aspects for using the index as a social policy tool because they help to prioritize policy measures. Such an approach also makes it possible to track the effectiveness of implemented measures: if the weight of the domain in the index structure decreases, the social support system has a positive influence. The following countries use the MPI as a social policy tool: Mexico, Columbia, Costa Rica, Chile, and Vietnam (UNDP, 2019b).

The article is devoted to the index description and its calculation on Russian data. Recently, interest in poverty methodology measurement has risen. In 2017 the Ministry of Labor and Social Support introduced an initiative to change the structure of the consumer basket by 2021. However, in 2021 this question became irrelevant as the relative approach to poverty measurement was set for the official statistics. The minimum subsistence level is now based not on the consumer basket but on the income distribution of the population. The poverty­ line was set at 44.2% of median population income. The changes were fixed in the Federal Law dated October 23, 1997 No. 134-FZ “About the minimum subsistence level in Russia”; it is planned to review this ratio in 5 years.

As the poverty assessment was long based on the consumer basket, it was necessary to use the comparable approach to follow the poverty dynamics. For such evaluations, the notion of “poverty bound” was introduced. The calculation was based on the consumer basket that was multiplied by the price index.

Despite all the changes in the methodology of poverty measurement, all the introduced indicators have one characteristic in common: they are aimed at assessing monetary indicators and ignore the non-monetary aspects of poverty.

The problems of poverty in Russia seem to be an interesting case for research also in the political context. In 2018, the Decree of the President of the Russian Federation No. 204 dated May 7, 2018 “On national goals and strategic objectives of the development of the Russian Federation for the period up to 2024” was signed. The Decree aimed at halving the incidence of poverty levels: from 13.2% in 2017 to 6.6% in 2024. The COVID-19 pandemic changed the timing and the Decree “On the national development goals of the Russian Federation for the period up to 2030” was signed. The latter revises the period of expected poverty reduction to 2030. This indicates that the relatively rapid decrease of officially measured monetary poverty is planned while other poverty indicators fall out of the scope. The calculation of the MPI and its evaluation at the beginning and at the end of the considered period can show changes in non-monetary poverty aspects that accompany the rapid decrease in monetary poverty.

Summarizing all the ideas above, Russia seems to be a good example for MPI evaluation as the poverty line in the country changed several times over the last 30 years; however, it was always based on monetary approaches. As a result, the level and profile of absolute poverty are well-known, but less is known about non-monetary issues. This paper aims to fill this gap.

The dynamics of different poverty indicators are tracked by the Federal State Statistics Service (Rosstat). The open data demonstrates the share of the poor following the official methodology of poverty measurement and in accordance with international standards (Fig. 1). The World Bank sets the poverty lines at $1.9 per day (if it is employed, the poverty level in Russia is close to zero), $3.2 per day, and $5.5 per day. The share of the poor identified by non-monetary approaches is not available.

Poverty in Russia is quite changeable: the transformations touch upon both the number of the poor and the composition of this group. In accordance with monetary poverty indicators, in the 1990s the decrease in living standards, that started during the transformation period, pushed into poverty about ¹/₃ of the popu­lation, and the group of “the new poor” appeared. In the 2000s the economic growth that accompanied the favorable situation on the world raw materials market resulted in gradual poverty reduction. The economic crisis of 2008–2009 had a severe impact on the population; however, poverty levels didn’t change dramatically. The situation after this crisis turned out to be different: after 2013 the longest period of the decrease in real income took place—the process of recovery lasted several years, and the officially registered number of poor reached 13.3% (in 2015). The most significant reason for the poverty growth was the decrease in real wages and the growth in prices of basic goods (the spending on this ­category has a high share in the budget of the poor). In addition, for the first time in 15 years the decrease in real pensions was evidenced (in 2015), which dropped to 96.2% of the previous year’s level (Rosstat, 2022).

The comparative analysis of the structure of the poor population shows the most vulnerable groups (Tables 1–2). Those who live in rural areas, and members of large families (the share of households with 5 or more people among the poor is almost 4 times higher than among the families in general) face the highest risks of poverty. Families with children also often suffer from lack of money.

When the gender and age structure of the poor are considered, the dominance of the children aged below 16 years old should be mentioned. The share of those above the working age is lower than for the population in general. High risks of poverty are also typical for non-working people (except for non-working retirees).

The poverty profiles mentioned above were described by a number of scholars and remained stable in recent years (Ovcharova, 2014; Pishnyak et al., 2021; Gorshkov and Tikhonova, 2014).

The steps for evaluating non-monetary deprivation approaches were previously taken in the Russian scientific field (Tikhonova, 2014; Institute for Social Policy, 2017). The usage of different methodologies (different lists of deprivations and their number set as a poverty line) caused high variation in the estimated share of the poor: from 25% in 2013 (Tikhonova, 2014) to 14% in 2016 (Institute for Social Policy, 2017). The assessment based on the deprivation approach highlighted the higher poverty risks for retirees, who are seldom considered to be poor by the official statistics, especially in the case of families that consist only of retirees. The families with children, that are usually monetary poor, were relatively low deprived in comparison with households in general (Institute for Social Policy, 2017).

Figure 1. 

The poverty level in Russia according to different approaches. Source: Rosstat.

There are different ways to widen the scope of poverty analysis and include non-monetary indicators (like evaluation of subjective poverty or deprivations analysis). One of the examples of such an approach is the AROPE index (at risk of poverty or social exclusion) (Eurostat, 2021a). This index has a long history; in 2021 it was modified. Now it consists of three domains: severe material deprivation (presence of 7 of 13 different material deprivations), at risk of poverty rate, and low work intensity indicator. Such an index structure widens the definition of poverty, including not only monetary deprivations in the index. However, the index structure is rigid in that it enables cross-country comparisons but doesn’t allow to adapt the index for a regional context.

The deprivation index, which was described above, is the alternative to the AROPE index. When such a methodology is employed, the set of deprivations is formed. Those who suffer from a certain number of problems are classified as poor (UNECE, 2017). The list of deprivations can be changed, making it possible to adapt the index for each country. However, some problems can be more harmful to people than others. This idea can be taken into account when the Multidimensional poverty index is used, which introduces the weights for each index component (the higher is the weight, the more serious is the problem). Below, the index methodology is described.

We focus on the MPI that has different implementations all over the world. The renowned economist Amartya Sen is considered to be the founder of this approach, as he was the first to formulate the idea that poverty is not just about the lack of money, but rather the lack of capabilities. According to his theory, the development of society should result in widening the range of human capabilities. If there are no such capabilities, or they are not enough, one can be considered poor. Sen (1995) supposed that just reducing the definition of poverty to a mere lack of money makes people set lower requirements and, finally, they adjust their expectations and wishes to the issues that appear feasible which is a sort of “adapted preferences.” However, people should live a “valued life.”

Sen’s idea was developed by his followers, Sabina Alkire and James E. Foster (Alkire and Foster, 2008). They proposed a methodology that included the aggregated indicator to take into account the problems that the poor face and which capabilities they lack (in the paper we will call it “deprivation­”). The MPI was approved by many scholars, and used as a basis for the United Nations Development Program Global Multidimensional Poverty Index (UNDP, 2019a).

Two steps should be taken to build this index. Firstly, the set of deprivations that a person or family can face is formulated. The criteria for suffering from each problem are set up, to make it clear whether one faces deprivation or not. For example, for such deprivation as “access to drinking water,” the following criteria can be used: “having access to improved drinking water within 30-minute walk from home, round trip”.

Secondly, all the identified problems are divided into groups or domains. As a result, the index consists of domains, and each domain consists of a list of deprivations. The methodology of the index calculation is based on the assumption that the importance of different domains, for poverty evaluation, can differ. To take it into account, the weight coefficient for each domain can be introduced: the higher is the weight, the more important is the domain and the higher is its impact on the total index. The coefficients are set in accordance with expert opinion or mathematical calculations. In any case, all the coefficients should sum up to 1.

The weight of each domain is allocated evenly to each deprivation it includes. After that, for each case in the sample (person or family), the total sum of the weights of deprivations it faces is computed. The result is compared with a threshold—the specific poverty line (sum of weights that depends on the number of deprivations) and, if the sum is higher than this threshold, the individual or household is considered to be poor.

MPI is calculated as the product of two indicators:

MPI = H × A, (1)

where H is poverty headcount; A is average intensity of deprivation.

The share of the poor is calculated as the ratio:

$H=\frac{q}{n}$, (2)

where q is the number of poor, n is all the population.

The average intensity of deprivation is estimated as the weighted average of deprivations among the poor population:

$A=\frac{{\sum }_1^q{c}_i}{q}$, (3)

where q is the number of the poor, c_i is the Poverty index (weighted) for individual i.

The MPI methodology is still developing nowadays. Initially, it was used to evaluate­ poverty indicators in a certain period, but later, the authors decided that it was important to track a person’s position: can one escape from poverty, or do they have to stay poor for a long time? The MPI methodology was widened and used to evaluate chronic poverty (Alkire et al., 2017a). The index is also used for cross-country comparisons (Alkire et al., 2017b) and for tracking the position of specific population categories (for example, to assess poverty in children; Alkire and Sumner, 2013).

Proposing the tool for poverty index measurement, the authors rejected the idea of constructing a unique set of domains and deprivations, believing that each situa­tion of poverty measurement has its peculiarities, and the list of problems should depend on the research tasks. That made it possible to conduct similar computations, but using the data that were available for them (Alkire and Foster, 2011).

The principles of MPI construction become more evident when looking at the examples of the index (Table 3). The Poverty index, proposed for developing countries, and used in the UN work, is probably one of the most well-known cases. The index includes three domains (UNDP, 2016): education (school attainment, school attendance), health (nutrition, child mortality), and standard of living (electricity­, drinking water, sanitation, cooking fuel, having a home with dirt, sand or dung floor, assets). In this case, the weights of the domains are distributed evenly, and the threshold is set at 33.3%. The indices with a similar structure were used by the MPI authors to assess chronic poverty and poverty dynamics in different countries, for example, for chronic poverty evaluation on survey data in Chile in 1996, 2001, and 2016. In this case, the weights were also distributed evenly among the domains (with the threshold set at 33.3%; Alkire et al., 2017a). Cross-country comparisons, which cover 34 countries from different­ regions, were also conducted, with the last observations made in 2010–2012 (Alkire et al., 2017b).

The other index structure was chosen by the authors for Indonesia. The index included eight domains. The authors compared the poverty level using the different poverty cut-offs. The poverty level varied from 0.5% (criteria set at eight domains) to 83.2% (poverty line set at one domain, i.e., to be considered poor one needed to suffer from only one domain included in the analysis) (Alkire and Foster, 2008).

There is no unique index structure for developed countries; the calculations were usually performed on EU-SILC (European Union statistics on income and living conditions) data. One of the MPI variations included four domains: basic deprivations, consumption deprivations, health, and environment (Whelan et al., 2014). The alternative modification was based on six domains with equal weights: income, employment, material deprivation, education, environment, and health. The authors also emphasize the dependence of MPI share of the chosen poverty line. Finally, they choose the poverty line set at 33.3% of all the domains and estimated the MPI poverty headcount in Europe as 8.8% for 2012.

The case of MPI for the USA is also worth noting (Alkire and Foster, 2008). The index had the following structure: income, health, schooling, and health insurance. The authors also considered different poverty lines and the pover­ty headcount based on each of them. The indicator varied from 0.44% (while the poverty line was set at four domains) to 23.82% when the poverty line was set at one domain.

The examples of the MPIs described above show the huge difference in indicators for different objects. However, general ideas for all the MPIs consider­ed are quite similar. Using the different survey questions, all of them include health, education, and material well-being. Besides this, the data demonstrates the variation in poverty headcount for different poverty lines. The MPI with a structure similar to the UNDP one was calculated for Russia; however, it dates back to 2003 and the situation has changed dramatically in subsequent years (as we demonstrated for monetary poverty). Besides this, the relevance of the indicators included in the index nowadays is to some extent questionable. The index equals 0.005 and the poverty headcount achieved 1.3% (the share of the poor in accordance with official statistics for the same period was 17.4%). The alternative version of the index, introduced in 2019, was made with the correction of its structure. The calculation on the Comprehensive Monitoring of Living Conditions of the Population for 2014 included three domains: education, health, and living conditions. In accordance with this approach, the pover­ty headcount was 22.8% and the MPI was 0.100 (Kapelyuk and Ryabushkin, 2019). The attention to MPI was paid even in more recent studies; however, scholars focused on theoretical aspects of the MPI and AROPE calculation (Maleva et al., 2019).

The adepts of MPI made many attempts to construct similar indices for different countries, including developed ones. However, in most cases, they faced problems owing to the lack of totally comparable data and the existence of some specific traits of each country (as we’ve mentioned, initially, MPI was constructed for developing countries and included deprivations that are typical for them, like access to drinking water, having a ground floor, and the type of construction material—concrete, for example, in the house, etc.).

When adapting the index for the goals of different countries, many scholars tried to keep the structure of the index, using the same list of domains as the UN, but changing the set of problems. Other authors made attempts to expand the list of domains or formulate a new one, grouping the deprivations that are relevant for a certain country.1 In most cases, the research strategies were conditioned by the data available to the scholars. Taking into account the existence of several approaches to index construction, we assess the ability to use it on Russian data.

For a long time, the assessment of poverty was based on monetary indicators, namely the income and expenditures of households. But the monetary approach cannot demonstrate all the dimensions of poverty in the modern world. Besides, this methodology can sometimes be incorrect due to the limitations of sociological and statistical data, the necessity of incorporating inflation (in case of dynamic studies) and the purchasing power parity into calculations (in instances of cross-country, and sometimes cross-regional, comparison). From this point of view, the Multidimensional poverty index seems to be a better tool to provide a detailed and full description of the poor.

Alternative methods for gauging non-monetary poverty also exist (deprivation index, AROPE), however, they do not provide the ability to correct the list of deprivations included in the index and to present the relative importance of the problems included in it. This reasoning became crucial for the MPI choice.

The MPI based on Statistical Survey of Income and Participation in Social Programs and setting the threshold to get the per cent of the poor similar to the relative income poverty level results in the poverty headcount ratio at 24.8% of the Russian population. The poverty headcount ratio based on MPI is higher than the poverty level based on monetary indicators calculated on the same data­base (13.0%). The overwhelming majority of those considered to be poor were classified as poor by MPI also. The estimations are consistent with the assessment performed by other authors: the calculation on the Comprehensive Monitoring of Living Conditions of the Population treat 22.8% of the population as poor (Kapelyuk and Ryabushkin, 2019). The MPI index can never be a substitution but rather a useful addition to poverty indicators. It shows that groups with a high risk of poverty include: low-educated and low-skilled workers and older people. MPI is also higher for families living in rural areas, larger households, and households with 3 or more children. These tendencies are also fixed in the case of monetary approaches (Ovcharova, 2014).

Nevertheless, the index also widens the scope of poverty analysis adding to the poor retired and disabled people who relatively rarely figure among the poorest­ in accordance with the absolute monetary approach. This thesis validates the findings that were described in the studies based on non-monetary indicators (Tikhonova, 2014) and still classifies families with several children as poor (contrary to the results of: Institute for Social Policy, 2017).

The comparison of the poor identified in accordance with the MPI and absolute monetary approach criteria also seems to be very important. In contrast with official statistics, the MPI treats twice as many people as poor. The structure of the MPI for those who are poor by the MPI criteria only and by both the MPI and the absolute monetary approach criteria almost doesn’t differ.

The core MPI advantage is the ability of index decomposition by the domains. The data shows that the more domains are set as arbiters of poverty, the higher is the impact of severe deprivations (like food and clothing purchase). If the poverty line is set at a lower level, the impact of the domains connected with leisure, travelling, and large purchases increases.

MPI could be especially important when working on social support measures. First, it helps identify vulnerable groups that are ignored by the absolute pover­ty approach. Second, it makes possible to highlight the sharpest problems of the poor.

The MPI index presented in the study is an example of a wide range of multidimensional poverty indices, which are used to identify the poor in different countries (mainly the developing ones). The deprivations included into the index in such countries are not relevant for Russia, but the idea of combining monetary and non-monetary estimations in order to analyze poverty seems to be forward-looking. The study demonstrated that using such a methodology widens­ the list of vulnerable groups of the population, adding retired and disabled people. The credibility of the results is proved by previous poverty studies based on the analysis of deprivations, which also highlight that older and disabled people are not formally poor; however, they suffer from different non-monetary deprivations.

The MPI approach can also influence decisions concerning social policy in Russia. Nowadays, the idea of combining the monetary (i.e., low income) and non-monetary (connected primarily to property and employment status) criteria to identify the beneficiaries of social policy measures is widely discussed and even implemented in some cases (primarily in the case of new social support measures like social benefits for children aged 3–7 years old). If this idea is developed further, the MPI index will be useful for both poverty evaluation and means testing.

The core limitation of the study is the list of poverty indicators that is now defined by the questionnaire of Statistical Survey of Income and Participation in Social Programs. The next step to develop the MPI for Russia is to construct the index that will be comparable with the indices implemented in developed countries and can be used for the purposes of social policy. However, that will be possible only if the necessary data is collected.

This study was supported by the Ministry of Science and Higher Education of the Russian Federation (grant ID: 075-15-2022-325).