This statistic shows the poverty headcount ratio at national poverty lines in Ukraine from 2009 to 2019. In 2019, the poverty headcount ratio at national poverty lines in Ukraine amounted to 1.1 percent.

Ukraine UA: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population data was reported at 0.100 % in 2016. This stayed constant from the previous number of 0.100 % for 2015. Ukraine UA: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population data is updated yearly, averaging 0.100 % from Dec 1995 (Median) to 2016, with 17 observations. The data reached an all-time high of 5.400 % in 1996 and a record low of 0.000 % in 2014. Ukraine UA: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ukraine – Table UA.World Bank: Poverty. Poverty headcount ratio at $1.90 a day is the percentage of the population living on less than $1.90 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Slovakia was the European Union (EU) country with the largest expected increase in poverty due to the Russia-Ukraine war that began in February 2022. According to the estimates, the share of the Slovak population at risk of poverty was estimated to increase by 4.3 percent as a consequence of economic issues caused by the invasion, such as inflation. Estonia was projected the second-highest poverty increase, at 3.7 percent of residents.

Ukraine UA: Income Share Held by Fourth 20% data was reported at 22.400 % in 2016. This stayed constant from the previous number of 22.400 % for 2015. Ukraine UA: Income Share Held by Fourth 20% data is updated yearly, averaging 22.500 % from Dec 1992 (Median) to 2016, with 19 observations. The data reached an all-time high of 23.200 % in 1992 and a record low of 21.900 % in 1995. Ukraine UA: Income Share Held by Fourth 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ukraine – Table UA.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Over nine percent of children in Russia were estimated to fall into poverty additionally due to the economic crisis caused by the Russian invasion of Ukraine, based on the analysis from 2022. Russia had the most children among Eastern European and Central Asian countries. Furthermore, five percent of the Ukrainian child population was expected to experience poverty as a result of the economic shock. The economic decline caused by the war was also projected to increase adult poverty across the region, though to a lesser extent.

0,20 (%) in 2020. Population below $3.1 a day is the percentage of the population living on less than $3.1 a day at 2005 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

The index provides the only comprehensive measure available for non-income poverty, which has become a critical underpinning of the SDGs. Critically the MPI comprises variables that are already reported under the Demographic Health Surveys (DHS) and Multi-Indicator Cluster Surveys (MICS) The resources subnational multidimensional poverty data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa (2023)

Nearly 2.5 million people in Ukraine were estimated to be facing insufficient food consumption as of January 28, 2025. The number of people in Ukrainian households with a food consumption score (FCS) of less than 42 increased from the end of the previous month.

0,2 (%) in 2019. Poverty headcount ratio at $3.20 a day is the percentage of the population living on less than $3.20 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

Ukraine UA: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 25.000 % in 2016. This records a decrease from the previous number of 25.500 % for 2015. Ukraine UA: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 27.000 % from Dec 1992 (Median) to 2016, with 19 observations. The data reached an all-time high of 39.300 % in 1995 and a record low of 24.000 % in 2014. Ukraine UA: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ukraine – Table UA.World Bank.WDI: Poverty. Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

0,0 (%) in 2019. Poverty gap at $1.90 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $1.90 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘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 definition'.

The poverty headcount ratio at national poverty lines in Belarus decreased to 3.9 percent compared to the previous year. This marks the lowest poverty headcount ratio during the observed period. These figures refer to the share of the population living below the poverty line, based on parameters set by relevant authorities.Find more key insights for the poverty headcount ratio at national poverty lines in countries like Ukraine and Moldova.

Abstract

The Household Living Conditions Survey 2011 provides information on poverty analysis in Ukraine. The results of the household survey are used in Ukraine for analyzing various issues, among which poverty, access to material benefits, subjective self-evaluation by households of their level of well-being are of special priority. The data obtained through this survey makes it possible to carry out methodologically comparative poverty studies using almost all above criteria.

The data can be used to analyze the following: - social-demographic characteristics of household members; - expenditures and consumption; - income and other resources, including those coming from subsidiary farming; - housing conditions; - availability of durable goods; - evaluation of health conditions and access to medical goods and services; - evaluation of well-being level and economic expectations; - access to certain goods and services; - access to information and communication technologies.

Geographic coverage

National, except some settlements within the territories suffered from the Chernobyl disaster.

Analysis unit

• Households,
• Individuals.

A household is a totality of persons who jointly live in the same residential facilities of part of those, satisfy all their essential needs, jointly keep the house, pool and spend all their money or portion of it. These persons may be relatives by blood, relatives by law or both, or have no kinship relations. A household may consist of one person (Law of Ukraine "On Ukraine National Census of Population," Article 1). As only 0.50% households have members with no kinship relations (0.65% total households if bachelors are excluded), the contemporary concepts "household" and "family" are very close.

Universe

Whole country, all private households. The survey does not cover collective households, foreigners temporarily living in Ukraine as well as the homeless.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey covers only private households. The sample does not include marginal population groups (individuals without permanent place of residence, etc.). Annual full rotation of respondents is used. Every five years survey territories are rotated. The territorial sampling excludes residential areas that are located in the exclusion and compulsory resettlement zone affected by radioactive contamination as a result of the Chernobyl nuclear power station accident. Sampling is done by stratified multistage probability sampling methods. The sampling methodology ensures that each household has a certain non-zero probability of being selected.

Mode of data collection

Face-to-face [f2f]

Research instrument

The household living conditions survey includes three components and uses various survey tools to obtain information.

I. Collecting general data on a household - basic interview. Interviewing of households takes place at the survey commencement stage based on the adequate questionnaire program on general basic household features: household composition, housing facilities, availability and use of land plots, cattle and poultry, and also characteristics of household members: anthropometric data, education, employment status, etc. In addition, while interviewing, the interviewer completes a household composition check card to trace any changes during the entire survey period.

II. Observation of household expenditures and incomes over a quarter. For the observation, two survey tools are used: Weekly diary of current expenditures, which is completed directly by a household twice a quarter. In the diary respondents (households) record all daily expenditures in details (e.g. for purchased foodstuffs - product description, its weight and value, and place of purchase). In addition, a household puts into the diary information on consumption of products produced in private subsidiary farming or received as a gift.

Households are evenly distributed among rotation groups, who complete diaries in different week days of every quarter. Assuming that the two weeks data are intrinsic for the entire quarter, the single time period of data processing (quarter) is formed by means of multiplying diary data by ratio 6.5 (number of weeks in a quarter divided on the number of weeks when diary records were made). Inclusion of foodstuffs for long-time consumption is done based on quarterly interview data.

Quarterly questionnaire is used in quarterly interviewing of households in the first month following the reporting quarter. At this state, we collect data on large and irregular expenditures, in particular those relating to the purchase of foodstuffs for long-time consumption (e.g. sacks, etc.), and also data on household incomes. Since recalling all incomes and expenditures made in a quarter is uneasy, households make records during a quarter in a special 'Quarterly expenditures log'.

The major areas for quarterly observation are the following: - structure of consumer financial expenditures for goods and services; - structure of other expenditures (material aid to other households, expenditures for private subsidiary farming, purchase of real estate, construction and major repair of housing facilities and outbuildings, accumulating savings, etc); - importance of private subsidiary farming for household welfare level (receipt and use of products from private subsidiary farming for own consumption, financial income from sales of such products, etc.); - structure of income and other financial sources of a household. We separately study the income of every individual household member (remuneration of labor, pension, scholarship, welfare, etc.) and the income in form payments to a household as a whole (subsidies for children, aid of relatives and other persons, income from - sales of real estate and property, housing and utility subsidies, use of savings, etc.).

III. Single-time topical interviews Questionnaires are used for quarterly interviewing.

Quarterly topical interviews covered the following: - household expenditures for construction and repair of housing facilities and outbuilding; - availability in a household of durable goods; - assessment by households members of own health and accessibility of selected medical services; - self-assessment by a household of adequacy of its income; - a household's access to Internet.

In 2022, the poverty headcount ratio in Western Balkans was estimated at 15.9 percent. In other words, this share of the population in the region lived on less than 6.85 U.S. dollars per day in revised 2017 purchasing power parity (PPP) terms. The war in Ukraine and subsequent energy and food price growth negatively affected poverty rates in the region. The country with the highest poverty rate in the region in 2017 was Kosovo.

Ukraine UA: Income Share Held by Third 20% data was reported at 17.900 % in 2016. This records an increase from the previous number of 17.800 % for 2015. Ukraine UA: Income Share Held by Third 20% data is updated yearly, averaging 17.600 % from Dec 1992 (Median) to 2016, with 19 observations. The data reached an all-time high of 18.000 % in 2014 and a record low of 15.400 % in 1995. Ukraine UA: Income Share Held by Third 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ukraine – Table UA.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

0,0 (%) in 2019. Poverty gap at $3.20 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $3.20 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence.

Abstract

The World Bank Group is interested in gauging the views of clients and partners who are either involved in development in Ukraine or who observe activities related to social and economic development. The following survey will give the World Bank Group's team that works in Ukraine, greater insight into how the Bank's work is perceived. This is one tool the World Bank Group uses to assess the views of its stakeholders, and to develop more effective strategies that support development in Ukraine. A local independent firm was hired to oversee the logistics of this survey.

This survey was designed to achieve the following objectives: - Assist the World Bank Group in gaining a better understanding of how stakeholders in Ukraine perceive the Bank Group; - Obtain systematic feedback from stakeholders in Ukraine regarding: · Their views regarding the general environment in Ukraine; · Their overall attitudes toward the World Bank Group in Ukraine; · Overall impressions of the World Bank Group's effectiveness and results, knowledge work and activities, and communication and information sharing in Ukraine; · Perceptions of the World Bank Group's future role in Ukraine. - Use data to help inform Ukraine country team's strategy.

Geographic coverage

Kyiv, Oblast Center, Other city

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank Group in Ukraine

Kind of data

Sample survey data [ssd]

Sampling procedure

In October 2013, 321 stakeholders of the World Bank Group in Ukraine were invited to provide their opinions on the World Bank Group's assistance to the country by participating in a country survey. Participants in the survey were drawn from the office of the President, Prime Minister; office of a minister; office of a parliamentarian; ministries, ministerial departments, or implementation agencies; consultants/contractors working on World Bank Group-supported projects/ programs; project management units (PMUs) overseeing implementation of a project; local government officials; bilateral and multilateral agencies; private sector organizations; private foundations; the financial sector/private banks; NGOs; community based organizations; the media; independent government institutions; trade unions; faith-based groups; academia/research institutes/think tanks; the judiciary branch; and other organizations.

Mode of data collection

Mail Questionnaire [mail]

Research instrument

The Questionnaire consists of 8 sections:

A. General Issues Facing Ukraine: Respondents were asked to indicate whether Ukraine is headed in the right direction, what they thought were the top three most important development priorities in the country, which areas would contribute most to reducing poverty and generating economic growth in Ukraine, and how "shared prosperity" would be best achieved in Ukraine.

B. Overall Attitudes toward the World Bank Group (WBG): Respondents were asked to rate their familiarity with the World Bank Group, the WBG's effectiveness in Ukraine, WBG staff preparedness to help Ukraine solve its development challenges, their agreement with various statements regarding the WBG's work, and the extent to which the WBG is an effective development partner. Respondents were asked to indicate the WBG's greatest values and weaknesses, the most effective instruments in helping reduce poverty in Ukraine, with which stakeholder groups the WBG should collaborate more, in which sectoral areas the WBG should focus most of its resources (financial and knowledge services), and to what reasons respondents attributed failed or slow reform efforts.

C. World Bank Group's Effectiveness and Results: Respondents were asked to rate the extent to which the WBG's work helps achieve development results in Ukraine, the extent to which the WBG meets Ukraine's needs for knowledge services and financial instruments, and the WBG's level of effectiveness across twenty one development areas, such as economic growth, governance, private sector development, education, and job creation.

D. The World Bank Group's Knowledge Work and Activities: Respondents were asked to indicate how frequently they consult WBG's knowledge work and activities and to rate the effectiveness and quality of the WBG's knowledge work and activities, including how significant of a contribution it makes to development results and its technical quality.

E. Working with the World Bank Group: Respondents were asked to rate their level of agreement with a series of statements regarding working with the WBG, such as the WBG's "Safeguard Policy" requirements being reasonable, the WBG imposing reasonable conditions on its lending, disbursing funds promptly, and providing effective implementation support.

F. The Future Role of the World Bank Group in Ukraine: Respondents were asked to indicate what the WBG should do to make itself of greater value in Ukraine, and which services the WBG should offer more of in the country.

G. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, how they prefer to receive information from the WBG, and their usage and evaluation of the WBG's websites. Respondents were also asked about their awareness of the WBG's Access to Information policy, past information requests from the WBG, and their level of agreement that they use more data from the WBG as a result of the WBG's Open Data policy.

H. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the WBG, their exposure to the WBG in Ukraine, which WBG agencies they work with, and their geographic location.

Questionnaires were in English and Ukrainian

Response rate

A total of 169 stakeholders participated in the survey (53% response rate).

0,0 (Millionen) in 2019. Number of people, in millions, living on less than $1.90 a day at 2011 PPP is calculated by multiplying the poverty rate and the population. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

Over the past 30 years, there has been an almost constant reduction in the poverty rate worldwide. Whereas nearly 38 percent of the world's population lived on less than 2.15 U.S. dollars in terms of 2017 Purchasing Power Parity (PPP) in 1990, this had fallen to 8.7 percent in 2022. This is despite the fact that the world's population was growing over the same period. However, there was a small increase in the poverty rate during the COVID-19 pandemic in 2020 and 2021, when thousands of people became unemployed overnight. Moreover, rising cost of living in the aftermath of the pandemic and spurred by the Russian invasion of Ukraine in 2022 meant that many people were struggling to make ends meet. Poverty is a regional problem Poverty can be measured in relative and absolute terms. Absolute poverty concerns basic human needs such as food, clothing, shelter, and clean drinking water, whereas relative poverty looks at whether people in different countries can afford a certain living standard. Most countries that have a high percentage of their population living in absolute poverty, meaning that they are poor compared to international standards, are regionally concentrated. African countries are most represented among the countries in which poverty prevails the most. In terms of numbers, Sub-Saharan Africa and South Asia have the most people living in poverty worldwide. Inequality on the rise How wealth, or the lack thereof, is distributed within the global population and even within countries is very unequal. In 2022, the richest one percent of the world owned almost half of the global wealth, while the poorest 50 percent owned less than two percent in the same year. Within regions, Latin America had the most unequal distribution of wealth but this phenomenon is present in all world regions.