Poverty rate at $3.2 a day of Nepal sank by 79.37% from 44.10 % in 2010 to 9.10 % in 2022. Since the 7.97% slump in 1995, poverty rate at $3.2 a day plummeted by 89.36% in 2022. 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.

Poverty rate at $3.2 a day of Tunisia dropped by 14.29% from 2.80 % in 2015 to 2.40 % in 2021. Since the 5.10% jump in 1995, poverty rate at $3.2 a day plummeted by 92.23% in 2021. 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.

Number of poor at $1.9 a day of Algeria plummeted by 87.50% from 1.6 million persons in 1995 to 0.2 million persons in 2011. Since the 6.67% surge in 1995, number of poor at $1.9 a day sank by 87.50% in 2011. 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.

Number of poor at $1.9 a day of Tunisia plummeted by 100.00% from 0.2 million persons in 2010 to 0.0 million persons in 2015. Since the 22.22% surge in 1995, number of poor at $1.9 a day sank by 100.00% in 2015. 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.

Poverty gap at $1.9 a day of Saint Lucia plummeted by 79.53% from 12.7 % in 1995 to 2.6 % in 2016. Since the 79.53% drop in 2016, poverty gap at $1.9 a day remained constant by 0.00% in 2016. 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.

Abstract

Starting from 1995, the National Statistical Committee of the Republic of Belarus (formerly the Ministry of Statistics and Analysis) has been conducting a sample survey of 6,000 households on a yearly basis, according to the methodology complying with international standards. The survey is carried out in all regions of the country and Minsk City, covering 49 cities, towns and urban-type settlements, and 53 rural councils. Data from the latest population census is used to construct the sample.

For the survey, researchers collect information on demographic characteristics of household members, housing conditions, personal subsidiary plots, property, household expenditure and income.

The information obtained from the survey is used to analyze the influence of new social processes on living standards and to develop policies aimed at social protection of various population groups. Data is also used to compile household accounts in the system of National Accounts, to calculate consumer price index for goods and services, and to estimate the poverty level in the country.

Geographic coverage

National coverage

Analysis unit

A household is understood as the unit of the survey. For survey purposes the category "households" includes: 1) families consisting of a husband and wife with or without children or single parent families; 2) relatives living together and having a common budget (brother and sister, grandmother and grandson and etc.); 3) persons living together and having a common budget but who are not relatives, for example two friends; 4) persons living alone; 5) families consisting of two and more married couples with or without children.

Universe

The survey covers all household members excluding persons fully supported by the state, for example persons staying in homes for the elderly and the disabled, children in public care institutions, prisoners, etc. The survey also excludes foreigners living and working in Belarus on contract basis and families of military men living in military residential settlements or other restricted areas.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampled households are surveyed for a year and then are subject to replacement (rotation). To conduct the survey, households' residential addresses are sampled. Sampled population forming 0.2% of universe general population is annually arranged by the statistical office.

A household is understood as the unit of the survey. This is a person or a group of persons (mainly relatives) living together and having a common budget. Close relationship is not an obligatory condition.

Sampling was based on the territorial principle of forming a selection. In accordance with this principle, sampling involved three stages. Different territorial units of selection were used at every stage: the larger units were used at the initial stage while at the third stage the surveyed unit was equal to the selection unit. To ensure equal distribution of sample over the territory of the country, the selection was made separately for urban and rural population.

At the first stage, administrative and territorial units such as cities (including urban settlements) and rural councils were taken as the units of selection. Nineteen cities with the population above 72,000 people and 58 village councils were selected.

At the second stage, constituencies were taken as the selection units in urban areas and residential settlements were taken as the selection units in rural areas. The list of constituencies is drafted at the regional level based on the district (city) executive committees' data on the number of eligible voters. The list of voters excluded persons living in students' and workers' hostels. At the second stage maps of all selected cities and village councils were widely used when building a sample.

At the third stage, a household was taken as the unit of selection. Within the area of the selected constituencies in urban areas and residential settlements in rural areas, the lists of residential apartments and individual houses were drafted based on the data of apartment register in towns and village councils' registers in rural areas. The lists were drafted in line with the numbering of buildings within the area of the selected constituencies in urban areas and in residential settlements in rural areas.

Detailed information about the sampling is available in "Belarus Household Budget Survey Methodology" in Technical Documents (p.9-17).

Mode of data collection

Face-to-face [f2f]

Research instrument

The main components of the survey are:

1) The main interview which is intended to establish the first contact with the household, to make the list of all household members, to collect the basic information about the household in general and its individual members and to fix the date for subsequent interviews. Before an interview a household receives the initial letter signed by the Minister of Statistics and Analysis stating the date and time of the interviewer's visit. The main interview is conducted in December of the previous year;

2) Four quarterly interviews, conducted in April, July, October of the current year and January of the next year. Quarterly interview covers three previous months and summarizes the information about incomes and major expenditures of the households. At the beginning of every quarter a household is given a diary for recording expenditures during the quarter. The diary is used during quarterly interviews;

3) Four two-week diaries which are handed to a household every quarter. The diary is intended for daily recording of expenditures on foodstuffs and non-food products within 14 days as well as for recording of the consumed foodstuffs which were produced at the individual subsidiary land plot or received as a present.

Cleaning operations

The following coding systems were developed and introduced for Belarus household sample survey: 1) Coding of households covered by the survey; 2) Coding of household expenditures; 3) Coding of additional incomes and employment of household members by sectors and types of activity.

Detailed information about coding procedures is available in "Belarus Household Budget Survey Methodology" (p.22-25) in Technical Documents.

Poverty ratio at $5.5 a day of Tunisia plummeted by 42.62% from 30.5 % in 2010 to 17.5 % in 2015. Since the 1.01% improve in 1995, poverty ratio at $5.5 a day sank by 70.93% in 2015. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 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.

Abstract

Susenas is a survey designed to collect socio-demographic data in large area. The data collected were related to the fields of education, health / nutrition, housing / environmental, socio-cultural activities, consumption and household income, trips, and public opinion about the welfare of household. In 1992, Susenas data collection system has been updated, the information used to develop indicators of welfare (Welfare) contained in the module (information collected once every three years) drawn into the core (group information is collected each year).

The questions are included in the core is intended to obtain the information and to monitor the things that may change each year. It is also useful for short-term planning, as well as questions that can be associated with a question module, such as expenditures. Questions in the modules required to analyze problems that do not need to be monitored every year or analyze issues like government intervention, such as poverty and malnutrition.

Core module combined data can generate analysis to answer questions such as, whether the poor can get benefit from the appropriate educational program launched by the government (e.g., 9-year compulsory education program), who are able to take advantage of government subsidies in education, is there any kind -certain types of birth control that is more widely used by poor people than others, whether there is a link between working hours and fertility, then whether there is a link between sanitation and health status.

Since 1993 the core Susenas sample size is enlarged to generate simple statistics for the district / city level. This new development gives a new dimension to the Susenas data analyst and in that time, several counties have started to develop the indicators / statistics on the welfare of each.

Geographic coverage

National coverage, representative to the district level

Analysis unit

Household Members (Individual) and Household

Universe

In 1995 Susenas conducted in all geographic regions of Indonesia with a sample size of 206,240 households spread across urban and rural areas. Number of households to be enumerated with the core questionnaire only is 140 576 and the enumerated with core-module questionnaires 65,664.

Kind of data

Sample survey data [ssd]

Sampling procedure

Design of 1995 Susenas sampling is a two-phase sampling design. Sampling for urban area and rural area is to be conducted separately. Procedure of 1995 Susenas sampling for a district/city is as follows:

• Phase 1, from master sampling frame (MSF) of normal census block of 1995 Economic Census result (SE06) are to be selected census block nh (h = 1, for urban; h = 2, for rural) in a probability proportional to size (pps) method whereas size is the number of households from P4B census result (April 1995). For census block that has contents of more than 150 households, selection of one census sub-block in PPS-systematic is required with the size of household number of P4B census result. Household listing is conducted to all selected census blocks/sub-blocks.

• Phase 2, from every selected census blocks/sub-blocks, then, to be selected m = 16 households from the listing result systematically.

All 1995 Susenas selected households will be enumerated with core questionnaire (VSEN1995.K List) and questionnaire of socio-cultural and educational module (VSEN1995.MSBP List) in February 1995.

Mode of data collection

Face-to-face [f2f]

Poverty ratio at $3.2 a day of Tunisia sank by 67.39% from 9.2 % in 2010 to 3.0 % in 2015. Since the 3.93% upward trend in 1995, poverty ratio at $3.2 a day plummeted by 90.54% in 2015. 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.

Poverty ratio at $1.9 a day of Saint Lucia plummeted by 86.74% from 34.7 % in 1995 to 4.6 % in 2016. Since the 86.74% drop in 2016, poverty ratio at $1.9 a day remained constant by 0.00% in 2016. 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.

Austria AT: Poverty Gap at $1.90 a Day: 2011 PPP: % data was reported at 0.500 % in 2019. This stayed constant from the previous number of 0.500 % for 2018. Austria AT: Poverty Gap at $1.90 a Day: 2011 PPP: % data is updated yearly, averaging 0.250 % from Dec 1987 (Median) to 2019, with 22 observations. The data reached an all-time high of 1.000 % in 1995 and a record low of 0.000 % in 2006. Austria AT: Poverty Gap at $1.90 a Day: 2011 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Austria – Table AT.World Bank.WDI: Social: Poverty and Inequality. 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.; ; World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from around 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Poverty ratio at $5.5 a day of Saint Lucia plummeted by 76.67% from 85.3 % in 1995 to 19.9 % in 2016. Since the 76.67% drop in 2016, poverty ratio at $5.5 a day remained constant by 0.00% in 2016. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 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.

Poverty ratio at $1.9 a day of Sri Lanka plummeted by 52.63% from 1.9 % in 2012 to 0.9 % in 2016. Since the 2.15% rise in 1995, poverty ratio at $1.9 a day sank by 90.53% in 2016. 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.

Paraguay PY: Poverty Gap at $1.90 a Day: 2011 PPP: % data was reported at 0.300 % in 2016. This records a decrease from the previous number of 0.400 % for 2015. Paraguay PY: Poverty Gap at $1.90 a Day: 2011 PPP: % data is updated yearly, averaging 1.700 % from Dec 1990 (Median) to 2016, with 20 observations. The data reached an all-time high of 5.300 % in 1995 and a record low of 0.300 % in 2016. Paraguay PY: Poverty Gap at $1.90 a Day: 2011 PPP: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Paraguay – Table PY.World Bank.WDI: Poverty. 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.; ; 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.

Abstract

The 1997 Family Income and Expenditute Survey had the following objectives: 1. to gather data on family income and family living expenditures and related information affecting income and expenditure levels and patterns in the Philippines;

1. to determine the sources of income and income distribution, levels of living and spending patterns, and the degree of inequality among families;

2. to provide benchmark information to update weights in the estimation of consumer price index (CPI); and

3. to provide inputs in the estimation of the country's poverty threshold and incidence.

Geographic coverage

National coverage

Analysis unit

Household Consumption expenditure item Income by source

Universe

The 1997 FIES has as its target population, all households and members of households nationwide. A household is defined as an aggregate of persons, generally but not necessarily bound by ties of kinship, who live together under the same roof and eat together or share in common the household food. Household membership comprises the head of the household, relatives living with him such as his/her spouse, children, parent, brother/sister, son-in-law/daughter-in-law, grandson/granddaughter and other relatives. Household membership likewise includes boarders, domestic helpers and non-relatives. A person who lives alone is considered a separate household.

Institutional population is not within the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design of the 1997 FIES adopted that of the Integrated Survey of Households (ISH). Starting July 1996, the sampling design of the ISH uses the new master sample design. The multi-stage sampling design of the master sample consists of 3,416 PSUs in the expanded sample for provincial level estimates with a sub-sample of 2,247 PSUs designated as the core master sample for regional levels estimates. The 1997 FIES was based on the expanded sample.

Domains The urban and rural areas of each province are the principal domains for the survey. In addition, areas with 150,000 or more population as of 1995 Census of Population (POPCEN) are also domains of the survey with rural and urban dimensions. The domains for the new master sample are similar to that of the previous ISH design with an addition of 23 newly created domains.

The multi-stage sampling design of the master sample involves the selection of the sample barangays for the first stage, selection of sample enumeration areas for the second stage, and the selection of sample households for the third stage in each stratum for every domain.

The frame for the first stage and second stages of sample selection were based mainly on the results of the 1995 POPCEN. The 1995 list of barangays with the household and population counts is used in the first stage of sample selection. The stratification of barangays included in the frame, however are based on the 1990 Census of Population and Housing (CPH) and other administrative reports from the field offices of NSO. An enumeration area (EA) is a physical delineated portion of the barangay. For barangays that were not divided into EAs, the barangay was treated as an EA.

The enumeration areas which constitutes the secondary sampling units are those that were formed during the 1995 POPCEN. The sample barangays were selected systematically with probability proportional to size from the list of barangays that were implicitly stratified.

The frame for the third stage of sample selection is the list of households from the 1995 POPCEN. The selection of sample households for the third stage was done systematically from the 1995 POPCEN List of Households.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire has five main parts consisting of the following: Part I. Identification and Other Information (Geographic Identification, Other Information and Particulars about the Family)

Part II. Expenditures and Other Disbursements Section A. Food, Alcoholic Beverages and Tobacco Section B. Fuel, Light and Water, Transportation and Communication, Household Operations Section C. Personal Care and Effects, Clothing Footwear and Other Wear Section D. Education, Recreation, and Medical Care Section E. Furnishings and Equipment Section F. Taxes Section G. Housing, House Maintenance and Minor Repairs Section H. Miscellaneous Expenditures Section I. Other Disbursements

Part III. Income Section A. Salaries and Wages from Employment Section B. Net Share of Crops, Fruits and Vegetables Produced and/or Livestock and Poultry Raised by Other Households Section C. Other Sources of Income Section D. Other Receipts Section E. Family Sustenance Activities

Part IV. Entrepreneurial Activities Section A1. Crop Farming and Gardening Section A2. Livestock and Poultry Raising Section A3. Fishing Section A4. Forestry and Hunting Section A5. Wholesale and Retail Section A6. Manufacturing Section A7. Community, Social, Recreational and Personal Services Section A8. Transportation, Storage and Communication Services Section A9. Mining and Quarrying Section A10. Construction Section A11. Entrepreneurial Activities Not Elsewhere Classified

Part V: Health - Care Section A. Health - care Expenditures Section B. Health Insurance

Cleaning operations

The 1997 FIES questionnaire contains about 800 data items and a guide for comparing income and expenditures. The questionnaires were subjected to a rigorous manual and machine edit checks for completeness, arithmetic accuracy, range validity and internal consistency.

The electronic data processing system developed since 1985 FIES by the Information System Development Section was used in processing the 1997 FIES with few modifications.

There were thirteen major steps in the machine processing and these are as follows: 1. Data entry and verification 2. Structural editing (minor edit) 3. Edit list verification/correction 4. Update 5. Completeness check 6. Completeness check list verification/correction 7. Identification verification 8. Identification verification extraction of summary file for preliminary results 9. Matching of visit records 10. Expansion 11. Tabulations 12. Generation of CPI weights 13. Variance analysis

Steps 1 to 8 were performed right after each visit while the remaining steps were carried out upon completion of the data collection for the first and second visits.

Steps 1 to 7 were implemented at the regional office while the concluding steps were handled at the Central Office.

Response rate

The response rate for the 1997 FIES is 96.4%.

Sampling error estimates

As in all surveys, two types of non-response were encountered in the 1997 FIES: Interview non-response and item non-response. Interview non-response refers to a sample household that could not be interviewed. Since the survey requires that the sample households be interviewed in both visits, households that transferred to another dwelling unit, temporarily away, on vacation, not at home, household unit demolished, destroyed by fire/typhoon and refusal to be interviewed in the second visit contributed to the number of interview non-response cases.

Item non-response, or the failure to obtain responses to particular survey items, resulted from factors such as respondents being unaware of the answer to a particular question, unwilling to provide the requested information or ENs' omission of questions during the interview. Deterministic imputation was done to address item nonresponse. This imputation is a process in which proper entry for a particular missing item was deduced from other items of the questionnaire where the non-response item was observed. Notes and remarks indicated in the questionnaire were likewise used as basis for imputation.

Egypt EG: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data was reported at 61.900 % in 2015. This records a decrease from the previous number of 70.300 % for 2012. Egypt EG: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data is updated yearly, averaging 73.900 % from Dec 1990 (Median) to 2015, with 8 observations. The data reached an all-time high of 80.000 % in 1995 and a record low of 61.900 % in 2015. Egypt EG: Poverty Headcount Ratio at $5.50 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 Egypt – Table EG.World Bank: Poverty. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 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.

Ukraine UA: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 0.500 % in 2016. This stayed constant from the previous number of 0.500 % for 2015. Ukraine UA: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 0.700 % from Dec 1995 (Median) to 2016, with 17 observations. The data reached an all-time high of 22.700 % in 1996 and a record low of 0.100 % in 2014. Ukraine UA: Poverty Headcount Ratio at $3.20 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 $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.; ; 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.

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.

Ethiopia ET: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data was reported at 84.700 % in 2015. This records a decrease from the previous number of 93.100 % for 2010. Ethiopia ET: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data is updated yearly, averaging 95.500 % from Dec 1995 (Median) to 2015, with 5 observations. The data reached an all-time high of 97.300 % in 1999 and a record low of 84.700 % in 2015. Ethiopia ET: Poverty Headcount Ratio at $5.50 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 Ethiopia – Table ET.World Bank.WDI: Poverty. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 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.

Germany DE: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data was reported at 0.200 % in 2018. This stayed constant from the previous number of 0.200 % for 2017. Germany DE: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data is updated yearly, averaging 0.200 % from Dec 1991 (Median) to 2018, with 28 observations. The data reached an all-time high of 0.500 % in 1995 and a record low of 0.200 % in 2018. Germany DE: Poverty Headcount Ratio at $5.50 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 Germany – Table DE.World Bank.WDI: Social: Poverty and Inequality. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 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, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from around 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).