Poverty rate at $3.2 a day of Trinidad and Tobago shot up by 80.00% from 5.00 % in 1988 to 9.00 % in 1992. Since the 80.00% jump in 1992, poverty rate at $3.2 a day remained stable by 0.00% in 1992. 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.

Between 1987 and 1988, just three percent of the population in Central and Eastern Europe lived below the poverty level; between 1993 and 1995, this had increased to one quarter of the population. This drastic shift came as a result of communism's end in Europe, and the dissolution of the Soviet Union. In Russia alone, just two percent of the population lived in poverty in 1989, but this rose to 23.8 percent in 1998.

Jamaica Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 22.000 % in 2021. This records an increase from the previous number of 17.200 % for 2018. Jamaica Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 25.400 % from Dec 1988 (Median) to 2021, with 9 observations. The data reached an all-time high of 29.400 % in 1993 and a record low of 17.200 % in 2018. Jamaica Poverty Headcount Ratio at Societal Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jamaica – Table JM.World Bank.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;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 more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

This statistic shows the primary child care arrangements made for children aged 5 and under by working mothers who were below the poverty line in the years 1985 and 2010 in the United States. In 2010, grandparent care accounted for 23 percent of childcare arrangements made by employed mothers below 100 percent poverty.

Poverty rate at $1.9 a day of Burundi decreased by 2.11% from 75.80 % in 2013 to 74.20 % in 2020. Since the 3.06% rise in 1998, poverty rate at $1.9 a day sank by 15.30% in 2020. Population below $1.9 a day is the percentage of the population living on less than $1.9 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.

Belgium Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 9.200 % in 2021. This records an increase from the previous number of 9.000 % for 2020. Belgium Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 10.500 % from Dec 1985 (Median) to 2021, with 25 observations. The data reached an all-time high of 11.900 % in 2015 and a record low of 8.000 % in 1988. Belgium Poverty Headcount Ratio at Societal Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Belgium – Table BE.World Bank.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;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 more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Trinidad and Tobago: Poverty ratio, percent living on less than 1.90 USD a day: The latest value from 1992 is 1.3 percent, an increase from 0 percent in 1988. In comparison, the world average is 17.23 percent, based on data from 37 countries. Historically, the average for Trinidad and Tobago from 1988 to 1992 is 0.65 percent. The minimum value, 0 percent, was reached in 1988 while the maximum of 1.3 percent was recorded in 1992.

Poverty gap at $5.5 a day of Trinidad and Tobago soared by 59.15% from 7.1 % in 1988 to 11.3 % in 1992. Since the 59.15% surge in 1992, poverty gap at $5.5 a day remained constant by 0.00% in 1992. Poverty gap at $5.50 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $5.50 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.

Ivory Coast Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data was reported at 2.200 % in 2018. This records an increase from the previous number of 2.100 % for 2014. Ivory Coast Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data is updated yearly, averaging 2.470 % from Dec 1985 (Median) to 2018, with 10 observations. The data reached an all-time high of 3.050 % in 1987 and a record low of 1.660 % in 1988. Ivory Coast Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank.WDI: Social: Poverty and Inequality. This indicator shows the fraction of a country’s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the 60% median consumption but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).;Global Health Observatory. Geneva: World Health Organization; 2023. (https://www.who.int/data/gho/data/themes/topics/financial-protection);Weighted average;This indicator is related to Sustainable Development Goal 3.8.2 [https://unstats.un.org/sdgs/metadata/].

Algeria: Poverty ratio, percent living on less than 5.50 USD a day: The latest value from 2011 is 36.3 percent, a decline from 61.1 percent in 1995. In comparison, the world average is 27.77 percent, based on data from 77 countries. Historically, the average for Algeria from 1988 to 2011 is 53.67 percent. The minimum value, 36.3 percent, was reached in 2011 while the maximum of 63.6 percent was recorded in 1988.

64.60 (%) 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.

Bangladesh Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 28.100 % in 2022. This records a decrease from the previous number of 34.100 % for 2016. Bangladesh Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 44.150 % from Dec 1983 (Median) to 2022, with 10 observations. The data reached an all-time high of 48.900 % in 1988 and a record low of 28.100 % in 2022. Bangladesh Poverty Headcount Ratio at Societal Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;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 more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Algeria: Poverty ratio, percent living on less than 1.90 USD a day: The latest value from 2011 is 0 percent, a decline from 6.1 percent in 1995. In comparison, the world average is 7.26 percent, based on data from 77 countries. Historically, the average for Algeria from 1988 to 2011 is 4.17 percent. The minimum value, 0 percent, was reached in 2011 while the maximum of 6.4 percent was recorded in 1988.

Algeria DZ: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 3.700 % in 2011. This records a decrease from the previous number of 23.500 % for 1995. Algeria DZ: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 23.500 % from Dec 1988 (Median) to 2011, with 3 observations. The data reached an all-time high of 24.500 % in 1988 and a record low of 3.700 % in 2011. Algeria DZ: 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 Algeria – Table DZ.World Bank.WDI: Social: Poverty and Inequality. 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, 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).

Algeria DZ: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population data was reported at 0.400 % in 2011. This records a decrease from the previous number of 5.600 % for 1995. Algeria DZ: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population data is updated yearly, averaging 5.600 % from Dec 1988 (Median) to 2011, with 3 observations. The data reached an all-time high of 6.300 % in 1988 and a record low of 0.400 % in 2011. Algeria DZ: 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 Algeria – Table DZ.World Bank.WDI: Social: Poverty and Inequality. 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, 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 rate at $3.2 a day of Angola shot up by 40.58% from 38.20 % in 2008 to 53.70 % in 2018. Since the 5.21% slump in 2008, poverty rate at $3.2 a day soared by 40.58% in 2018. 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 Urban Institute undertook a comprehensive assessment of communities approaching decay to provide public officials with strategies for identifying communities in the early stages of decay and intervening effectively to prevent continued deterioration and crime. Although community decline is a dynamic spiral downward in which the physical condition of the neighborhood, adherence to laws and conventional behavioral norms, and economic resources worsen, the question of whether decay fosters or signals increasing risk of crime, or crime fosters decay (as investors and residents flee as reactions to crime), or both, is not easily answered. Using specific indicators to identify future trends, predictor models for Washington, DC, and Cleveland were prepared, based on data available for each city. The models were designed to predict whether a census tract should be identified as at risk for very high crime and were tested using logistic regression. The classification of a tract as a "very high crime" tract was based on its crime rate compared to crime rates for other tracts in the same city. To control for differences in population and to facilitate cross-tract comparisons, counts of crime incidents and other events were converted to rates per 1,000 residents. Tracts with less than 100 residents were considered nonresidential or institutional and were deleted from the analysis. Washington, DC, variables include rates for arson and drug sales or possession, percentage of lots zoned for commercial use, percentage of housing occupied by owners, scale of family poverty, presence of public housing units for 1980, 1983, and 1988, and rates for aggravated assaults, auto thefts, burglaries, homicides, rapes, and robberies for 1980, 1983, 1988, and 1990. Cleveland variables include rates for auto thefts, burglaries, homicides, rapes, robberies, drug sales or possession, and delinquency filings in juvenile court, and scale of family poverty for 1980 through 1989. Rates for aggravated assaults are provided for 1986 through 1989 and rates for arson are provided for 1983 through 1988.

Abstract

The Iraq Household Socio-Economic Survey conducted in 2006-2007 (IHSES 2007), was Iraq's first nationwide income and expenditure survey since 1988. Based on the model of the Living Standards Measurement Surveys, it covered more than 18,000 households, collected detailed data on all aspects of household income and expenditure and generated information on a wide variety of socio-economic indicators. It also formed the basis for updating the Consumer Price Index (CPI), from an outdated index based in 1990 to a revised index with the base year of 2007. Detailed analysis of poverty, its incidence, characteristics, determinants and consequences, was undertaken using this comprehensive survey. Under the overall guidance of the Poverty Reduction Strategy High Committee (PRSHC) and a technical sub-committee, a poverty line was defined and adopted by the Council of Ministers. Six years later, in 2012, the second round of the IHSES was completed. Learning from past and international experience on survey design, implementation and sampling, IHSES 2012 also incorporated additional modules on areas of evolving interest. It is the most comprehensive socio-economic survey as yet undertaken in Iraq.

Objectives of the survey: 1) to provide data to help measure and analyse poverty and monitor the implementation of the national strategy to alleviate poverty (issued in 2009) and update it with a new strategy 2) to provide an integrated system of data to assess the social and economic situation of families and develop indicators related to human development 3) to provide data meeting the requirements and needs of the national accounts 4) to provide detailed indicators of consumer spending and the impact of various changes in it to serve the production, consumption, export and import decision-making, 5) to provide detailed indicators of the incomes of individuals and families by source 6) to provide the data required for creating a new index record of consumer prices beyond 2012

Geographic coverage

National

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The IHSES intends to provide estimators of comparable quality for each of Iraq's 118 gadahs (districts). This implies that the sample should be explicitly stratified by gadah, with a similar sample size allocated to each gadah, regardless of its size. A sample size of 216 households per gadah is proposed, equivalent to a total sample of 25,488 households for the country. Within each gadah, the sample will be selected in two stages, as follows:

1. First, using Census Enumeration Areas (EAs) as Primary Sampling Units (PSUs), select 24 EAs with Probability Proportional to Size (PPS), using the number of households as a Measure of Size (MoS), and with implicit stratification by urban/rural and the subsequent geographical codes (nahya, mahala, village, mukataa and census block).
2. Second, using households as secondary Sampling Units (SSUs), select a cluster of 9 households by systematic, equal probability sampling (SEPS) in each of the selected EAs.

The sample frames for both stages can be developed from the 2010 Census enumeration, with no updating of the household lists. In some of the smallest gadahs, the standard PPS procedure may result in the selection of fewer than 24 EAs, with some of the larger EAs selected more than once. In those cases, two or more clusters will be taken in the EA, as needed. 2,832 EAs were selected in total. 33 of them had less than the 9 households nominally required in the second stage and were merged ex-post with neighbouring EAs.

Mode of data collection

Face-to-face [f2f]

Philippines Per Capita Poverty Threshold: Cordillera Administrative Region (CAR) data was reported at 21,770.000 PHP in 2015. This records an increase from the previous number of 19,483.000 PHP for 2012. Philippines Per Capita Poverty Threshold: Cordillera Administrative Region (CAR) data is updated yearly, averaging 13,471.500 PHP from Dec 1988 (Median) to 2015, with 10 observations. The data reached an all-time high of 21,770.000 PHP in 2015 and a record low of 5,116.000 PHP in 1988. Philippines Per Capita Poverty Threshold: Cordillera Administrative Region (CAR) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H025: Family Income and Expenditure Survey: Poverty Statistics and Proportion of Poor Population: By Regions.

Abstract

In order to develop an effective poverty reduction policies and programs, Iraqi policy makers need to know how large the poverty problem is, what kind of people are poor, and what are the causes and consequences of poverty. Until recently, they had neither the data nor an official poverty line. (The last national income and expenditure survey was in 1988.)

In response to this situation, the Iraqi Ministry of Planning and Development Cooperation established the Household Survey and Policies for Poverty Reduction Project in 2006, with financial and technical support of the World Bank. The project has been led by the Iraqi Poverty Reduction Strategy High Committee, a group which includes representatives from Parliament, the prime minister’s office, the Kurdistan Regional Government, and the ministries of Planning and Development Cooperation, Finance, Trade, Labor and Social Affairs, Education, Health, Women’s Affairs, and Baghdad University.

The Project has consisted of three components: - Collection of data which can provide a measurable indicator of welfare, i.e.the Iraq Household Socio Economic Survey (IHSES). - Establishment of an official poverty line (i.e. a cut off point below which people are considered poor) and analysis of poverty (how large the poverty problem is, what kind of people are poor and what are the causes and consequences of poverty). - Development of a Poverty Reduction Strategy, based on a solid understanding of poverty in Iraq.

Geographic coverage

National coverage Domains: Urban/rural/metropolitan; governorates

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Total sample size and stratification

The total effective sample size of the IHSES 2007 is 17,822 households. The survey was nominally designed to visit 18,144 households - 324 in each of 56 major strata. The strata are the rural, urban and metropolitan sections of each of Iraq's 18 governorates, with the exception of Baghdad, which has three metropolitan strata. The IHSES 2007 and the MICS 2006 survey intended to visit the same nominal sample. Variable q0040 indicates whether this was indeed the case.

Sampling strategy and sampling stages

The sample was selected in two stages, with groups of majals (Census Enumeration Areas) as Primary Sampling Units (PSUs) and households as Secondary Sampling Units. In the first stage, 54 PSUs were selected with probability proportional to size (pps) within each stratum, using the number of households recorded by the 1997 Census as a measure of size. In the second stage, six households were selected by systematic equal probability sampling (seps) within each PSU. To these effects, a cartographic updating and household listing operation was conducted in 2006 in all 3,024 PSUs, without resorting to the segmentation of any large PSUs. The total sample is thus nominally composed of 6 households in each of 3,024 PSUs.

Trios, teams and survey waves

The PSUs selected in each governorate (270 in Baghdad and 162 in each of the other governorates) were sorted into groups of three neighboring PSUs called trios -- 90 trios in Baghdad and 54 per governorate elsewhere. The three PSUs in each trio do not necessarily belong to the same stratum. The 12 months of the data collection period were divided into 18 periods of 20 or 21 days called survey waves. Fieldworkers were organized into teams of three interviewers, each team being responsible for interviewing one trio during a survey wave. The survey used 56 teams in total - 5 in Baghdad and 3 per governorate elsewhere. The 18 trios assigned to each team were allocated into survey waves at random. The 'time use' module was administered to two of the six households selected in each PSU: nominally the second and fifth households selected by the seps procedure in the PSU.

(For a formatted version of this field, see "IHSES sampling design and sampling weights.pdf" in "External Resources".) (For a map of Iraq's governorates and districts, see "Iraq governorates and districts.pdf" in "External Resources".)

Sampling deviation

The design did not consider the replacement of any of the randomly selected units (PSUs or households.) However, certain emergency procedures were defined to deal with security situations: If a survey team was unable to visit a trio of PSUs in the originally allocated wave, that trio was to be swapped with the trio from a randomly selected future wave that was secure at the time. If none of the still unvisited trios was secure, one of the secure trios already visited was randomly selected instead, and the team visited in each of its PSUs a new seps sample of six households - different from those interviewed when the trio was visited the first time.

This explains why the survey datasets only contain data from 2,876 of the 3,024 originally selected PSUs, whereas 55 of the PSUs contain more that the six households nominally dictated by the design.

The wave number in the survey datasets is always the nominal wave number, corresponding to the random allocation considered by the design. The effective interview dates can be found in questions 35 to 39 of the survey questionnaires.

Practice deviated from the designed procedures in two cases: In one of the governorates (Suleimaniya,) the survey was fielded for an additional two waves (waves 19 and 20,) in order to visit an extra 18 PSUs, selected from certain metropolitan areas that were not included in the original sample frame. These areas are to be analyzed jointly with the rest of metropolitan Suleimaniya, but from a sampling standpoint they constitute a de facto fourth stratum in the governorate. In another governorate (Kirkuk,) local managers used their judgment rather than the established procedures to select 12 replacement PSUs. To identify the 30 PSUs resulting from these deviations in the survey datasets, their original 'cluster numbers' (ranging from 0001 to 3024) were increased by 5000.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was designed by COSIT in continuous consultation with the WB consultants. It is composed of 18 sections covering household characteristics, government ration, housing, education, health, recreation facilities, employment, expenditure and income, transfers and risks along with the diary and time use. A pre-test of the questionnaire was conducted at an early stage of the project in a small number of households with different characteristics in some governorates.

To facilitate its administration, the questionnaire was divided into 5 physical booklets called "forms". Form 1 gathers socio economic information on household members and housing; Form 2 is to record non food expenditures, Form 3 is for employment, transfers and others;

Form 4 is the diary used to record household's food purchases during 10 days and finally Form 5 with the time use sheet administered to one third of the households in the sample.

All forms where produced in three languages: Arabic, Kurdish and English (all available in "External Resources").

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: 1. Office editing by local supervisors. 2. Based on the validation rules incorporated in the data entry program (CSPro), rejection reports were produced, based on which data are corrected. 3. Structural checking of SPSS data files. 4. Automatic fixing programme at the analysis phase. Detailed documentation of the editing of data can be found in the "Data processing guidelines" document provided as an external resource.

Response rate

The table below gives the response rates by stratum:

Stratum   Rural  Urban  Metro1 Metro2 Metro3 Total
Duhok    93.5%  99.1%  84.6%      92.4%

Mosul    100.%  99.1%  99.4%      99.5%

Sulaimaniya 98.1%  97.5%  94.8%  85.2%    95.6%

Kirkuk   82.7%  94.8%  117.%      98.3%

Erbil    97.8%  95.7%  96.0%      96.5%

Diyala   89.8%  96.9%  91.7%      92.8%

Anbar    86.4%  98.1%  98.5%      94.3%

Baghdad 99.7%  99.4%  99.1%  98.1%  96.9%  98.6%

Babylon   98.5%  98.8%  96.9%      98.0%

Kerbela   99.7%  96.9%  98.5%      98.4%

Wasit    98.5%  98.5%  97.5%      98.1%

Salah Al-Deen  97.2%  99.7%  99.4%      98.8%

Najaf    100.%  98.8%  100.%      99.6%

Qadisiya  98.1%  100.%  100.%      99.4%

Muthanna  99.7%  100.%  99.4%      99.7%

Thi-Qar   97.8%  98.8%  98.8%      98.5%

Maysan   99.7%  99.7%  100.%      99.8%

Basrah   99.7%  98.8%  98.1%      98.9%

Total    96.5%  98.4%  98.3%  94.9%  96.9%  97.6%

Notes: Baghdad has three metropolitan strata by design, whereas an additional metropolitan stratum appeared in Suleimaniya for reasons explained in the field "Deviations from Sample Design".

In Kirkuk the response rate is lower than average in the rural stratum and higher that 100 percent in the metropolitan stratum as a result of the special replacement procedures used there (certain unsecure rural PSUs were replaced by metropolitan PSUs -- see field "Deviations from Sample Design".)

Sampling error estimates

The estimation of standard errors must account for the design features explained in the "Sampling" field. (See also "IHSES sampling design and sample weights" in "External Resources.")

The following variables, included in all datasets, are needed for the estimation of standard errors:

xweight : sampling weight

xstrat: sampling stratum

xcluster: primary sampling unit

Warning: Variable 'xbeea', also present in all datasets, identifies rural, urban and metropolitan environments for tabulation purposes; it is sometimes wrongly referred to as 'stratum', but it should not be used for the estimation of sampling errors. The variable that