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).

Historical dataset showing Bangladesh poverty rate by year from 1983 to 2022.

Bangladesh BD: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population data was reported at 14.300 % in 2016. This records a decrease from the previous number of 19.200 % for 2010. Bangladesh BD: Poverty Headcount Ratio at $1.90 a Day: 2011 PPP: % of Population data is updated yearly, averaging 34.200 % from Dec 1983 (Median) to 2016, with 9 observations. The data reached an all-time high of 43.500 % in 1991 and a record low of 14.300 % in 2016. Bangladesh BD: 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 Bangladesh – Table BD.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 Bangladesh sank by 54.14% from 44.70 % in 2016 to 20.50 % in 2022. Since the 0.39% upward trend in 1991, poverty rate at $3.2 a day plummeted by 73.65% 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.

Bangladesh BD: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data was reported at 35.200 % in 2010. This records a decrease from the previous number of 43.800 % for 2005. Bangladesh BD: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data is updated yearly, averaging 43.800 % from Dec 2000 (Median) to 2010, with 3 observations. The data reached an all-time high of 52.300 % in 2000 and a record low of 35.200 % in 2010. Bangladesh BD: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural 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. Rural poverty headcount ratio is the percentage of the rural population living below the national poverty lines.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

Poverty rate of Bangladesh plummeted by 23.65% from 25.1 % in 2005 to 19.2 % in 2010. Since the 0.57% climb in 1991, poverty rate sank by 55.88% in 2010. Population below $1.90 a day is the percentage of the population living on less than $1.90 a day at 2011 international prices.

Abstract

The main objective of the Bangladesh Poverty and Groundwater Salinity Survey (BPGSS) 2016 is to understand the linkages between groundwater salinity and poverty in coastal areas in Bangladesh. It is also to assess the extent to which high water salinity might be associated with poor health outcomes among women and children, and identify potential coping and adaptation mechanisms, which households might be using to address high water salinity in these areas.

Geographic coverage

Regional coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING PROCEDURE The Bangladesh Poverty and Groundwater Salinity Survey 2016 collected data from a total of 1,500 households in three sub-districts or upazilas in Bangladesh - 500 households in each upazila distributed across 50 primary sampling units (PSUs). The three upazilas selected for this study are the following: (i) Taltoli upazila in the Barguna district of the Barisal division; (ii) Morrelganj upazila in the Bagerhat district of the Khulna division; and (iii) Shyamnagar upazila in the Satkhira district in the Khulna division. Each upazila was allocated an equal size of households in order to get poverty estimates of similar precision. The sampling frame consists of a list of all rural villages developed by the Bangladesh Bureau of Statistics (BBS) based on the Census Enumeration Areas (CEAs) constructed for the 2011 Census of Population and Housing. PSUs are constructed by dividing rural villages into listing blocks or Enumeration Areas (EAs) of around 50 households each and then randomly selecting one block for listing.

The three upazilas included in this study where selected based on discussion with a water salinity expert in Bangladesh and practical considerations using a two-stage procedure. In the first stage, we combined upazila level poverty data from the official 2010 Bangladesh Poverty Maps with upazila level information on groundwater salinity collected by the Bangladesh Water Development Board (BWDB) with support from the Institute of Water Modelling (IWM). Using these combined dataset, we classified all 146 upazilas in coastal areas in four groups: (i) high water salinity and high poverty rate; (ii) high water salinity and low poverty rates; (iii) low water salinity and high poverty rate; (iv) low water salinity and low poverty rates. Figure 1 shows the spatial distribution of coastal area upazilas based on these four categories. In the second stage, we selected one upazila from each of the first three categories as focal areas for this study after discussion with a groundwater expert on availability of other water-supply options (e.g. managed aquifer recharge) and practical considerations. This categorization of upazilas also serve as our three sampling strata - high water salinity and high poverty rate, high water salinity and low poverty rates, and low water salinity and high poverty rate.

Mode of data collection

Face-to-face [f2f]

Research instrument

The household questionnaire is available in Bengali and English under the Related Materials tab.

Cleaning operations

Data entry and editing was done by Survey CTO.

Bangladesh BD: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data was reported at 84.200 % in 2016. This records a decrease from the previous number of 87.600 % for 2010. Bangladesh BD: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data is updated yearly, averaging 92.600 % from Dec 1983 (Median) to 2016, with 9 observations. The data reached an all-time high of 97.100 % in 1983 and a record low of 84.200 % in 2016. Bangladesh BD: 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 Bangladesh – Table BD.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).

Gathered for the GAFSP Open Data Services activity. This file contains summary statistics of poverty by division 2016. Data collected by the Bangladesh Bureau of Statistics BBS and published in the "Preliminary Report on Household Income and Expenditure Survey 2016".

Bangladesh Multidimensional Poverty Headcount Ratio: World Bank: % of total population data was reported at 6.600 % in 2022. This records a decrease from the previous number of 20.500 % for 2016. Bangladesh Multidimensional Poverty Headcount Ratio: World Bank: % of total population data is updated yearly, averaging 20.500 % from Dec 2010 (Median) to 2022, with 3 observations. The data reached an all-time high of 31.300 % in 2010 and a record low of 6.600 % in 2022. Bangladesh Multidimensional Poverty Headcount Ratio: World Bank: % of total 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 multidimensional poverty headcount ratio (World Bank) is the percentage of a population living in poverty according to the World Bank's Multidimensional Poverty Measure. The Multidimensional Poverty Measure includes three dimensions – monetary poverty, education, and basic infrastructure services – to capture a more complete picture of poverty.;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).

Bangladesh BD: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data was reported at 21.300 % in 2010. This records a decrease from the previous number of 28.400 % for 2005. Bangladesh BD: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban Population data is updated yearly, averaging 28.400 % from Dec 2000 (Median) to 2010, with 3 observations. The data reached an all-time high of 35.200 % in 2000 and a record low of 21.300 % in 2010. Bangladesh BD: Poverty Headcount Ratio at National Poverty Lines: Urban: % of Urban 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. Urban poverty headcount ratio is the percentage of the urban population living below the national poverty lines.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

Poverty ratio at $3.2 a day of Bangladesh dropped by 12.83% from 60.0 % in 2010 to 52.3 % in 2016. Since the 0.97% upward trend in 1991, poverty ratio at $3.2 a day plummeted by 37.37% in 2016. 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.

Bangladesh BD: Poverty Headcount Ratio at $2.15 a Day: 2017 PPP: % of Population data was reported at 5.000 % in 2022. This records a decrease from the previous number of 13.500 % for 2016. Bangladesh BD: Poverty Headcount Ratio at $2.15 a Day: 2017 PPP: % of Population data is updated yearly, averaging 32.650 % from Dec 1983 (Median) to 2022, with 10 observations. The data reached an all-time high of 41.900 % in 1991 and a record low of 5.000 % in 2022. Bangladesh BD: Poverty Headcount Ratio at $2.15 a Day: 2017 PPP: % 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. Poverty headcount ratio at $2.15 a day is the percentage of the population living on less than $2.15 a day at 2017 purchasing power adjusted 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 more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

14.3 (%) 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.

Description for the Dataset

Title: Comprehensive Socio-Economic and Environmental Dataset of Bangladesh 1980-2023

Description:
This dataset provides an extensive overview of Bangladesh's socio-economic, demographic, and environmental indicators over time. It encompasses a wide array of features, including literacy rates, population statistics, economic growth metrics, trade balances, environmental indicators, healthcare spending, and poverty rates. The dataset aims to facilitate research and analysis on Bangladesh's development trends, policy impacts, and sustainability challenges.

Key Features: - Population and Demographics: Includes total population, growth rates, population density, birth/death rates, infant mortality rates, fertility rates, urban and rural population distributions, and migration statistics.
- Economic Indicators: GDP, GNP, GNI, trade balances, export and import metrics, inflation rates, unemployment rates, labor force participation, and foreign direct investment.
- Poverty and Social Metrics: National, rural, and urban poverty rates, literacy rates, healthcare spending, and maternal mortality rates.
- Environmental Metrics: Tree cover loss, carbon emissions, renewable energy usage, deforestation causes, and greenhouse gas emissions.
- Infrastructure and Development: Access to electricity and clean water, arable land, private vehicles, and tourism spending.
- Crime and Defense: Crime rates, homicide rates, and military spending.
- Education: Education spending as a percentage of GDP and youth unemployment rates.

Intended Use:
This dataset is designed for data analysis, trend forecasting, and machine learning applications. It is suitable for researchers, policymakers, and analysts studying socio-economic development, environmental sustainability, and public policy in Bangladesh.

Source and Methodology:
The dataset aggregates publicly available statistics from reliable sources, including government reports, international organizations, and research publications. It has been curated and processed to ensure consistency and usability.

Potential Applications:
- Analyzing the impact of socio-economic policies on literacy and poverty rates.
- Forecasting demographic and economic growth trends.
- Exploring the relationship between environmental changes and economic activities.
- Studying the effects of urbanization and migration on rural-urban dynamics.

License:
CC BY-SA 4.0

Keywords:
Bangladesh, Socio-Economic Indicators, Environmental Metrics, Development Trends, Poverty Rates, Literacy Rates, GDP, Carbon Emissions, Renewable Energy, Migration.

Bangladesh has continued to improve access to education and educational attainment. Gains have been equitable, reducing disparities by gender, wealth, and geography. Yet progress is still needed at higher education levels, and there are still persistent gaps between the poor and rich and across districts. Gains are partly the result of Government of Bangladesh (GOB) efforts to improve education outcomes, but also reflect increased private spending by households. GOB education spending is still low compared to other countries in the region and presents large variation across the territory, which is not correlated with education outcomes and internal efficiency indicators. Only when public spending translates into lower student-to-teacher ratios do outcomes seem to improve, but those ratios remain inadequate compared to other countries and unevenly distributed across districts. Focusing on higher quality spending rather than increasing overall budgets will be a priority for further progress. Stipend programs help with the progressivity of the system at the primary level. However, at the secondary level, there is still significant room to improve the progressivity of these benefits. Finally, addressing norms and expectations around the benefits of schooling can be an important avenue to increase school attendance. About four in ten secondary school-age children out of school report lack of interest or being too old to go back as their main reasons for not attending school; three in ten females cite family chores and marriage as reasons for not attending.

Abstract

The 2018 Dhaka Low Income Area Gender, Inclusion, and Poverty (DIGNITY) survey attempts to fill in the data and knowledge gaps on women's economic empowerment in urban areas, specifically the factors that constrain women in slums and low-income neighborhoods from engaging in the labor market and supplying their labor to wage earning or self-employment. While an array of national-level datasets has collected a wide spectrum of information, they rarely comprise all of the information needed to study the drivers of Female Labor Force Participation (FLFP). This data gap is being filled by the primary data collection of the specialized DIGNITY survey; it is representative of poor urban areas and is specifically designed to address these limitations. The DIGNITY survey collected information from 1,300 urban households living in poor areas of Dhaka in 2018 on a range of issues that affect FLFP as identified through the literature. These range from household composition and demographic characteristics to socioeconomic characteristics such as detailed employment history and income (including locational data and travel details); and from technical and educational attributes to issues of time use, migration history, and attitudes and perceptions.

The DIGNITY survey was designed to shed light on poverty, economic empowerment, and livelihood in urban areas of Bangladesh. It has two main modules: the traditional household module (in which the head of household is interviewed on basic information about the household); and the individual module, in which two respondents from each household are interviewed individually. In the second module, two persons - one male and one female from each household, usually the main couple, are selected for the interview. The survey team deployed one male and one female interviewer for each household, so that the gender of the interviewers matched that of the respondents. Collecting economic data directly from a female and male household member, rather than just the head of the household (who tend to be men in most cases), was a key feature of the DIGNITY survey.

Geographic coverage

The DIGNITY survey is representative of low-income areas and slums of the Dhaka City Corporations (North and South, from here on referred to as Dhaka CCs), and an additional low-income site from the Greater Dhaka Statistical Metropolitan Area (SMA).

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling procedure followed a two-stage stratification design. The major features include the following steps (they are discussed in more detail in a copy of the study's report and the sampling document located in "External Resources"):

FIRST STAGE: Selection of the PSUs

Low-income primary sampling units (PSUs) were defined as nonslum census enumeration areas (EAs), in which the small-sample area estimate of the poverty rate is higher than 8 percent (using the 2011 Bangladesh Poverty Map). The sampling frame for these low-income areas in the Dhaka City Corporations (CCs) and Greater Dhaka is based on the population census of 2011. For the Dhaka CCs, all low-income census EAs formed the sampling frame. In the Greater Dhaka area, the frame was formed by all low-income census EAs in specific thanas (i.e. administrative unit in Bangladesh) where World Bank project were located.

Three strata were used for sampling the low-income EAs. These strata were defined based on the poverty head-count ratios. The first stratum encompasses EAs with a poverty headcount ratio between 8 and 10 percent; the second stratum between 11 and 14 percent; and the third stratum, those exceeding 15 percent.

Slums were defined as informal settlements that were listed in the Bangladesh Bureau of Statistics' slum census from 2013/14. This census was used as sampling frame of the slum areas. Only slums in the Dhaka City Corporations are included. Again, three strata were used to sample the slums. This time the strata were based on the size of the slums. The first stratum comprises slums of 50 to 75 households; the second 76 to 99 households; and the third, 100 or more households. Small slums with fewer than 50 households were not included in the sampling frame. Very small slums were included in the low-income neighborhood selection if they are in a low-income area.

Altogether, the DIGNITY survey collected data from 67 PSUs.

SECOND STAGE: Selection of the Households

In each sampled PSU a complete listing of households was done to form the frame for the second stage of sampling: the selection of households. When the number of households in a PSU was very large, smaller sections of the neighborhood were identified, and one section was randomly selected to be listed. The listing data collected information on the demographics of the household to determine whether a household fell into one of the three categories that were used to stratify the household sample:

i) households with both working-age male and female members; ii) households with only a working-age female; iii) households with only a working-age male.

Households were selected from each stratum with the predetermined ratio of 16:3:1. In some cases there were not enough households in categories (ii) and (iii) to stick to this ratio; in this case all of the households in the category were sampled, and additional households were selected from the first category to bring the total number of households sampled in each PSU to 20.

The total sample consisted of 1,300 households (2,378 individuals).

Sampling deviation

The sampling for 1300 households was planned after the listing exercise. During the field work, about 115 households (8.8 percent) could not be interviewed due to household refusal or absence. These households were replaced with reserved households in the sample.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaires for the survey were developed by the World Bank, with assistance from the survey firm, DATA. Comments were incorporated following the pilot tests and practice session/pretest.

Cleaning operations

Collected data was entered into a computer by using the customized MS Access data input software developed by Data Analysis and Technical Assistance (DATA). Once data entry was completed, two different techniques were employed to check consistency and validity of data as follows:

1. Five (5%) percent of the filled-in questionnaire was checked against entered data to measure the transmission error or typos, and;
2. A logical consistency checking technique was employed to identify inconsistencies using SPSS and or STATA software.

Abstract

The main objective of the 2019 Chattogram for Low Income Area Gender, Inclusion, and Poverty (CITY) study is to collect primary data from male and female residents in slum and non-slum poor neighborhoods in Chattogram, the second largest city of Bangladesh, and build the evidence base about their constraints to access more and better jobs. The CITY survey was designed to shed light on poverty, economic empowerment, and livelihood in urban areas of Bangladesh as well as to identify key constraints and solutions for low-income women trying to obtain better jobs.

A broad array of information was collected on issues related to women's economic empowerment, ranging from demographic and socioeconomic characteristics to detailed work history, time use, attitudes about work, and perceptions of work. The key feature of this survey is to collect economic data directly from the main household members, generally the main couples, unlike traditional surveys which only interviewed the heads of households (who tend to be men in most cases); thus, failed to gather valuable information from the female population.

Geographic coverage

Poor areas of slum & non-slum areas of Chattogram, the second largest city of Bangladesh.

Analysis unit

Household, individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The CITY 2019 survey was designed using a two-stage sampling strategy. The major features include the following steps:

FIRST STAGE: The primary sampling units (PSUs) in the first stage were selected using a probability proportional to size (PPS) methods. Using the 2011 census sampling frame, low-income PSUs were defined as non-slum census enumeration areas (EAs) using the 2011 Bangladesh Poverty Map. Three strata were used for sampling the low-income EAs. These strata were defined based on the poverty head-count ratios. The first stratum encompasses EAs with a poverty headcount ratio less than 10%; the second stratum between 11% and 14%; and the third stratum, those exceeding 15%. Overall, 22 low-income EAs were selected in the Chattogram City Corporation (CC).

Slums were defined as informal settlements that were listed in the Bangladesh Bureau of Statistics' slum census from 2013/14. This census was used as sampling frame of the slum areas. Based on the sizes of the slums, three strata were used for sampling purposes. This time the strata were based on the size of the slums. The first stratum comprises slums of 50 to 75 households; the second 76 to 99 households; and the third, more than 100 households. Small slums with fewer than 50 households were not included in the sampling frame. Overall, 18 slums were included as a part of the survey.

SECOND STAGE: The second stage of the selection process in each of the EAs began with a listing exercise. For very large EAs, a smaller section was delineated for the listing. The second level of stratification are defined as follows:

i) Households with both working-age male and female members; ii) Households with only a working-age female; iii) Households with only a working-age male.

Households were randomly selected from each stratum with the predetermined ratio of 16:3:1. Overall, data was collected from 805 households (1289 individuals - 580 in slum and 709 in non-slum areas).

Sampling deviation

For EAs where the ratio was unable to be attained due to absence of households in certain strata, households from the first category to arrive at a final number of 20 per EA.

Mode of data collection

Computer Assisted Personal Interview [capi]

Response rate

77%

Bangladesh BD: Number of People Pushed Below the 50% Median Consumption Poverty Line by Out-of-Pocket Health Care Expenditure data was reported at 5,184,000.000 Person in 2010. This records an increase from the previous number of 4,701,000.000 Person for 2005. Bangladesh BD: Number of People Pushed Below the 50% Median Consumption Poverty Line by Out-of-Pocket Health Care Expenditure data is updated yearly, averaging 4,763,000.000 Person from Dec 2000 (Median) to 2010, with 3 observations. The data reached an all-time high of 5,184,000.000 Person in 2010 and a record low of 4,701,000.000 Person in 2005. Bangladesh BD: Number of People Pushed Below the 50% Median Consumption Poverty Line by Out-of-Pocket Health Care Expenditure 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. Number of people pushed below the 50% median consumption poverty line by out-of-pocket health care expenditure; ; Wagstaff et al. Progress on Impoverishing Health Spending: Results for 122 Countries. A Retrospective Observational Study, Lancet Global Health 2017; Sum;

Poverty gap at $3.2 a day of Bangladesh sank by 18.18% from 18.7 % in 2010 to 15.3 % in 2016. Since the 0.60% upward trend in 1991, poverty gap at $3.2 a day plummeted by 54.73% in 2016. 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.