This statistic shows the biggest cities in Bangladesh in 2022. In 2022, approximately ***** million people lived in Dhaka, making it the biggest city in Bangladesh.

Bangladesh BD: Population in Largest City data was reported at 23,935,652.000 Person in 2024. This records an increase from the previous number of 23,209,616.000 Person for 2023. Bangladesh BD: Population in Largest City data is updated yearly, averaging 7,344,419.000 Person from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 23,935,652.000 Person in 2024 and a record low of 507,921.000 Person in 1960. Bangladesh BD: Population in Largest City 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: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.;United Nations, World Urbanization Prospects.;;

Actual value and historical data chart for Bangladesh Population In Largest City

Bangladesh BD: Population in Largest City: as % of Urban Population data was reported at 33.448 % in 2024. This records an increase from the previous number of 33.444 % for 2023. Bangladesh BD: Population in Largest City: as % of Urban Population data is updated yearly, averaging 30.733 % from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 33.448 % in 2024 and a record low of 19.085 % in 1960. Bangladesh BD: Population in Largest City: as % 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: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.;United Nations, World Urbanization Prospects.;Weighted average;

Context

This dataset contains geolocation information of Locations (Major Cities, Neighborhoods and Localities of Bangladesh) in Bangladesh

Content

This dataset was collected by using a combination of Nomiatim, Positionstack, and Opencage geocoding API. The dataset has 6 columns containing information about Locations (Major Cities, Neighborhoods and Localities of Bangladesh) - area_name: The name of the location - latitude - longitude - area_type: The type of the location i.e., locality, neighborhood, venue, etc. - county_name: The name of the county/district the location resides in - region: The name of the region/division the location resides in

Inspiration

• This dataset can be used as a supplementary dataset for any spatial analysis of Bangladesh's demographic

Graph and download economic data for Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding Headquarters, for Other Deposit Takers for Bangladesh (BGDFCBODDLNUM) from 2004 to 2015 about branches and Bangladesh.

The below dataset shows the top 800 biggest cities in the world and their populations in the year 2024. It also tells us which country and continent each city is in, and their rank based on population size. Here are the top ten cities:

• Tokyo, Japan - in Asia, with 37,115,035 people.
• Delhi, India - in Asia, with 33,807,403 people.
• Shanghai, China - in Asia, with 29,867,918 people.
• Dhaka, Bangladesh - in Asia, with 23,935,652 people.
• Sao Paulo, Brazil - in South America, with 22,806,704 people.
• Cairo, Egypt - in Africa, with 22,623,874 people.
• Mexico City, Mexico - in North America, with 22,505,315 people.
• Beijing, China - in Asia, with 22,189,082 people.
• Mumbai, India - in Asia, with 21,673,149 people.
• Osaka, Japan - in Asia, with 18,967,459 people.

This dataset comprises 1500 high-quality images depicting various forms of road surface damage collected from major cities in Bangladesh, specifically Dhaka, Mymensingh, and Chattogram. The dataset captures real-world conditions of urban and semi-urban road networks, providing valuable visual data for analysis in computer vision, machine learning, deep learning, and civil infrastructure research. The images are captured under diverse lighting conditions and angles, ensuring variability and practical utility for robust algorithm development.

Dataset Composition:

Total Images: 1500

Format: JPG

Image Resolution: Varied, high-resolution suitable for computer vision tasks.

Class-wise Distribution:

Asphalt Damage: 500 images

Crack: 500 images

Pothole: 500 images

Dataset Potential Applications:

Training, validation, and benchmarking for deep learning and machine learning algorithms focusing on road infrastructure assessment.

Development of computer vision-based automated systems for road damage detection and classification.

Research and development in intelligent transportation systems (ITS), smart city infrastructure management, and predictive road maintenance.

Analysis and testing of algorithms for damage severity assessment and automated cost estimation for repairs.

Intended Users:

Researchers in civil engineering, transportation, and urban planning.

Machine learning and computer vision practitioners focus on infrastructure monitoring and predictive maintenance.

Government bodies and policymakers are interested in infrastructural health assessments and proactive maintenance planning.

🌍 Bangladesh Air Quality Index (AQI) Dataset (2000-2025)

Comprehensive Historical Air Pollution Data Across 103 Cities

📊 Dataset Overview

This dataset provides comprehensive air quality measurements for 103 cities across Bangladesh, spanning from 2000 to 2025. It contains over 3.19 million hourly observations of key air pollutants and environmental indicators, making it one of the most extensive air quality datasets for Bangladesh available for public use.

Key Features: - ✅ 103 cities covering all major regions of Bangladesh - ✅ 3.19+ million hourly observations (2000-2025) - ✅ 8 pollutant measurements: PM10, PM2.5, CO, CO₂, NO₂, SO₂, O₃, AQI - ✅ Precise geolocation with latitude/longitude coordinates - ✅ Standardized format with consistent column naming - ✅ Research-ready for environmental science, public health, and ML applications

📋 Dataset Summary

Property	Value
Total Records	3,193,198 rows
Number of Cities	103 cities
Time Period	2000-2025 (25 years)
Temporal Resolution	Hourly measurements
File Format	CSV (Comma-separated values)
Total Columns	13
Geographic Coverage	All major regions of Bangladesh

📅 City-wise Data Coverage

City Name	From Date	Total Rows
Dhaka	2000-01-01	227,016
Narsingdi	2020-01-01	37,991
Rangpur	2022-08-04	28,993
Sherpur	2022-08-04	28,993
Dinājpur	2022-08-04	28,993
Lākshām	2022-08-04	28,993
Comilla	2022-08-04	28,993
Thākurgaon	2022-08-04	28,993
Teknāf	2022-08-04	28,993
Tungi	2022-08-04	28,993
Sylhet	2022-08-04	28,993
Dohār	2022-08-04	28,993
Jamālpur	2022-08-04	28,993
Shibganj	2022-08-04	28,993
Sātkhira	2022-08-04	28,993
Sirājganj	2022-08-04	28,993
Netrakona	2022-08-04	28,993
Sandwīp	2022-08-04	28,993
Shāhzādpur	2022-08-04	28,993
Rāmganj	2022-08-04	28,993
Rājshāhi	2022-08-04	28,993
Purbadhala	2022-08-04	28,993
Pirojpur	2022-08-04	28,993
Panchagarh	2022-08-04	28,993
Patiya	2022-08-04	28,993
Parbatipur	2022-08-04	28,993
Nārāyanganj	2022-08-04	28,993
Nālchiti	2022-08-04	28,993
Nāgarpur	2022-08-04	28,993
Nageswari	2022-08-04	28,993
Mymensingh	2022-08-04	28,993
Muktāgācha	2022-08-04	28,993
Mirzāpur	2022-08-04	28,993
Maulavi Bāzār	2022-08-04	28,993
Morrelgonj	2022-08-04	28,993
Mehendiganj	2022-08-04	28,993
Mathba	2022-08-04	28,993
Lalmanirhat	2022-08-04	28,993
Kushtia	2022-08-04	28,993
Kālīganj	2022-08-04	28,993
Jhingergācha	2022-08-04	28,993
Joypur Hāt	2022-08-04	28,993
Ishurdi	2022-08-04	28,993
Habiganj	2022-08-04	28,993
Gaurnadi	2022-08-04	28,993
Gafargaon	2022-08-04	28,993
Feni	2022-08-04	28,993
Rāipur	2022-08-04	28,993
Sarankhola	2022-08-04	28,993
Chilmāri	2022-08-04	28,993
Chhāgalnāiya	2022-08-04	28,993
Lālmohan	2022-08-04	28,993
Khagrachhari	2022-08-04	28,993
Chhātak	2022-08-04	28,993
Bhātpāra Abhaynagar	2022-08-04	28,993
Bherāmāra	2022-08-04	28,993
Bhairab Bāzār	2022-08-04	28,993
Bāndarban	2022-08-04	28,993
Kālia	2022-08-04	28,993
Baniachang	2022-08-04	28,993
Bājitpur	2022-08-04	28,993
Badarganj	2022-08-04	28,993
Narail	2022-08-04	28,993
Tungipāra	2022-08-04	28,993
Sarishābāri	2022-08-04	28,993
Sakhipur	2022-08-04	28,993
Raojān	2022-08-04	28,993
Phultala	2022-08-04	28,993
Pālang	2022-08-04	28,993
Pār Naogaon	2022-08-04	28,993
Nabīnagar	2022-08-04	28,993
Lakshmīpur	2022-08-04	28,993
Kesabpur	2022-08-04	28,993
Jahedpur	2022-08-04	28,993
Hājīganj	2022-08-04	28,993
Farīdpur	2022-08-04	28,993
Uttar Char Fasson	2022-08-04	28,993
Chittagong	2022-08-04	28,993
Char Bhadrāsan	2022-08-04	28,993
Bera	2022-08-04	28,993
Burhānuddin	2022-08-04	28,993
Sātkania	2022-08-04	28,993
Cox's Bāzār	2022-08-04	28,993
Khulna	2022-08-04	28,993
Bhola	2022-08-04	28,993
Barisāl	2022-08-04	28,993
Jessore	2022-08-04	28,993
Pābna	2022-08-04	28,993
Tāngāil	2022-08-04	...

Graph and download economic data for Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding Headquarters, for Deposit Taking Microfinance Institutions (MFIs) for Bangladesh (BGDFCBODMFLNUM) from 2004 to 2015 about microfinance, branches, Bangladesh, and deposits.

The population density in Bangladesh reached its highest in 2020, amounting to approximately 1.27 thousand people per square kilometer. The South Asian country was the tenth most densely populated country in the world in 2019. Within the Asia Pacific region, Bangladesh’s population density was only exceeded by Macao, Singapore, Hong Kong, and the Maldives. Overall, Asia had the highest population density in the world in 2018.

Population growth in Bangladesh

In 1971, Bangladesh gained its independence from Pakistan. Bangladesh’s birth rate and mortality rate had declined significantly in the past years with a life expectancy of 72.59 years in 2019. In general, the population in Bangladesh had been growing at a slow pace, slightly fluctuating around an annual rate of one percent. This growth was forecasted to continue, although it was estimated to halve by 2040. As of today, Dhaka is the largest city in Bangladesh.

Population density explained

According to the source, “population density is the mid-year population divided by land area in square kilometers.” Further, “population is based on the de facto definition of population, which counts all residents.” Bangladesh’s population reached an estimated number of 164.69 million inhabitants in 2020. In 2018, the country’s land area amounted 130.2 thousand square kilometers.

This map service includes geology, major faults, geologic provinces, and political boundaries in Bangladesh. This compilation is part of an interim product of the U.S. Geological Survey's World Energy Project (WEP) and part of a series on CD-ROM. The data sets include arcs, polygons, and labels that outline and describe the general geologic age and geophysical fields of Bangladesh. Political boundaries are provided to show the general location of administrative regions and state boundaries. Major base topographic data like cities, rivers, etc. were derived from the same paper map source as the geology.

Abstract

The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular. MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.

Survey Objectives The 2006 Bangladesh Multiple Indicator Cluster Survey has the following objectives: - To provide up-to-date information for assessing the situation of children and women in Bangladesh; - To furnish data needed for monitoring progress toward goals established by the Millennium Development Goals, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; - To contribute to the improvement of data and monitoring systems in Bangladesh and to strengthen technical expertise in the design, implementation, and analysis of such systems.

Survey Content MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.

Survey Implementation The survey was implemented by the Bangladesh Bureau of Statistics , with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

Geographic coverage

The survey is nationally representative and covers the whole of Bangladesh.

Analysis unit

Households (defined as a group of persons who usually live and eat together)

De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)

Women aged 15-49

Children aged 0-4

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the sample design for the Bangladesh Multiple Indicator Cluster Survey was to produce statistically reliable estimates of most indicators, at the national level, for urban and rural areas, and for the six divisions of the country, municipal areas, city corporation's slum areas of two big cities and tribal areas. Rural areas, municipal areas, city corporation areas, slum areas and tribal areas were defined as the sampling domain.

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample.

Sample Size and Sample Allocation The target sample size for the Bangladesh MICS was calculated as 68247 households. For the calculation of the sample size, the key indicator used was the DPT immunization (3+doses) prevalence among children aged 12-23 months. The following formula was used to estimate the required sample size for these indicators: n = [ 4 (r) (1-r) (f) (1.1) ] [ (0.12r)2 (p) (nh) ]

where n is the required sample size, expressed as number of households 4 is a factor to achieve the 95 per cent level of confidence r is the predicted or anticipated prevalence (coverage rate) of the indicator 1.1 is the factor necessary to raise the sample size by 10 per cent for non-response f is the shortened symbol for deff (design effect) 0.12r is the margin of error to be tolerated at the 95 per cent level of confidence, defined as 12 per cent of r (relative sampling error of r) p is the proportion of the total population upon which the indicator, r, is based nh is the average household size.

For the calculation, r (DPT immunization 3+doses prevalence) was assumed to be 39.7 percent in the Rangamati districts. The value of deff (design effect) was taken as 1.5 based on estimates from previous surveys, p (percentage of children aged 12-23 months in the total population) was taken as 2.3 percent, and nh (average household size) was taken as 4.9 households.

For the sub national level, the margin of error should be high which was also acknowledged in the MICS manual. Therefore, for sub national estimates the margin of error need to be relaxed considerably. If a rate of 30% of r is used this would give a margin of error ± 0.06 for prevalence rates of 0.20, ± 0.12 for prevalence rates of 0.40, and so on. Considering this phenomenon, in case of Rangamati 30% of r has been used.

The resulting number of households from this exercise was about 900 households which is the sample size needed in each district - thus yielding about 68250 in total. The average cluster size in the Bangladesh MICS was determined as 35 households, based on a number of considerations, including the budget available, and the time that would be needed per team to complete one cluster. Dividing the total number of households by the number of households per cluster, it was calculated that the selection of a total number of 26 clusters would be needed in each district.

Equal allocation of the total sample size to the 75 domains was targeted. Therefore, 26 clusters were allocated to each district with the final sample size calculated at 68250 households (1950 cluster X 35 households per cluster). In each stratum, the clusters (primary sampling units) were distributed to rural, municipal, city corporations, slum and tribal areas on PPS method.

Sampling Frame and Selection of Clusters The 2001 census frame was used for the selection of clusters. Census enumeration areas were defined as primary sampling units (PSUs), and were selected from each of the sampling domains by using systematic pps (probability proportional to size) sampling procedures, based on the estimated sizes of the enumeration areas from the 2001 Population Census. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the 5 strata namely rural, municipal, city corporations, slum and tribal areas.

Listing Activities Since the sample frame of the 2001 Population Census was not up to date, household lists in all selected enumeration areas were updated prior to the selection of households. For this purpose, listing teams were formed, who visited each enumeration area, and listed the occupied households. The BBS officials working in the upazila were responsible for the listing of all households in the respective PSUs.

Selection of Households Lists of households were prepared by the Upazila officials of BBS. The households were sequentially numbered from 1 to 100 (or more) households in each enumeration area at the where selection of 35 households in each enumeration area was carried out using systematic selection procedures.

(Information extracted from the final report: BBS and UNICEF. 2007. Bangladesh Multiple Indicator Cluster Survey 2006, Final Report. Dhaka, Bangladesh: BBS and UNICEF)

Sampling deviation

No major deviations from the original sample design were made. All sample enumeration areas were accessed and successfully interviewed with good response rates.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires of MICS 2006 are based on the global format of MICS3 model questionnaire. From the MICS3 model English version, the questionnaires were translated into Bangla and were pre-tested in four sample areas of which two were in rural areas, one in City Corporation and one in the slum area during May 2006. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

The questionnaire for under-five children was administered to mothers or caretakers of under-five children living in the households. Normally, the questionnaire was administered to mothers of under-five children; in cases when the mother was not listed in the household roster, a primary caretaker for the child was identified and interviewed.

Cleaning operations

Data editing took place at a number of stages throughout the processing (see Other processing), including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files

Detailed documentation of the editing of data can be found in the data processing guidelines

Response rate

Of the 68,247 of households selected for the sample, 67,540 were found to be occupied. Of these, 62,463 households were successfully interviewed for a household response rate of 92.5 percent. In the interviewed households, 78,260 of eligible women (age 15-49) were identified. Of these, 69,860 of women were successfully interviewed, yielding a response rate of 89.3 percent. In addition, 34,710 of children under 5 were listed in HH questionnaire.

The data set for these maps includes arcs, polygons, and labels that outline and describe the general geologic age and geophysical fields of Bangladesh. Political boundaries are provided to show the general location of administrative regions and state boundaries. Major base topographic data like cities, rivers, etc. were derived from the same paper map source as the geology. The data provide government, the geologic community, consultants, and the general public with an important geological base for small scale natural resource surveys, exploration and analysis. The maps on this CD-ROM have been compiled from: 1. Md. Khurshid Alam, A.K.M.Shahidul Hasan, and Mujibur Rahman Khan (Geological Survey of Bangladesh), and John W. Whitney (United States Geological Survey), 1990, Geological Map of Bangladesh: Geological Survey of Bangladesh Publication, scale 1:1,000,000. 2. M.A. Rahman, (Geological Survey of Bangladesh), M.A. Mannan, (Bangladesh Petroleum Exploration Company), H. R. Blank, M.D. Kleinkopf, and R. P. Kucks, (United States Geological Survey), 1990, Bouguer Gravity Anomaly Map of Bangladesh: Geological Survey of Bangladesh Publication,, scale 1:1,000,000. 3. M.A. Rahman, (Geological Survey of Bangladesh), H. R. Blank, M.D. Kleinkopf, and R. P.Kucks, (United States Geological Survey), 1990, Aeromagnetic Anomaly Map of Bangladesh: Geological Survey of Bangladesh Publication,, scale 1:1,000,000.

Thematic results at a glance.

Dhaka City Reddit Corpus (2025)

Context

This dataset contains a collection of Reddit posts scraped from major Bangladeshi subreddits (r/Dhaka, r/Bangladesh). It captures the pulse of the city, covering topics ranging from politics and traffic to food recommendations and social issues.

Content

The dataset is provided in JSON format and includes the following fields for each post: * Title: The headline of the Reddit thread. * Body: The main text content of the post. * Author: The Reddit username of the poster. * Upvotes: The net score (upvotes minus downvotes) at the time of scraping. * Comments: The number of comments on the thread. * Date: The timestamp of when the post was created. * Subreddit: The source community. * URL: Direct link to the original thread.

Potential Use Cases

This dataset is ideal for: 1. Sentiment Analysis: Understanding the general mood of Dhaka residents regarding current events (e.g., the 2025 earthquake scares, political changes). 2. Topic Modeling: Identifying the most discussed themes in urban Bangladesh. 3. Social Network Analysis: Analyzing engagement patterns (upvotes vs. comments).

Collection Methodology

Data was scraped using the Reddit API (PRAW) targeting keywords related to "Dhaka" and general activity within the r/Dhaka and r/Bangladesh subreddits.

Acknowledgements

Data sourced from Reddit. All content belongs to the respective original posters.

The SHAHAR (Supporting Household Activities for Health, Assets and Revenue) project aims to increase incomes and improve unhygienic environments and sanitation conditions in poor urban communities, including slums, in major selected secondary cities in Bangladesh. Using relevant indicators namely socioeconomic; health and hygiene; nutrition and diet; and governance and social institutions the project provides insight into the livelihood conditions and the livelihood security of these slum households. The SHAHAR baseline survey was conducted in July to August, 2002 in slum (basti) communities in Dinajpur. The SHAHAR census survey suggested that only 52 percent of households had children under 5 years of age; doubling the sample size would ensure that the final sample would have at least this many households with children under 5 years of age. This gave an estimated sample size of 271 * 2 = 542. As slum dwellers are assumed to be highly mobile, and the losses would increase over the year between round I in July – August, 2002 and round III a year later, a substantial reserve was added to the sample, as well as some allowance for refusal or other non-response, for a final total of 614 households. The field survey was carried out by two teams, each consisting of three male and female pairs and a supervisor. One pair interviewed one household at a time, with the female interviewer interviewing the main female member of the household and collecting information on household composition, migration and education; training; savings; loans; food consumption; household food security; health; anthropometry and childcare; environment, water and sanitation; shocks and coping strategies; social capital; crime, violence, physical security; governance; and women’s status. The male interviewer interviewed the main male member of the household asking questions on language, religion, and migration; training; employment; transfers, social assistance and other income; household assets; land own ership and tenure; urban agriculture; savings; loans; housing; non food expenditure; shocks and coping strategies; social capital; crime, violence and physical security; and governance. The pairs on each team worked together to cover three households per day and the 614 households surveyed in approximately 39 days in July to August, 2002 in Dinajpur. The SHAHAR (Supporting Household Activities for Health, Assets and Revenue) Dinajpur baseline survey was conducted in collaboration with Data Analysis and Technical Assistance (DATA), Dhaka, Bangladesh; and CARE-Bangladesh. The questionnaires were developed by the International Food Policy Research Institute. The funding for the survey was provided by CARE-Bangladesh; and US Agency for International Development (USAID).

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.

Abstract

The survey provides important basic information relating to the structure and operational pattern of agricultural lands and their utilization. The survey was conducted in 2005 to meet the immediate data needs of the three years rolling plan of the Government after the 1996/97 Agriculture Census.

Geographic coverage

National

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design used for conducting the Agriculture Sample Survey 2005 is a stratified cluster sampling. A technical sub-committee was formed for the development of the sampling design. The sub-committee developed a stratified cluster design with Mohalla/ Mauza as cluster of households. For this survey, each agricultural household is the ultimate sampling unit (element) from which agricultural data were collected. This sample survey covered 10% of total mauzas and mahallas of the country.

Stratification: Primarily, a two-way stratification was done. The first stratification was done by locality dividing the whole country into 3 strata: (i) Metropolitan area consisting of municipalities of 6 Metropolitan cities, (ii) Urban area consisting of municipalities of other Zila towns, (iii) Rural area consisting of remaining areas of the country.

The secondary stratification was done within the selected locality. A fixed number of clusters (10% mauza/mahalla) were selected in each zila/city and the selected agricultural households were interviewed in each selected cluster. This means that about 10% Mohallas were selected in samples for first 2 strata and about 10% Mauzas were selected in the third stratum. The selected sample Mauzas were divided into 2 size classes, namely (1) Mauzas with up to 500 households and (2) Mauzas with more than 500 households. EAs were delineated with about 200 households from the selected mauzas and 300 households from the selected Mohallas. All EAs comprising of 200 or less households from mauzas of size class-1 were selected and 1/3 EAs of mauzas of size class-2 were selected at random. A total of 13,539 EAs were thus selected for enumeration.

Refer to details in the Technical Documents (Preliminarty Report).

Mode of data collection

Face-to-face [f2f]

Research instrument

The schedule-1 (short questionnaire), which was canvassed and used for collecting data on agriculture in the 10% sample enumeration, contained the following information: • Household members • Agricultural labour • Land ownership • Land use • Area under permanent crops • Area under temporary crops • Area under bamboo bushes • Area under ponds • Homestead land • Current fallow land • Cultivated land • Commercial farms • Loan taken and use of loan • Livestock and poultry • Use of agricultural equipments • Employment in agriculture • Farm transports • Farm population, etc.

Cleaning operations

The zonal officer at his respective zone of the Upazila received all filled-in questionnaires just after completion of the enumeration as per schedule. Steps were taken to train zonal officers and supervisors for manual editing and checking of the filled in schedules in the field. Training was imparted to the Zonal Officers and Upazila Co-ordinators for ensuring consistencies of the critical items of information. To eliminate errors made by both respondents and interviewers in the field, a good number of unemployed and educated youths (enumerators and supervisors) edited all the items of the schedule carefully to ensure consistencies. A ten-day editing programme was allowed for editing Schedule-1 (short questionnaire) and Form-16 (summary information of every household) at Upazila level. In some identified cases, imputation of missing data in Schedule-1 as well as in Form-16 was made by them through spot verification.

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.