Home / Central Data Catalog / BGD_2018_DIGNITY_V01_M

Dhaka Low Income Area Gender, Inclusion, and Poverty Survey 2018

Bangladesh, 2018
Central
The World Bank Group
Created on March 09, 2020 Last modified March 09, 2020 Page views 10832 Download 1756 Documentation in PDF Metadata DDI/XML JSON

Identification

Survey ID Number
BGD_2018_DIGNITY_v01_M
Title
Dhaka Low Income Area Gender, Inclusion, and Poverty Survey 2018
Country
Name Country code
Bangladesh BGD
Study type
Integrated Survey (non-LSMS) [hh/is]
Series Information
The Data for Low Income Area Gender, Inclusion, and Poverty (DIGNITY) survey was designed to shed light on poverty, economic empowerment, and livelihood in urban areas of Bangladesh. So far it has been conducted in two cities in Bangladesh - Dhaka (documented in this DDI) and Chittagong. The survey collected issues related to women's economic empowerment, ranging from demographic and socioeconomic characteristics to a detailed work history, time use, and attitudes about work, and perceptions of work.
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.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Household
- Individual

Version

Version Description
-v01: Edited, anonymous datasets for public distribution.

Scope

Notes
The 2018 DIGNITY Survey covered the following topics:

Household Section:
• Household Identification
• Household Roster
• Housing
• Consumption
• Services

Individual Section:
• Individual Identification
• Employment and Childcare
• Work History, Training, Mentoring
• Time Use
• Family and Marriage
• Migration
• Dwelling and Land Ownership
• Access to Productive Capital
• Access to Finance
• Group Membership
• Attitudes toward Work and Earnings
• Intra-household Relationships
• Individual Leadership and Influence in the Community
• Safety Perception
• Aspiration, Stress and Depression
• Crisis

Coverage

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).

Producers and sponsors

Primary investigators
Name
The World Bank Group
Funding Agency/Sponsor
Name Abbreviation Role
Umbrella Facility for Gender Equality UFGE Financial Assistance

Sampling

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).
Deviations from the Sample Design
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.
Weighting
The weight was constructed as the inverse likelihood of a particular household being selected.

Please see the sampling document in 'External Documents' for more detailed information on how the probability of a particular household to be selected was calculated as well as more information on the weighting attributed to each household.

Data Collection

Dates of Data Collection
Start End
2018-06-06 2018-06-19
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Collectors
Name Abbreviation
Data Analysis and Technical Assistance DATA

Questionnaires

Questionnaires
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.

Data Processing

Data Editing
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.

Access policy

Contacts
Name Affiliation Email
Aphichoke Kotikula The World Bank Group akotikula@worldbank.org
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:

- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download

Example:

The World Bank Group. Dhaka Low Income Area Gender, Inclusion, and Poverty Survey (DIGNITY) 2018, Ref. BGD_2018_DIGNITY_v01_M. Dataset downloaded from [url] on [date].

Metadata production

DDI Document ID
DDI_BGD_2018_DIGNITY_v01_M_WB
Producers
Name Abbreviation Affiliation Role
Development Economics Data Group DECDG The World Bank Documentation of the study
Date of Metadata Production
2020-01-31
DDI Document version
Version 01 (January 2020)

This site uses cookies to optimize functionality and give you the best possible experience. If you continue to navigate this website beyond this page, cookies will be placed on your browser. To learn more about cookies, click here.