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%

Chart and table of population level and growth rate for the Dhaka, Bangladesh metro area from 1950 to 2025.

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.