Community-Based Conditional Cash Transfer Program Impact Evaluation 2009-2012, Baseline, Midline, and Endline surveys
Baseline, Midline, and Endline surveys
Other Household Health Survey [hh/hea]
There are 3 rounds for this survey : Round 1 (January - May 2009), Round 2 (July - September 2011) and Round 3 (August - October 2012).
The overall objective of the pilot is to test how a conditional cash transfer (CCT) program could be implemented through a social fund using a community-driven development (CDD) approach, and to learn about what systems may need to be in place to achieve positive results for highly vulnerable populations. This project represents both the first time that a social fund agency was used to implement a CCT program in Africa, and the first time that a CCT program was delivered using a CDD approach. Specific objectives of this pilot project included (a) to develop operational modalities for the community-driven delivery of a CCT program through a social fund operation; and (b) to test the effectiveness of the community-based CCT model and ensure that lessons from the pilot inform government policy on support for vulnerable families.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Edited, anonymous dataset for public distribution.
HOUSEHOLD: Household characteristics, household listing, assets (including livestock), education, health, health-seeking behavior, consumption, home production, shocks, and transfers.
ELDERLY: Ability to perform daily activities
CHILDREN: school enrollment, school attendance and grade level, activities/ chores, child assets (including shoes), and anthropometrics (height, weight, MUAC).
COMMUNITY: health clinic characteristics, health clinic staff, school characteristics, school staffing, community governance indicators
Three districts: Bagamoyo, Chamwino, and Kibaha
The poorest and most vulnerable households in the three selected study districts of Tanzania (Bagamoyo, Chamwino, and Kibaha), as identified by elected Community Management Committees in each village.
Producers and sponsors
David K. Evans
Technical assistance in data processing and analysis
CGIAR Research Program on Policies, Institutions, and Markets
International Initiative for Impact Evaluation
Endline surveys and analysis
Strategic Impact Evaluation Fund
Trust Fund for Environmentally and Socially Sustainable Development
Japanese Social Development Fund
Tanzania Social Action Fund (TASAF)
Tanzania Social Action Fund (TASAF)
Former Executive Director
Tanzania Social Action Fund (TASAF)
Head of Systems, Training, Research and Participation
At the household level, eligibility criteria for beneficiary households were based on household characteristics of the very poor that were defined by communities themselves through focus group discussions. The criteria were that the households be: (a) very poor, (b) not receiving similar benefits in kind or cash from another program, and (c) home to an elderly person (60+) or an orphan or vulnerable child (OVC). "Very poor" was defined by stakeholders as a household meeting at least three of the following characteristics: (1) lack of a basic dwelling or shamba; (2) difficulty having two meals per day; (3) no adult member has worked in the last month; (4) children with clothes/shoes in poor condition; (5) family does not own livestock; and (6) family does not own land.
The study was conducted in three districts - Bagamoyo (70 km from Dar es Salaam), Chamwino (500 km from Dar), and Kibaha (35 km from Dar). The baseline survey covered 80 villages (40 treatment and 40 control). All 80 villages within the three districts had community management committees that received financial training from TASAF and had successfully managed at least one TASAF-supported project. The villages were randomized into treatment and control groups, stratified on village size and district. Among villages of a similar size and in the same district, each village had an equal likelihood of becoming a treatment village (i.e., getting the cash transfers) or becoming a control village (i.e., does not receive the cash transfer). This maximized the likelihood that treatment and control villages were similar in unobserved characteristics as well as the measured characteristics.
Random selection of the control and treatment villages was done after vulnerable households had been identified in all 80 villages, in order to ensure comparability between vulnerable households identified in the treatment and control groups.
Researchers have not computed sample weights.
Dates of Data Collection
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data were collected electronically and sent to the survey firm as interviews were completed. The software program automatically incorporated skip patterns and gave error messages for invalid responses, significantly reducing data entry errors.
Data Collection Notes
Interviews took about 80-90 minutes per household.
Economic Development Initiatives
All questionnaires were written in Swahili, and most (>99% at baseline) interviews were communicated in Swahili.
A household questionnaire was administered in each household. It contained modules for the household roster, education, health, assets, and TRUST.
The roster module collected information on sex, age, and relationship of all household members. In the second and third rounds of the survey there were questions about migration both in and out of the household.
The education module contains questions about literacy, highest grade of education attained, and whether currently in school. These data were collected for those at least 3 years old.
The health module contains questions about the number of clinic visits made, health problems in last 4 weeks, treatment details for illnesses, ability to complete activities of daily living (ADL), and anthropometrics. Data on ADL were collected for those at least 15 years old in the first wave of the survey and collected for those at least 60 years old in subsequent waves. Anthropometric and child feeding practices data were collected for those under 5 years old. Other general health data were collected for everyone in the sample.
The child module inquires about the number of various assets (shoes, exercise books, etc) owned for children younger than 6 to 18 years old. It also asks questions about whether the child (4-18 years) works on a family income generating activity.
There are many other sections that pertain to the household as a whole (not its members). These include sections on the CCT program (how many payments has household received, how payment received, understanding CCT rules, etc), housing quality (floor material, roof material, etc), land/livestock owned, crops grown, transfers given/received, shocks (floods, droughts, deaths, etc), trust in community members (shopkeepers, teachers, doctors, etc), and participation in community activities.
Three community-level questionnaires were administered only in the third wave of the survey: The school questionnaire was given to a teacher and covered topics such as school type, size, amenities, and location (GPS). The health facility questionnaire was given to a hospital employee and covered topics such as facility type, size, amenities, location (GPS), and ability to test for a range of illnesses. The last community-level questionnaire was given to a government official to learn about the community. Topics covered included village population, records kept by the local government, frequency of meetings, etc.
Raw data are provided.
Development Data Group
World Bank Group
The data have been anonymized.
Direct access, accessible to all
Evans, David K., Brian Holtemeyer, and Katrina Kosec. Surveys for Impact Evaluation of Tanzania Community-Based Conditional Cash Transfer Program 2009-2012, Ref.TZA_2009-2012_CCT_v01_M. Dataset downloaded from [URL] on [date].
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
(c) 2016, The World Bank and the International Food Policy Research Institute (IFPRI)