Geographic coverage

County

Analysis unit

Household/Individuals

Universe

County

Sampling procedure

Two stage cluster sampling based probability proportional to Population size (PPS)

Mode of data collection

Face to Face

Kenya had a Muslim population of roughly 5.6 million people, according to the last country census conducted in 2019. Nearly 50 percent of individuals adhering to Islam lived in the Northern-East counties of Mandera (856.5 thousand people), Garissa (815.8 thousand people), and Wajir (767.3 thousand people). Overall, around 10 percent of Kenya's population identified as Muslim.

Abstract

The Mwangaza Mashinani is a project that aims to enhance energy access for the most vulnerable segment of the Kenyan population. The project is targeted at vulnerable, off-grid households with school-going children who are enrolled in the GoK's cash transfer programme in Kilifi and Garissa. Once enrolled, households may choose to purchase a three-bulb solar home system for lighting and with a USB point for phone charging on a pay-as-you-go basis. To address the issue of affordability of these products, the project provides households with a bi-monthly cash top-up (i.e., a subsidy) which can be used to make repayments for the solar device over a one-year period.

Beyond improving access to clean energy for households, the project aims to increase children's and their families' well-being in terms of: Health - households reduce their use of kerosene and/or candles for lighting resulting in a reduction in indoor air pollution and fire hazards and, ultimately, a reduction in the prevalence of respiratory illness, burns and eye irritation; Education - children can increase the number of hours that they spend studying at night by using solar lighting resulting in improved educational outcomes; and Livelihoods - households can use the solar device to continue their productive activities at night, diversify livelihoods (e.g., by charging mobile phones for a fee), and reduce their net energy expenditure, resulting in an increase in household income.

UNICEF contracted OPM to conduct an independent evaluation of the Mwangaza Mashinani pilot project. The primary purpose of the evaluation was to render a summative assessment of the impact of the pilot project, and to generate scientifically robust evidence on whether and how the project has impact on the quality of life of children and their families in terms of education, health, and livelihoods. The evaluation also had a formative purpose, to improve the processes of the pilot project.

To fulfil these aims, a mixed methods research framework was designed. Broadly, this framework combines four methodologies: i) a quantitative research study to respond to questions of effectiveness and impact, and to support answers on relevance and sustainability. This study is based on a quasi-experimental design (using propensity score matching) and a quantitative household survey, which was implemented through an in-person survey at baseline and endline, and remotely through a mobile phone survey at midline; ii) a qualitative research study to respond to questions of relevance and effectiveness, and to provide initial indications of sustainability. This study is based on interviews with community leaders, community-based project support structures, and male and female household members; iii) an implementation review to respond to questions regarding the relevance and effectiveness of the project. This study is based on interviews with national-level stakeholders, including the GoK, UNICEF, and the implementing consortium and iv) a VfM study to respond to questions of efficiency. It relies on data from UNICEF and the implementing consortium.

Geographic coverage

Kilifi and Garissa counties

Analysis unit

Individuals Households

Universe

The following sub-counties are included in the population : Ganze, Magarini and Kaloleni in Kilifi county and Balambala, Dadaab, Fafi and Ijara in Garissa county. The definition of the population is constricted by the circumstances on the ground. Particularly, areas of extreme security risk are excluded from the viable population as the operation of both implementation and evaluation teams would be unsafe. Within these areas, the population of households is restricted to those households eligible for enrolment in the Mwangaza Mashinani pilot project. Specifically, these are CT-OVC and/or OP-CT beneficiary households residing in off-grid communities in Kilifi and Garissa, that have at least one household member enrolled in and attending school and that do not possess a solar device with more than one bulb and who have indicated to be willing to pay 250 Ksh as a deposit for the solar device.

Sampling procedure

Since a high ratio of the total population eligible for the pilot project was sampled for the evaluation, a sampling methodology was chosen that adheres to the required principles of the representativity of the proposed sample and randomness of the selection. A single stage sampling method was implemented as any optimisation of the costs and field logistics that would have been gained by the multistage approach is offset by the high sampling ratio where most geographical units suitable for primary stage clusters need to be included in the sample. A single sampling method applies the selection algorithm directly on the sample frame in its entirety.

The use of a stratified systematic random selection method would have been ideal for drawing the sample. However, the high sampling ratio (above 50% of the population) in this context precluded the use of systematic methods. To retain control over the structure of the sample and thus ensure representativity, explicit stratification combined with a simple random sampling (SRS) within each stratum was used. Consequently, the allocation of the sample proportion in each explicit stratum is proportional to the size of each stratum in the population.

The definition of the explicit strata is based on the following criteria: · Cash transfer type - CT-OVC or OP-CT · Gender of the household head - Male or Female · Sub-county - Ganze, Magarini, Kaloleni, Dadaab, Fafi, Ijara or Balambala. As mentioned, the proposed sample includes beneficiaries from both targeted counties: Kilifi and Garissa. The allocation of the sample to the two counties is proportional to the total population in each county. As such, county was imposed as a super-strata with pre-defined allocations of the sample. The SRS method of selection within each stratum is based on the random number generator.

Given the longitudinal nature of the evaluation, the same baseline respondents were tracked and re-interviewed at midline and endline so as to create a panel of survey respondents. The final quantitative survey sample achievement is shown below, including the distribution by county and treatment status:

Baseline - Kilifi: 387 (Treatment) and 373 (Control) - Garissa: 213 (Treatment) and 213 (Control)

Midline - Kilifi: 321 (Treatment) and 268 (Control) - Garissa: 180 (Treatment) and 174 (Control)

Endline - Kilifi: 378 (Treatment) and 366 (Control) - Garissa: 189 (Treatment) and 181 (Control)

Mode of data collection

Computer Assisted Personal Interviewing (CAPI) at baseline and endline; and Computer Assisted Telephone Interviewing (CATI) at midline

Research instrument

The baseline, midline and endline survey questionnaires are provided in English, for download as external resources.

Abstract

The Kenya National Housing Survey (KNHS) was carried out in 2012 to 2013 in 44 counties of the Republic of Kenya. It was undertaken through the NASSEP (V) sampling frame. The objectives of the 2012/2013 KNHS were to: improve the base of housing statistics and information knowledge, provide a basis for future periodic monitoring of the housing sector, facilitate periodic housing policy review and implementation, assess housing needs and track progress of the National Housing. Production goals as stipulated in the Kenya Vision 2030 and its first and second Medium Term Plan, provide a basis for specific programmatic interventions in the housing sector particularly the basis for subsequent Medium Term frameworks for the Kenya Vision2030; and facilitate reporting on the attainment of the Millennium Development Goals (MDG) goals particularly goal 7, target 11.

The 2012/2013 KNHS targeted different players in the housing sector including renters and owner occupiers, housing financiers, home builders/developers, housing regulators and housing professionals. Whereas a census was conducted among regulators and financiers, a sample survey was conducted on renters and owner occupiers, home builders/developers and housing professionals. To cover renters and owner occupiers, the survey was implemented on a representative sample of households - National Sample Survey and Evaluation Program V (NASSEP V) frame which is a household-based sampling frame developed and maintained by KNBS - drawn from 44 counties in the country, in both rural and urban areas. Three counties namely Wajir, Garissa and Mandera were not covered because the household-based sampling frame had not been created in the region by the time of the survey due to insecurity.

Considering that the last Housing Survey was carried out in 1983, it is expected that this report will be a useful source of information to policy makers, academicians and other stakeholders. It is also important to note that this is a basic report and therefore there is room for further research and analysis of various chapters in the report. This, coupled with regularly carrying out surveys, will enrich the data available in the sector which in turn will facilitate planning within the government and the business community.

One of the main challenges faced during the survey process was insufficient information during data collection. This could serve as a wake-up call to all county governments on the need to keep proper records on such issues like the number of housing plans they approve, housing finance institutions within their counties, the number of houses that are built within the county each year and so on since they have the machinery all the way to sub-location level.

Geographic coverage

The survey covered all the districts in Kenya. The data representativeness are at the following levels -National -Urban/Rural -Provincial -District

Analysis unit

• Households
• Indviduals

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame utilized in the renters and owner occupiers and home builders/ developers was the current National Sample Survey and Evaluation Program V (NASSEP V) frame which is a household based sampling frame developed and maintained by KNBS. During the 2009 population and housing census, each sub-location was subdivided into approximately 96,000 census Enumeration Areas (EAs).

In cognizance of the devolved system of government and the need to have a static system of administrative boundaries, NASSEP V utilizes the county boundaries. The frame was implemented using a multi-tiered structure, in which a set of 4 sub-samples were developed. It is based on the list of EAs from the 2009 Kenya Population and Housing Census. The frame is stratified according to county and further into rural and urban areas. Each of the sub-samples is representative at county and at national (i.e. urban/rural) level and contains 1,340 clusters. NASSEP V was developed using a two-stage stratified cluster sampling format with the first stage involving selection of Primary Sampling Units (PSUs) which were the EAs using Probability Proportional to Size (PPS) method. The second stage involved the selection of households for various surveys.

2012/2013 KNHS utilized all the clusters in C2 sub-sample of the NASSEP V frame excluding Wajir, Garissa and Mandera counties. The target for the household component of the survey was to obtain approximately 19,140 completed household interviews.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The survey implemented a Paper and Pencil Interviewer (PAPI) technology administered by trained enumerators while data entry was decentralised to collection teams with a supervisor. Data was keyed from twelve (12) questionnaires namely household based questionnaire for renters, owner occupier and home builders, building financiers such as banks and SACCOs, building professionals such as architects, valuers etc., institutional questionnaires covering Local Authorities, Lands department, Ministry of Housing, National Environmental Management Authority, Physical Planning department and, Water and Sewerage Service providers and housing developers. Each of these questionnaires was keyed individually.

The data processing of the 2012/13 Kenya National Housing Survey results started by developing data capture application for the various questionnaires using CSPro software. Quality of the developed screens was informed by the results derived from 2012/2013 KNHS pilot survey. Every county data collection team had a trained data entry operator and two data analysts were responsible for ensuring data was submitted daily by the trained data entry operators. They also cross-checked the accuracy of submitted data by doing predetermined frequencies of key questions. The data entry operators were informed of detected errors for them to re-enter or ask the data collection team to verify the information.

Data entry was done concurrently with data collection therefore guaranteeing fast detection and correction of errors/inconsistencies. Data capture screens incorporated inbuilt quality control checks triggered in case of invalid entry. Such checks were necessary to guarantee minimal data errors that would be removed during the validation stage (data cleaning).

In data cleaning, a team comprising subject-matter specialists developed editing specifications which were programmed to cross-check raw data for errors and inconsistencies. The printed log file was evaluated with a view to fixing errors and inconsistencies found. Further on, they also developed data tabulation plans to be used on the final datasets and cross checked tabulated outputs were used in writing the survey basic report.