Namibia Financial Inclusion Survey
2017
Namibia, 2017
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NAM_NSA_2017_NFIS V4
Namibia Financial Inclusion Survey
2017
NFIS
English
| Name | Country code |
|---|---|
| Namibia | NAM |
Socio-Economic/Monitoring Survey [hh/sems]
The 2017 Namibia Financial Inclusion Survey (NFIS) was the fourth of its kind to be conducted in Namibia, however, the first for the Namibia Statistics agency (NSA). The first three financial inclusion surveys were conducted in 2004, 2007 and 2011 respectively, through the Finscope survey of FinMark Trust, an independent trust based in South Africa. The decision to have the survey conducted by the NSA resulted from several engagements between the NSA, Bank of Namibia (BON) and FinMark Trust. The localization of the survey was necessitated by the need to ensure sustainable conduct of the survey, funded by government and conducted by the agency that has the mandate to collect national data for policy making and development planning purposes in Namibia.
This report presents the main results of the 2017 Namibia Financial Inclusion Survey. The survey was conducted by the Namibia Statistics Agency, in all 14 regions of Namibia, with funding from the Bank of Namibia and the World Bank. By design, the NFIS surveys was intended to involve a range of stakeholders through syndicate membership to enrich the entire survey process through cross-cutting learning, sharing of information, and to facilitate the extended utilization of the final data.
A nationally representative sample of Namibians 16 years and older was employed. During October and November 2017 1863 face-to-face interviews were conducted, one interview per selected household. The data was captured into a tablet-based questionnaire using the Survey-To-Go application. The data collected was weighted to reflect the adult/eligible population (i.e. aged 16 years or older) in Namibia, as this is the minimum age legally allowed for any individual to make use of formal financial products in their own capacity. It is also important to note that the results of 2017 are representative only at national and urban/rural areas levels, but not regional.
· To measure the levels of financial inclusion (inclusive of formal and informal usage)
· To describe the landscape of access (type of products and services used by financially included individuals)
· To identify the drivers of, and barriers to the usage of financial products and services
· To track and compare results and provide an assessment of changes and reasons thereof (including possible impacts of interventions to enhance access)
· To stimulate evidence-based dialogue that will ultimately lead to effective public/private sector interventions that will increase and deepen financial inclusion strategies
· Provide information on new opportunities for increased financial inclusion and usage.
Sample survey data [ssd]
Individuals, households
Version
2018
Scope
Demographic characteristics
Income
Financial inclusion
Usage of financial products /services
| Topic |
|---|
| Household information and demographics |
| Farming |
| Income and Expenditure |
| Access to infrastructure |
| Informal products |
| Bank penetration |
| Risk and risk Mitigation |
| Borrowing |
| Financial capability |
| Saving |
| Remittances |
Coverage
National sampling frame is a list of small geographical areas called Primary Sampling Units (PSUs). There are a total of 6453 PSUs in Namibia that were created using the enumeration areas (EA) of the 2011 Population and Housing Census. The measure of size in the frame is the number of households within the PSU as reflected in the 2011 Census. The frame units were stratified first by region, and then by urban/rural areas within each region.
The results are only representative at national level, but not at regional level.
The target population for the NFIS 2017 was all people aged 16 and above who live in private households in Namibia. The eligible population living in institutions, such as hospitals, hostels, police barracks and prisons were not covered in this survey. However, private households within institutional settings such as teachers' houses in school premises were covered.
Producers and sponsors
| Name | Affiliation |
|---|---|
| Namibia Statistics Agency | NSA |
| Name | Role |
|---|---|
| FinMark Trust | Technical assistance in questionaire design and data analysis |
| Name | Abbreviation | Role |
|---|---|---|
| Bank of Namibia | BoN | Funding |
| World Bank group | WB | Funding |
Sampling
The target population for the NFIS 2017 was eligible members of private households in Namibia. The eligible population living in institutions, such as hospitals, hostels, police barracks and prisons were not covered in this survey. However, private households within institutional settings such as teachers' houses in school premises were covered. The sample design was a stratified three-stage cluster sample, where the first stage units were the PSUs, the second stage units were the households and the third stage were the eligible members, that is individuals who, by the time of the survey were 16 years or older, available during the duration of survey, mentally/physically capable to be interviewed and have resided in the selected household for at least six month preceding the survey. The age limit for the eligibility criteria was based on the fact that only individuals aged 16 years or above are officially authorized to get personal formal financial products (such as open a personal bank account) from formal financial institutions in Namibia, which makes them the target population of the financial sector. Only one individual was interviewed per selected household
The national sampling frame was used to select the first stage units (PSUs). The national sampling frame is a list of small geographical areas called Primary Sampling Units (PSUs) created using the enumeration areas (EAs) of 2011 Population and Housing Census. There are a total of 6 453 PSUs in Namibia. A total of 151 PSUs were selected from all the 14 regions, and 2 114 households were drawn from them, constituting the sample size. Power allocation procedures were adopted to distribute the samples across the regions so that the smaller regions will get adequate samples.
After data processing, 1863 out of 2114 sampled households were successfully interviewed, resulting in 88.1 percent response rate which is highly satisfactory given that the NSA subscribes to a response rate of 80 percent for all data collection in the social statistics domain. Overall, the rural response is higher than the urban response.
It was not possible to interview all the selected households when the household sample was implemented, due to refusals or non-contacts.
Weighting is a process of accounting for the selection probabilities and non-response in a sample survey. The inverse of these selection probabilities adjusted for non-response is called the design (base) weight. Given the population projections based on the 2011 Population and Housing Census figures, weight adjustment of the design weight was undertaken in order to ensure that the calculated survey estimates conforms to the projection totals. However, due to the limitations of post stratified weight adjustment in controlling a large number of cells at different levels, a complex procedure known as weight calibration was instead applied.
The sample sizes were determined to give reliable estimates of the population characteristics at the national and urban/ rural levels only. The sample was not determined to provide regional or constituency estimates. The design/base weights were the inverse of the selection probabilities, that is, the Inverse Sampling Rate (ISR) at the PSU, household and individual stages. The design weights were adjusted to account for household non-response. The non-response adjustment factor is the ratio of the sampled households to the responding households. The final step undertaken to in constructing the final weights at person/individual levels for the NFIS 2017 was to calibrate the design weights such that the respective aggregate totals matched the distribution of the population across key demographic variables such as age and sex nationally at urban/rural level. The control totals used for this calibration process were the 2017 population projections. This was achieved by running a Statistical Analysis System (SAS) Macro for weight calibration called GREGWT developed by Australian Bureau of Statistics (ABS).
Survey instrument
The 2017 NFIS questionnaire was made up of 13 sections in total. The questionnaire was transmitted onto CAPI (Computer aided Personal Interview) using the Survey-To-Go application.
The data processing methodology that was adopted for this study was the Computer Assisted Personal Interview method (CAPI). Data management tools to collect, transmit and store and clean (primary editing and recoding) survey data were designed and developed using surveyto Go computer system.
Data collection
| Start | End | Cycle |
|---|---|---|
| 2017-10-02 | 2017-11-13 | 1 month and 9 days |
| Start date | End date | Cycle |
|---|---|---|
| 2017-10-02 | 2017-11-13 | 1 month and 9 days |
- Face-to-face [f2f]
| Name | Affiliation | Abbreviation |
|---|---|---|
| Namibia Statistics Agency | Mimnistry of Economic Planning | NSA |
To ensure that reliable, quality and timely data were collected, a series of data assurance activities were undertaken at different levels of the survey. A pilot test was conducted to test the readiness of the fieldwork tools, and its results were used to improve the questionnaire, the CAPI application and the training manuals which were used in the main fieldwork. Field staff who were recruited for the main training received intensive training for two (2) weeks, and their participation in the main fieldwork was based on their performance evaluated through written tests. Moreover, during the main fieldwork, monitoring teams comprised of staff from the head office were sent to the regions at the beginning of the listing and interviewing phases respectively, to ensure that the field work was being conducted as planned and that all data collection rules and guidelines were being followed as prescribed. Monitoring teams had to observe interviews by at different households to monitor whether field staff were introducing the objectives of the survey properly and whether questions are asked as trained including the translation of questions from English to vernacular languages. In doing so remedial actions were taken timely without further delays and compromise to the data collection exercise.
In addition, daily transmission of the collected data to the head office were undertaken to ensure minimum effect in the event of loss or damage to the data collection tools (Tablets). As a result, secondary verification and completeness checks were carried out with the data collection application monitoring tool to ensure correct, complete and valid information are transmitted.
In order to ensure smooth running of the NFIS 2017, NSA undertook a pilot test for one week, 14-19 August 2017. A total of 2 PSUs were tested, by 2 field teams, 1 PSU allocated to each team. Two regions were selected for the pilot, Khomas and Kavango West and each region had 1 team working on 1 PSU.
The main objective of the pilot survey was to test whether the survey tools were going to measure what the survey intended to measure in terms of questions during the main fieldwork. This also involved testing the adequacy of logistics and administrative arrangements on the ground. The data processing plan was also tested through the use of the pilot survey data. The results for the pilot test were used to review and improve on the survey implementations in all areas of survey functionalities, such as review of the survey tools, draw up the final plans for the main survey in order to provide final estimations of resources required to implement survey activities effectively.
The main survey consisted of field teams operating within a region under the Regional Supervisor, a permanent position held by the NSA Regional statisticians (RS). Regional supervisors were supported by two (2) temporary IT technicians based at the head office who provided IT support to the regional field teams. Each IT technician was allocated 7 regions to support, oversee data transmission and management.
The field teams consisted of a team supervisor and two interviewers. Field personnel were recruited from their home areas since they needed to be familiar with the local terrain/locality and to facilitate interviews in local languages. In total 84 field staff were deployed for fieldwork for a period of about 8 weeks. The work plan was designed to include the first three weeks for listing of private households within the selected PSUs and the last three weeks to administer the questionnaire to the sampled 14 private households per PSU. Both listing and main data collection interviews were conducted through face-to-face interviews, in all 14 regions, from 2 October 2017 to 13 November 2017. Main interviews were conducted using a tablet administered questionnaire using Survey To Go (STG) application.
Data processing
The data processing methodology that was adopted for this study was the Computer Assisted Personal Interview. Data management series of operations to collect, transmit, clean and store the survey data were designed using SurveyToGo computer system onto the Dubloo platform.
Data entry is very crucial, since the quality of data collected impact heavily on the output. The collection process was designed to ensure that the data gathered are both defined and accurate, so that subsequent decisions based on the findings are valid.
Data appraisal
The most common measure of quality of the survey estimates reported from the sample surveys was the level of precision of the estimates. The quality indicators are meant to ascertain the analysis about the level of precision of the estimates at different domains. The statistical precision of the survey estimates were expressed using different types of statistics such as Standard errors (SE), the coefficient of variation (CV) and the Confidence Interval (CI). These statistics were used to indicate the level of precision of the survey estimates in estimating the population parameters of interest. There are a number of factors that can affect the precision of the survey estimates namely the size of the sample relative to the population size, the sample design and the variability of the characteristics of interest in the population. The data quality indicators were discussed in details in the following sub-section.
Distributor information
| Organization name | Abbreviation |
|---|---|
| Namibia Statistics Agency | NSA |
Data Access
| Name | Affiliation | URL | |
|---|---|---|---|
| Namibia Statistics Agency | NSA | www.nsa.org.na | +24 614313200 |
| Is signing of a confidentiality declaration required? | Confidentiality declaration text |
|---|---|
| yes | The Namibia Financial Inclusion Survey (NFIS) 2017 was conducted by the Namibia Statistics Agency (NSA) in collaboration with the Bank of Namibia, FinMark Trust of South Africa, under the provisions of the Statistics Act, 2011 (Act No. 9 of 2011). It is by the virtue of this Act that all information collected that could be linked to individual or households was, and will be kept strictly confidential. |
Namibia Statistics Agency,2017. Namibia Financial Inclusion Survey 2017 Report. Windhoek
Disclaimer and copyrights
The NSA as the original copllector of this data bears no responsibility for use of the data or for interpretations or inferences based upon further uses.
Namibia Statistics Agency
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Namibia Statistics Agency | NSA | +264614313200 | Ministry of Economic Planning |
Metadata production
NAM_NSA_2017_NFIS V4
| Name | Abbreviation |
|---|---|
| Namibia Statistics Agency | NSA |
2018
Metadata version
NAM_NSA_2017_NFIS_VOL4