Namibia Financial Inclusion Survey
Namibia, 2017
Namibia Statistics Agency
Identification
Title
Namibia Financial Inclusion Survey
Subtitle
2017
Translated title
English
Countries
| Name | Abbreviation |
|---|---|
| Namibia | NAM |
idno
NAM_NSA_2017_NFISV4
Study notes
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.
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.
Kind of data
Sample survey data [ssd]
Unit of analysis
Individuals, households
Version
Version date
2018
Scope
Topics
| Topic | Vocabulary | URI |
|---|---|---|
| Household information and demographics | ||
| Farming | ||
| Income and Expenditure | ||
| Access to infrastructure | ||
| Informal products | ||
| Bank penetration | ||
| Risk and risk Mitigation | ||
| Borrowing | ||
| Financial capability | ||
| Saving | ||
| Remittances |
Keywords
| keyword | URI |
|---|---|
| Financial capability | |
| Financial Literacy | |
| Bank penetration | |
| Financial Access | |
| Financial inclusion/exclusion |
Coverage
Geographic 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 results are only representative at national level, but not at regional level.
Unit of analysis
Individuals, households
Universe
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
Producer(s)
| Name | Affiliation | Role |
|---|---|---|
| FinMark Trust | Technical assistance in questionaire design and data analysis |
Funding agencies
| Name | Abbreviation | Role |
|---|---|---|
| Bank of Namibia | BoN | Funding |
| World Bank group | WB | Funding |
Sampling
Sampling procedure
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.
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.
Response rate
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.
It was not possible to interview all the selected households when the household sample was implemented, due to refusals or non-contacts.
Weighting
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).
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).
Data Collection
Dates of collection
| Start | End | Cycle |
|---|---|---|
| 2017-10-02 | 2017-11-13 | 1 month and 9 days |
Time period(s)
| Start | End | Cycle |
|---|---|---|
| 2017-10-02 | 2017-11-13 | 1 month and 9 days |
Mode of data collection
Face-to-face [f2f]
Data collection supervision
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 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.
Questionnaires
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.
Data collector(s)
| Name | Abbreviation | Affiliation |
|---|---|---|
| Namibia Statistics Agency | NSA | Mimnistry of Economic Planning |
Data Processing
Data editing
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 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 access
Access authorities
| Name | Affiliation | URI | |
|---|---|---|---|
| Namibia Statistics Agency | NSA | +24 614313200 | www.nsa.org.na |
Citation requirements
Namibia Statistics Agency,2017. Namibia Financial Inclusion Survey 2017 Report. Windhoek
Disclaimer and copyrights
Disclaimer
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.
Copyrights
Namibia Statistics Agency
contacts
Contact(s)
| Name | Affiliation | URI | |
|---|---|---|---|
| Namibia Statistics Agency | NSA | +264614313200 | Ministry of Economic Planning |