Household Income and Expenditure Survey 2006
Kiribati, 2006
Kiribati National Statistical Office
Identification
IDNO
SPC_KIR_2006_HIES_v01_M_v01_A_PUF
Title
Household Income and Expenditure Survey 2006
Country
| Name | Country code |
|---|---|
| Kiribati | KIR |
Abstract
The purpose of the Household Income and Expenditure Survey (HIES) survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in Kiribati. This information will be used to guide policy makers in framing socio-economic developmental policies and in initiating financial measures for improving economic conditions of the people.
Some more specific outputs from the survey are listed below:
a) To obtain expenditure weights and other useful data for the revision of the consumer price index;
b) To supplement the data available for use in compiling official estimates of household accounts in the systems of national accounts;
c) To supply basic data needed for policy making in connection with social and economic planning;
d) To provide data for assessing the impact on household living conditions of existing or proposed economic and social measures, particularly changes in the structure of household expenditures and in household consumption;
e) To gather information on poverty lines and incidence of poverty throughout Kiribati.
Some more specific outputs from the survey are listed below:
a) To obtain expenditure weights and other useful data for the revision of the consumer price index;
b) To supplement the data available for use in compiling official estimates of household accounts in the systems of national accounts;
c) To supply basic data needed for policy making in connection with social and economic planning;
d) To provide data for assessing the impact on household living conditions of existing or proposed economic and social measures, particularly changes in the structure of household expenditures and in household consumption;
e) To gather information on poverty lines and incidence of poverty throughout Kiribati.
Kind of Data
Sample survey data [ssd]
Version
Version number
Version 01: Cleaned, labelled and anonymized version of the Master file.
Version Date
2008-12-02
Version Notes
Reconstructed dataset from an Access dataset.
Scope
Keywords
| Keyword |
|---|
| Kiribati |
| HIES |
| Income |
| Expenditure |
| Education |
| Economic activity |
| Health |
Coverage
Geographic Coverage
National Coverage and Regional Island Groups (Northern Gilberts, South Tarawa, Central Giberts, Southern Gilberts, Linix).
There are five main populations of interest for which estimates are required for the 2006 Kiribati HIES: South Tarawa, Northern, Central and Southern Gilbert Islands, and the Line Islands.
There are five main populations of interest for which estimates are required for the 2006 Kiribati HIES: South Tarawa, Northern, Central and Southern Gilbert Islands, and the Line Islands.
Unit of Analysis
Persons, Households, Expenditure items.
Universe
The survey covered all persons resident in private households during the month of October 2006. It excluded persons living in institutions such as dormitories, hospitals, prisons or other institutions. Also excluded from the survey were ex-patriot temporary residents and permanent residents who were not residing (and intending to reside) in Kiribati for at least 12 months.
Income data were collected from persons aged 15 years and over and expenditure data from obtained from all household members at a household level.
Income data were collected from persons aged 15 years and over and expenditure data from obtained from all household members at a household level.
Producers and sponsors
Authoring entity/Primary investigators
| Agency Name | Affiliation |
|---|---|
| Kiribati National Statistical Office | Government of Kiribati |
Producers
| Name | Role |
|---|---|
| Pacific Community | Technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Kiribati Ministry Of Finance | Mof | Staffing costs |
| Asian Development Bank | ADB | Survey Costs |
Sampling
Sampling Procedure
Documentation for Kiribati HIES Sample Selection:
SAMPLE SIZE:
In determining an appropriate sample size for a survey of this nature, numerous factors come into the equation. These include:
a) The degree of accuracy required for key estimates
b) The population size of the country
c) The manner in which the sample is selected
d) Cost or staffing constraints which may exist
e) Whether or not estimates are required for sub-populations
f) The level of variability in the data being collected
Each of these factors have different magnitudes of importance, but the major priority should always be on selecting a sample big enough to produce results of suitable accuracy. Many of these issues are generally known as well - for instance:
· A user group may pre-specify what level of accuracy they may wish to achieve for the survey
· The population of a country can normally be estimated to a reasonable level of accuracy
· The sample selection technique adopted is known
· Cost and staff constraints are generally known, and
· A user group can once again provide information on whether estimates for sub-populations are required.
The one thing that normally isn't known is the degree of variability in the data being collected - this information comes after the survey. This factor is important because if there is not much variability in the data for key estimates, then the sample size does not need to be as large, and vice versa.
Without this sort of information, determining the appropriate sample size for a survey can often involve a bit of guess work. For that reason, based on previous survey experience in other Pacific Island countries, a sample of 10 per cent was considered more than sufficient for Kiribati. An additional 10 per cent of sample was selected to allow for sample loss.
As a result, a sample size of 1,555 households (10 per cent of 13,999, with a 10 per cent top-up) was considered suitable for the survey.
Allocation to "Target Areas"
For the Kiribati HIES, five target areas were identified as sub-populations for which estimates would be desirable. These five areas were:
1) South Tarawa
2) Northern Gilbert
3) Central Gilbert
4) Southern Gilbert
5) Line/Phoenix Islands
Once the sample size of 1,555 had been determined, the next step was determining how the sample should be allocated to each of these target areas in order to produce the required level of accuracy for each area. In order to achieve this, the sample was allocated in such a manner that the expected level of accuracy for each stratum would be similar. The resulting sample allocation can be found in the table below.
STRATIFICATION:
To achieve better representation within each target group, each target group was further stratified by grouping "like" islands. The plan from there was to select an island from each stratum to represent it. As a result, 11 strata were formed, with each of the 23 populated island/atolls of Kiribati allocated to one of these strata. The resulting strata, and islands which make them up, can be found in the following table.
The allocation of the sample to stratum within each target group was achieved by simply allocating the sample proportional to the population for that stratum. For example, for the target group Northern Gilbert, an overall sample size of 323 was desirable. To determine how much of that sample would be allocated to the first stratum which consisted of Makin and Butaritari, the following formula was applied:
n (Makin & Butaritari) = 323 * (889)/(889+1290+867)
= 94
EXCLUDED AREAS:
Although it would be desirable to cover all of Kiribati for this survey, due to cost and time constraints a couple of areas were excluded from the frame before the selections were made. The two areas removed from scope were:
· Banaba
· Kanton
The impact on final estimates is considered to be very small given the small populations on these two islands; 61 households on Banaba, and 9 households on Kanton. This accounts for about 0.5 per cent of the population of Kiribati.
SAMPLE SELECTION TECHNIQUE:
Selection of Islands:
For the stratum with more than one island, an island had to be selected in order to represent that stratum. The process used for this stage of selection was probability proportional to size (pps) sampling, where the size measure was the number of households on the island.
An example of how this process worked can be found below for the Central Gilbert - Group 2. For this stratum, a random number was selected between 0 and 1,005. Given the random number (254), fell within the cumulative number of households for Abemama, then that island was selected.
Selection of Households:
To minimize the travel requirements of interviewers, and thus travel costs, a two stage process was adopted to selected households.
The first stage of the process involved selecting EAs using probability proportional to size (pps) sampling. The required number of EAs to select from each island was simply determined by dividing the number of households to sample on that island by roughly 15, where 15 was the cluster size chosen from each selected EA.
Having selected the EAs in sample, a systematic skip was run through the list of households for each EA to determine which households would be selected in sample. These selections were performed in the NSO, and the lists provided to interviewers in the field. The lists used for this stage of selection were based on the 2005 Population Census, and thus would be out-of-date by a year or so, but given the significant gains in simplifying field logistics, this was the preferred option.
SAMPLE SIZE:
In determining an appropriate sample size for a survey of this nature, numerous factors come into the equation. These include:
a) The degree of accuracy required for key estimates
b) The population size of the country
c) The manner in which the sample is selected
d) Cost or staffing constraints which may exist
e) Whether or not estimates are required for sub-populations
f) The level of variability in the data being collected
Each of these factors have different magnitudes of importance, but the major priority should always be on selecting a sample big enough to produce results of suitable accuracy. Many of these issues are generally known as well - for instance:
· A user group may pre-specify what level of accuracy they may wish to achieve for the survey
· The population of a country can normally be estimated to a reasonable level of accuracy
· The sample selection technique adopted is known
· Cost and staff constraints are generally known, and
· A user group can once again provide information on whether estimates for sub-populations are required.
The one thing that normally isn't known is the degree of variability in the data being collected - this information comes after the survey. This factor is important because if there is not much variability in the data for key estimates, then the sample size does not need to be as large, and vice versa.
Without this sort of information, determining the appropriate sample size for a survey can often involve a bit of guess work. For that reason, based on previous survey experience in other Pacific Island countries, a sample of 10 per cent was considered more than sufficient for Kiribati. An additional 10 per cent of sample was selected to allow for sample loss.
As a result, a sample size of 1,555 households (10 per cent of 13,999, with a 10 per cent top-up) was considered suitable for the survey.
Allocation to "Target Areas"
For the Kiribati HIES, five target areas were identified as sub-populations for which estimates would be desirable. These five areas were:
1) South Tarawa
2) Northern Gilbert
3) Central Gilbert
4) Southern Gilbert
5) Line/Phoenix Islands
Once the sample size of 1,555 had been determined, the next step was determining how the sample should be allocated to each of these target areas in order to produce the required level of accuracy for each area. In order to achieve this, the sample was allocated in such a manner that the expected level of accuracy for each stratum would be similar. The resulting sample allocation can be found in the table below.
STRATIFICATION:
To achieve better representation within each target group, each target group was further stratified by grouping "like" islands. The plan from there was to select an island from each stratum to represent it. As a result, 11 strata were formed, with each of the 23 populated island/atolls of Kiribati allocated to one of these strata. The resulting strata, and islands which make them up, can be found in the following table.
The allocation of the sample to stratum within each target group was achieved by simply allocating the sample proportional to the population for that stratum. For example, for the target group Northern Gilbert, an overall sample size of 323 was desirable. To determine how much of that sample would be allocated to the first stratum which consisted of Makin and Butaritari, the following formula was applied:
n (Makin & Butaritari) = 323 * (889)/(889+1290+867)
= 94
EXCLUDED AREAS:
Although it would be desirable to cover all of Kiribati for this survey, due to cost and time constraints a couple of areas were excluded from the frame before the selections were made. The two areas removed from scope were:
· Banaba
· Kanton
The impact on final estimates is considered to be very small given the small populations on these two islands; 61 households on Banaba, and 9 households on Kanton. This accounts for about 0.5 per cent of the population of Kiribati.
SAMPLE SELECTION TECHNIQUE:
Selection of Islands:
For the stratum with more than one island, an island had to be selected in order to represent that stratum. The process used for this stage of selection was probability proportional to size (pps) sampling, where the size measure was the number of households on the island.
An example of how this process worked can be found below for the Central Gilbert - Group 2. For this stratum, a random number was selected between 0 and 1,005. Given the random number (254), fell within the cumulative number of households for Abemama, then that island was selected.
Selection of Households:
To minimize the travel requirements of interviewers, and thus travel costs, a two stage process was adopted to selected households.
The first stage of the process involved selecting EAs using probability proportional to size (pps) sampling. The required number of EAs to select from each island was simply determined by dividing the number of households to sample on that island by roughly 15, where 15 was the cluster size chosen from each selected EA.
Having selected the EAs in sample, a systematic skip was run through the list of households for each EA to determine which households would be selected in sample. These selections were performed in the NSO, and the lists provided to interviewers in the field. The lists used for this stage of selection were based on the 2005 Population Census, and thus would be out-of-date by a year or so, but given the significant gains in simplifying field logistics, this was the preferred option.
Response Rate
The response rate was 85.6% of the total number of households 1,555.
Weighting
Sample weights were calculated for each stratum and adjusted for non-response. Weights for the survey were derived using the inverse of the households probability of selection.
Data Collection
Dates of Data Collection (YYYY/MM/DD)
| Start date | End date |
|---|---|
| 2006-10-02 | 2006-11-14 |
Mode of data collection
Face-to-face [f2f]
Supervision
Responsibilities and Functions of the Supervisor
To supervise in accordance with the directions of the Statistics Office staff, the completion of the HIES 2006 for all selections, specifically to:
a) With assistance from the Island Council, undertake the recruitment of interviewers on their respective islands;
b) Ensure that all schedules and materials are distributed to interviewers according to the instructions of the NSO staff;
c) Ensure that the interviewers understand which household he/she is responsible for and that none are left out;
d) With assistance from the interviewer, conduct information sessions for selected households prior to collecting information from those households;
e) Visit interviewers regularly during the collection phase to make sure they are carrying out their responsibilities correctly;
f) Make sure all forms from the interviewers are accounted for at the end of each 3 week period;
g) Do spot checks for completeness of questionnaires and deal with any problems that might arise in the field;
h) Dispatch all completed questionnaires (in sealed envelopes) to the NSO after he/she is fully satisfied that
(i) All the entries of the questionnaires are properly completed.
The National Statistics Office recruited and trained 12 supervisors. The completed survey forms were processed by staff of the National Statistics Office who recorded their receipt from the supervisors and checked the questionnaires for completeness.
To supervise in accordance with the directions of the Statistics Office staff, the completion of the HIES 2006 for all selections, specifically to:
a) With assistance from the Island Council, undertake the recruitment of interviewers on their respective islands;
b) Ensure that all schedules and materials are distributed to interviewers according to the instructions of the NSO staff;
c) Ensure that the interviewers understand which household he/she is responsible for and that none are left out;
d) With assistance from the interviewer, conduct information sessions for selected households prior to collecting information from those households;
e) Visit interviewers regularly during the collection phase to make sure they are carrying out their responsibilities correctly;
f) Make sure all forms from the interviewers are accounted for at the end of each 3 week period;
g) Do spot checks for completeness of questionnaires and deal with any problems that might arise in the field;
h) Dispatch all completed questionnaires (in sealed envelopes) to the NSO after he/she is fully satisfied that
(i) All the entries of the questionnaires are properly completed.
The National Statistics Office recruited and trained 12 supervisors. The completed survey forms were processed by staff of the National Statistics Office who recorded their receipt from the supervisors and checked the questionnaires for completeness.
Type of Research Instrument
Four questionnaire forms were designed to collect information on household size and composition, personal and household income, major household expenditure, and regular food and household supply expenditures in the diaries. The income and expenditure questionnaires were administered by interview during the survey period, and the diaries were completed by the households over a two-week period. An additional questionnaire was developed and administered to collect detailed information on health facility utilization and access, educational attendance and attainment, and labour force status.
The questionnaires were published in English.
-HOUSEHOLD CONTROL FORM:
The Household Control Form (HCF) should be filled in during the first visit to the household. Its main objective is to collect basic demographic information about members of the household. Before completing this form however, the interviewer needs to determine if the household is in scope for the survey.
Only those households which have been residing in Kiribati for more than 1 year, or those households who intend to reside in Kiribati for a total of 12 months or more, should complete this form and partake in the survey. These households can be identified by going through section (e) in the field book for interviewers. If the household does not meet these criteria, then the survey is over. In assessing the eligibility of a household to be in the survey, use some common sense - there will be many occasions when it will be clear that the household has always lived in Kiribati, so don't bother asking these questions.
Once this issue has been addressed, the HCF can be filled in for the household. The HCF form is to record names of all the usual members of the household. Information on relationship to head of household, sex, date of birth and ethnicity are asked of all members in the household. For persons aged 15 and over, questions on marital status, educational attainment, activity status, literacy status and internet usage are also asked. Codes should be used to complete these questions, and they can be found in the interviewer's field book in section (a). You must enter the code for these questions.
-EXPENDITURE QUESTIONNAIRE:
The purpose of this questionnaire is to record household expenditure that is not included in the diary. There are some big purchases that the household may only make once or twice a year. Also the household may make regular payments, which may not be done during the survey period, and we would need to know such payments to produce good and complete estimates.
There are 15 sections in the Expenditure Questionnaire which relate to the following:
1. Dwelling characteristics
1. Dwelling tenure
2. Mortgages and loans for purchase of dwellings
3. Insurance policies
4. Construction of new dwellings
5. Major home improvement
6. Household operations
7. Transportation
8. Overseas and domestic travel
9. Education, recreation, sport and culture
10. Loans
11. Contribution to benefit schemes
12. Medical and health services
13. Miscellaneous payments
14. Agricultural assets
Detailed instructions for each section are not provided here as they can be found in the questionnaire itself on the left hand side of the booklet.
-INCOME QUESTIONNAIRE:
This questionnaire is to record the household's total income received or earned in the last 12 months. Information will be collected for all usual members of the household who are 15 years and over. Visitors are not to include their income earned in this section.
There are 7 sections in the Income Questionnaire which relate to the following:
1. Working for wage and/or salary
2. Agriculture, livestock, fishing and other sales
3. Other self employed and business operations
4. Previous jobs held in the last 12 months
5. Services provided to other private households
6. Welfare benefits/allowances
7. Other income, including remittances
Detailed instructions for each section are not provided here as they can be found in the questionnaire itself on the left hand side of the booklet.
-WEEKLY DIARY:
For each household observed, there will be two books, one for the first week and one for the second week. This is to keep a record of all daily expenditure for the 14 days. Interviewers have to make sure that these diaries are being kept for each day. Instructions on how to use the diary have been written on the front pages of these diaries.
In normal circumstances, the head of household organises the household activity. In some households this may not be the case - some members of that particular household may not be seeking the authority of the head when some expenditure is encountered. This situation may result in not recording all expenditure in the diary. The interviewer should discuss the matter with the head of the household to ensure that each member's expenditure is recorded in the household diary. If a member of the household does not co-operate with the head of the household he/she may be allocated a separate diary. That member of the household should be explained the full responsibility of recording the diary.
There are 4 main sections making up each weekly diary:
1) Items bought
2) Consumption of home produced commodities
3) Gifts of cash or goods
4) Winnings from gambling.
The questionnaires were published in English.
-HOUSEHOLD CONTROL FORM:
The Household Control Form (HCF) should be filled in during the first visit to the household. Its main objective is to collect basic demographic information about members of the household. Before completing this form however, the interviewer needs to determine if the household is in scope for the survey.
Only those households which have been residing in Kiribati for more than 1 year, or those households who intend to reside in Kiribati for a total of 12 months or more, should complete this form and partake in the survey. These households can be identified by going through section (e) in the field book for interviewers. If the household does not meet these criteria, then the survey is over. In assessing the eligibility of a household to be in the survey, use some common sense - there will be many occasions when it will be clear that the household has always lived in Kiribati, so don't bother asking these questions.
Once this issue has been addressed, the HCF can be filled in for the household. The HCF form is to record names of all the usual members of the household. Information on relationship to head of household, sex, date of birth and ethnicity are asked of all members in the household. For persons aged 15 and over, questions on marital status, educational attainment, activity status, literacy status and internet usage are also asked. Codes should be used to complete these questions, and they can be found in the interviewer's field book in section (a). You must enter the code for these questions.
-EXPENDITURE QUESTIONNAIRE:
The purpose of this questionnaire is to record household expenditure that is not included in the diary. There are some big purchases that the household may only make once or twice a year. Also the household may make regular payments, which may not be done during the survey period, and we would need to know such payments to produce good and complete estimates.
There are 15 sections in the Expenditure Questionnaire which relate to the following:
1. Dwelling characteristics
1. Dwelling tenure
2. Mortgages and loans for purchase of dwellings
3. Insurance policies
4. Construction of new dwellings
5. Major home improvement
6. Household operations
7. Transportation
8. Overseas and domestic travel
9. Education, recreation, sport and culture
10. Loans
11. Contribution to benefit schemes
12. Medical and health services
13. Miscellaneous payments
14. Agricultural assets
Detailed instructions for each section are not provided here as they can be found in the questionnaire itself on the left hand side of the booklet.
-INCOME QUESTIONNAIRE:
This questionnaire is to record the household's total income received or earned in the last 12 months. Information will be collected for all usual members of the household who are 15 years and over. Visitors are not to include their income earned in this section.
There are 7 sections in the Income Questionnaire which relate to the following:
1. Working for wage and/or salary
2. Agriculture, livestock, fishing and other sales
3. Other self employed and business operations
4. Previous jobs held in the last 12 months
5. Services provided to other private households
6. Welfare benefits/allowances
7. Other income, including remittances
Detailed instructions for each section are not provided here as they can be found in the questionnaire itself on the left hand side of the booklet.
-WEEKLY DIARY:
For each household observed, there will be two books, one for the first week and one for the second week. This is to keep a record of all daily expenditure for the 14 days. Interviewers have to make sure that these diaries are being kept for each day. Instructions on how to use the diary have been written on the front pages of these diaries.
In normal circumstances, the head of household organises the household activity. In some households this may not be the case - some members of that particular household may not be seeking the authority of the head when some expenditure is encountered. This situation may result in not recording all expenditure in the diary. The interviewer should discuss the matter with the head of the household to ensure that each member's expenditure is recorded in the household diary. If a member of the household does not co-operate with the head of the household he/she may be allocated a separate diary. That member of the household should be explained the full responsibility of recording the diary.
There are 4 main sections making up each weekly diary:
1) Items bought
2) Consumption of home produced commodities
3) Gifts of cash or goods
4) Winnings from gambling.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Kiribati National Statistics Office | KNSO | Government of Kiribati |
Data Processing
Cleaning Operations
The completed survey forms were processed by staff of the National Statistics Office who recorded their receipt from the supervisors and checked the questionnaires for completeness. The status of incomplete questionnaires was recorded as either out of scope, vacant dwelling, unable to be contacted, and refused to respond.
The completed questionnaires were entered into a data entry system (CSpro) and after editing and imputation, the data was loaded into a database (MSAccess) and tabulated using Excel pivot tables.
There are five types of checks performed: Structural check, Verification check, Consistency check, Macro Editing check, Data Quality assessment
Edit lists have been produced for health module, income and expenditure questionnaire which need to been checked against the questionnaires.
On the edit list correct the error by crossing out the incorrect or missing value and enter the correct value in red.
Missing amounts that are also missing on the questionnaire will need to be estimated using estimates from questionnaires in the same EA batch.
For the diaries, concatenate the batch files for each province and export to tab delimited files. Import into Excel and calculate unit price for each item using quantities and weights where possible.
Filter records for each item code and check for outlier unit price values (both large and small values as well as missing values). Missing amounts will need to be estimated using average prices from the items within the same EA.
The completed questionnaires were entered into a data entry system (CSpro) and after editing and imputation, the data was loaded into a database (MSAccess) and tabulated using Excel pivot tables.
There are five types of checks performed: Structural check, Verification check, Consistency check, Macro Editing check, Data Quality assessment
Edit lists have been produced for health module, income and expenditure questionnaire which need to been checked against the questionnaires.
On the edit list correct the error by crossing out the incorrect or missing value and enter the correct value in red.
Missing amounts that are also missing on the questionnaire will need to be estimated using estimates from questionnaires in the same EA batch.
For the diaries, concatenate the batch files for each province and export to tab delimited files. Import into Excel and calculate unit price for each item using quantities and weights where possible.
Filter records for each item code and check for outlier unit price values (both large and small values as well as missing values). Missing amounts will need to be estimated using average prices from the items within the same EA.
Other Processing
The completed questionnaires were entered into the CSPro data entry system.
HIES DATA PROCESSING:
1. Application Files
The data entry applications have been developed with CSPRO 3.1. There are 3 separate data entry applications corresponding to the different HIES questionnaires:
a. HIES 2006: (HCF + Income +Expenditure)
b. HIES 2006 Diary: (Household diary)
c. HIES 2006 HELF: (Health, Education, Labour Force)
Each application comprises three modules: a data dictionary, a forms file, and an application file. The data dictionary specifies all records and fields in the data file as well as the value ranges. The forms file specifies the layout and order of the data entry forms. The application file specifies the editing logic, including skips, lookup lists, nil and large values, and consistency checks.
The applications are stored on the data entry PCs in the folder: c:\HIES\Data Entry. The applications are selected via the HIES .pff icon on each PC. Each PC will have a different icon depending on the type of questionnaire being processed.
2. Data Files
Before data entry the default data file is replaced with the filename of the current batch, where each EA is a batch. Use the following filename templates 'QQisea.dat' where QQ = questionnaire type, is = Island code, ea = EA.number.
The batch data files are stored on the data server in the folder V:\HIES data files\data. Each questionnaire type is stored in a separate sub-folder: ./IE, ./DY, ./HE. A back up of this folder should be made on a daily basis and the files stored in .\backup\data folder.
3. Coding Operations
The HIES field staff are responsible for the coding of the household diaries which need to be coded according to the item code list. The coding of the diaries need to be completed for each batch before sending to the data entry operators.
For missing amounts for expenditure items listed in the diaries an estimate needs to be made of the costs of item. Refer to other diaries in the batch to estimate the local cost of the item. Enter the estimated cost in red pen.
For large expenditure items listed in the diaries a check should be made to ensure that the items are captured in the expenditure questionnaire. If not they should be added.
As the other questionnaires are mostly pre-coded, the data entry supervisor will code the income and expenditure questionnaires (especially for occupation & industry).
The data entry supervisor separates the batches into the three questionnaire types for data entry, and then returns them to their original envelopes for storage after the structural checks have been performed.
4. Data Entry operations
The data entry supervisor is responsible for ensuring the data is entered into the system according to the instructions in the HIES data entry manual. The data entry operators will be trained by the supervisor to follow the data entry procedures, including the re-checking of entered data. The operators are supervised during data entry operations and issues raised by them dealt with by the supervisor promptly.
As there more than 500 households to be processed over a period of two months, each operator is to complete a minimum of 10 households per day. Each batch should be completed before the operator takes a tea/lunch break or finishes for the day. The supervisor should monitor the work of the operators and take action to ensure the timetable is maintained.
To assess the level of accuracy during data entry, every tenth batch should be verified by re-entering the batch again preferably by a different operator. The batch should be named with a .ver suffix to distinguish it from the original file. The original and verified batches should be compared and a mismatch statistic produced and recorded.
5. Data Verification operations
For each batch, the supervisor performs a structural check by reviewing the file tree to ensure that all questionnaires have been entered and checked off on the household listing. If the numbers of households on the listing disagree with numbers entered, then the differences are resolved by either adding/deleting households from the system or amending the household listing.
If commodity items are not found in the item codes listing then the supervisor adds the code and description to the itemcodes.dat file by accessing the “itemcodes.ent” application on the data entry and master PCs. Any false errors should be reported to the developer for amendment.
6. Data Editing operations
After each batch is completed the supervisor should check that all person details have been entered from the household listing form (HCF) and should review the income and expenditure questionnaires for each batch ensuring that all items have been entered correctly. Any omitted or incorrect items should be entered into the system.
The supervisor is required to perform outlier checks (large or small values) on the batched diary data by calculating unit price (amount/quantity) and comparing prices for each item. This is to be conducted by loading the data into Excel files and sorting data by unit price for each item. Any changes to prices or quantities will be made on the Excel file.
7. Data Auditing operations
A list of all EAs should be maintained by the data entry supervisor and checked off once all households in the EA have been entered. The list should contain information on the number of households entered by EA. Any missing or incomplete questionnaires should be recorded. The number of entered households in each EA should be reconciled with the field listing.
If there are missing questionnaires or incomplete responses an attempt should be made to contact the field supervisor to obtain the questionnaires or responses. Also any problems raised during the data entry operations should be referred to the field supervisor if the responses are considered to be incorrect or invalid.
8. Data Management procedures
Once the batch has been entered, verified and audited, the data file should be stored on the server in the HIES data files folder under the sub-folder './Final Data'. Each batch should be stored in the appropriate sub-folder i.e. IE, DY, HE. This data should also be backed up in the ./backup/final data folder and a copy made on a CD on a weekly basis.
After data entry is completed, check that all batch files have been entered and are present in the /Final Data folder. There should be exactly101 data files in each subfolder that conform to the standard naming convention. If any files are missing or duplicated, resolve the issue by either re-entering the missing batch or deleting the duplicate data file.
HIES DATA PROCESSING:
1. Application Files
The data entry applications have been developed with CSPRO 3.1. There are 3 separate data entry applications corresponding to the different HIES questionnaires:
a. HIES 2006: (HCF + Income +Expenditure)
b. HIES 2006 Diary: (Household diary)
c. HIES 2006 HELF: (Health, Education, Labour Force)
Each application comprises three modules: a data dictionary, a forms file, and an application file. The data dictionary specifies all records and fields in the data file as well as the value ranges. The forms file specifies the layout and order of the data entry forms. The application file specifies the editing logic, including skips, lookup lists, nil and large values, and consistency checks.
The applications are stored on the data entry PCs in the folder: c:\HIES\Data Entry. The applications are selected via the HIES .pff icon on each PC. Each PC will have a different icon depending on the type of questionnaire being processed.
2. Data Files
Before data entry the default data file is replaced with the filename of the current batch, where each EA is a batch. Use the following filename templates 'QQisea.dat' where QQ = questionnaire type, is = Island code, ea = EA.number.
The batch data files are stored on the data server in the folder V:\HIES data files\data. Each questionnaire type is stored in a separate sub-folder: ./IE, ./DY, ./HE. A back up of this folder should be made on a daily basis and the files stored in .\backup\data folder.
3. Coding Operations
The HIES field staff are responsible for the coding of the household diaries which need to be coded according to the item code list. The coding of the diaries need to be completed for each batch before sending to the data entry operators.
For missing amounts for expenditure items listed in the diaries an estimate needs to be made of the costs of item. Refer to other diaries in the batch to estimate the local cost of the item. Enter the estimated cost in red pen.
For large expenditure items listed in the diaries a check should be made to ensure that the items are captured in the expenditure questionnaire. If not they should be added.
As the other questionnaires are mostly pre-coded, the data entry supervisor will code the income and expenditure questionnaires (especially for occupation & industry).
The data entry supervisor separates the batches into the three questionnaire types for data entry, and then returns them to their original envelopes for storage after the structural checks have been performed.
4. Data Entry operations
The data entry supervisor is responsible for ensuring the data is entered into the system according to the instructions in the HIES data entry manual. The data entry operators will be trained by the supervisor to follow the data entry procedures, including the re-checking of entered data. The operators are supervised during data entry operations and issues raised by them dealt with by the supervisor promptly.
As there more than 500 households to be processed over a period of two months, each operator is to complete a minimum of 10 households per day. Each batch should be completed before the operator takes a tea/lunch break or finishes for the day. The supervisor should monitor the work of the operators and take action to ensure the timetable is maintained.
To assess the level of accuracy during data entry, every tenth batch should be verified by re-entering the batch again preferably by a different operator. The batch should be named with a .ver suffix to distinguish it from the original file. The original and verified batches should be compared and a mismatch statistic produced and recorded.
5. Data Verification operations
For each batch, the supervisor performs a structural check by reviewing the file tree to ensure that all questionnaires have been entered and checked off on the household listing. If the numbers of households on the listing disagree with numbers entered, then the differences are resolved by either adding/deleting households from the system or amending the household listing.
If commodity items are not found in the item codes listing then the supervisor adds the code and description to the itemcodes.dat file by accessing the “itemcodes.ent” application on the data entry and master PCs. Any false errors should be reported to the developer for amendment.
6. Data Editing operations
After each batch is completed the supervisor should check that all person details have been entered from the household listing form (HCF) and should review the income and expenditure questionnaires for each batch ensuring that all items have been entered correctly. Any omitted or incorrect items should be entered into the system.
The supervisor is required to perform outlier checks (large or small values) on the batched diary data by calculating unit price (amount/quantity) and comparing prices for each item. This is to be conducted by loading the data into Excel files and sorting data by unit price for each item. Any changes to prices or quantities will be made on the Excel file.
7. Data Auditing operations
A list of all EAs should be maintained by the data entry supervisor and checked off once all households in the EA have been entered. The list should contain information on the number of households entered by EA. Any missing or incomplete questionnaires should be recorded. The number of entered households in each EA should be reconciled with the field listing.
If there are missing questionnaires or incomplete responses an attempt should be made to contact the field supervisor to obtain the questionnaires or responses. Also any problems raised during the data entry operations should be referred to the field supervisor if the responses are considered to be incorrect or invalid.
8. Data Management procedures
Once the batch has been entered, verified and audited, the data file should be stored on the server in the HIES data files folder under the sub-folder './Final Data'. Each batch should be stored in the appropriate sub-folder i.e. IE, DY, HE. This data should also be backed up in the ./backup/final data folder and a copy made on a CD on a weekly basis.
After data entry is completed, check that all batch files have been entered and are present in the /Final Data folder. There should be exactly101 data files in each subfolder that conform to the standard naming convention. If any files are missing or duplicated, resolve the issue by either re-entering the missing batch or deleting the duplicate data file.
Data Appraisal
Estimates of Sampling Error
The quality of data obtained through a household survey is subject to both sampling and nonsampling error. Both types of error can be assessed using statistical measures and the level of error reported in a data quality evaluation.
It should be noted that the analysis of the data contained in this report is based on a sample of households and therefore the estimates produced are subject to sampling error. It is anticipated that the relative standard error for the key estimates of total household income and expenditure will be less than five percent, which is the level at which the estimates are considered to reliable.
Standard errors for the key estimates will be calculated and included in the final report (provided as External Resource). A total of 1161 households out of 1546 selected fully responded to the survey, representing an overall response rate of 75 percent. Of the non-responding households, 8.2% refused to respond to questions, 5.3% were not able to be contacted, 9.1% were vacant dwellings, and 2.3% were out of scope for the survey. Lower responses rates (less than 70%) were obtained from Nonouti, North and South Tarawa than in the other surveyed islands. However, the response rate for each island group (apart from South Tarawa) was above the total response rate of 75%, indicating a very good level of response. Table 1.2 shows the number and percentage of responding households by island.
It should be noted that the analysis of the data contained in this report is based on a sample of households and therefore the estimates produced are subject to sampling error. It is anticipated that the relative standard error for the key estimates of total household income and expenditure will be less than five percent, which is the level at which the estimates are considered to reliable.
Standard errors for the key estimates will be calculated and included in the final report (provided as External Resource). A total of 1161 households out of 1546 selected fully responded to the survey, representing an overall response rate of 75 percent. Of the non-responding households, 8.2% refused to respond to questions, 5.3% were not able to be contacted, 9.1% were vacant dwellings, and 2.3% were out of scope for the survey. Lower responses rates (less than 70%) were obtained from Nonouti, North and South Tarawa than in the other surveyed islands. However, the response rate for each island group (apart from South Tarawa) was above the total response rate of 75%, indicating a very good level of response. Table 1.2 shows the number and percentage of responding households by island.
Data Appraisal
A data audit was completed - refer to the "Final Report - Kiribati 2006 HIES" in the External Resources.
Data access
Contact
| Name | Affiliation | URI | |
|---|---|---|---|
| Kiribati National Statistics Office | KNSO | [email protected] | www.spc.int/prism |
Confidentiality Declaration
The HIES data is protected under the National Statistics Act and cannot be disclosed to any individual without authorisation from the Government Statistician.
Conditions
Licensed datasets, accessible under conditions.
Citation requirement
"Kiribati National Statistics Office, Household Income and Expenditure Survey 2006 (HIES 2006), Version 01 of the licensed dataset (December 2008), provided by the Microdata Library. https://microdata.pacificdata.org/index.php/home"
Disclaimer and copyrights
Disclaimer
All publications need to be cleared by National Statistics Office (NSO) before publication as under the Statistics Act the NSO only has authority to publish national statistical data.
Copyright
c 2006 Kiribati National Statistics Office
Contacts
Contact
| Name | Affiliation | URI | |
|---|---|---|---|
| Government Statistician | Kiribati National Statistics Office | [email protected] | www.spc.int/prism |
Metadata production
Document ID
DDI_SPC_KIR_2006_HIES_v01_M_v01_A_PUF
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Statistics for Development Division | SDD | Pacific Community | Documentation of the study |
Date of Production
2008-12-02
Document version
Version 01 (December 2008): First attempt at documenting the Kiribati Household Income and Expenditure Survey of 2006.
Version 02 (July 2019): Review of existing documentation aiming at providing and documenting the datasets. Done by Statistics for Development Division in New Caledonia.
Version 02 (July 2019): Review of existing documentation aiming at providing and documenting the datasets. Done by Statistics for Development Division in New Caledonia.