Household Income and Expenditure Survey 2009
Tonga, 2009
Statistics Department of Tonga
Identification
IDNO
SPC_TON_2009_HIES_v01_M
Title
Household Income and Expenditure Survey 2009
Country
| Name | Country code |
|---|---|
| Tonga | TON |
Abstract
Tonga Household Income and Expenditure Survey 2009 (HIES), undertaken by the Tonga Statistics Department during the period from 1 January 2009 to 31 December 2009. This is the second survey of its kind in Tonga. The last one was carried out in 2000/01, and the results were used in November 2002 to rebase the Consumer Price Index (CPI). A report from that survey was produced in December 2002, and where possible, results from this report will be made to be comparable to the previous report.
• To provide updated information for the expenditure item weights for the CPI;
• To provide some data for the components of National Accounts; and
• To provide information on the nature and distribution of household income and expenditure for planners, policy makers, and the general public.
• To provide updated information for the expenditure item weights for the CPI;
• To provide some data for the components of National Accounts; and
• To provide information on the nature and distribution of household income and expenditure for planners, policy makers, and the general public.
Kind of Data
Sample survey data [ssd]
Version
Version number
Version 01: Cleaned, labelled and de-identified version of the Master file.
Version Date
2010
Scope
Keywords
| Keyword |
|---|
| Tonga |
| Household |
| Individual |
| Income |
| Expenditure |
| COICOP |
| PACCOI |
| HIES |
| Education |
| Health |
Coverage
Geographic Coverage
National Coverage and Island Division.
Unit of Analysis
Private Households, individuals, Income and expenditure items.
Universe
The survey covered all members of the household.
Producers and sponsors
Authoring entity/Primary investigators
| Agency Name | Affiliation |
|---|---|
| Statistics Department of Tonga | Government of Tonga |
Producers
| Name | Role |
|---|---|
| Secretariat of the Pacific Community | Technical assistance (questionaire design, sampling methodology and data processing) |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Asian Development Bank | ADB | Funding |
Sampling
Sampling Procedure
The sample design was done in such a way that promoted estimates primarily at the national level, but also at the island division level. For that reason a higher sample fraction was selected in the smaller island divisions.
Rural Tongatapu received the smallest sample fraction (8.3%) as it had the highest population. On the other hand the Ongo Niua received the largest sample fraction (21.5%) as their population was the smallest. Overall a sample of roughly 10 per cent was selected for Tonga.
The sample was selected independently within each of the 6 target areas. Firstly, extremely remote areas were removed from the frame (and thus not given a chance of selection) as it was considered too expensive to cover these areas. These areas only represented about 3.5 per cent of the total population for Tonga, so the impact of their removal was considered very minimal.
The sampling in each area was then undertaken using a two-stage process. The first stage involved the selection of census blocks using Probability Proportional to Size (PPS) sampling, where the size measure was the expected number of households in that block. For the second stage, a fixed number (twelve) of households were selected from each selected census block using systematic sampling. The household lists for all selected blocks were updated just prior to the second stage of selection.
Given the sample was spread out over four quarters during the 2009 calendar year, every 4th selected census block was allocated to a respective quarter. To ensure an equally distribution of sample to each quarter, the number of census blocks selected for each of the six target group was made divisible by four. This therefore meant the sample size for each target group was adjusted so that it was divisible by (4*12)=48, as can be seen in Table 1 of Section 1 of the survey report.
Rural Tongatapu received the smallest sample fraction (8.3%) as it had the highest population. On the other hand the Ongo Niua received the largest sample fraction (21.5%) as their population was the smallest. Overall a sample of roughly 10 per cent was selected for Tonga.
The sample was selected independently within each of the 6 target areas. Firstly, extremely remote areas were removed from the frame (and thus not given a chance of selection) as it was considered too expensive to cover these areas. These areas only represented about 3.5 per cent of the total population for Tonga, so the impact of their removal was considered very minimal.
The sampling in each area was then undertaken using a two-stage process. The first stage involved the selection of census blocks using Probability Proportional to Size (PPS) sampling, where the size measure was the expected number of households in that block. For the second stage, a fixed number (twelve) of households were selected from each selected census block using systematic sampling. The household lists for all selected blocks were updated just prior to the second stage of selection.
Given the sample was spread out over four quarters during the 2009 calendar year, every 4th selected census block was allocated to a respective quarter. To ensure an equally distribution of sample to each quarter, the number of census blocks selected for each of the six target group was made divisible by four. This therefore meant the sample size for each target group was adjusted so that it was divisible by (4*12)=48, as can be seen in Table 1 of Section 1 of the survey report.
Response Rate
The final Response Rates for the survey was high, which will assist in yielding statistically significant estimates. Across all six target groups the response rate was in excess of 95 per cent, with the exception of Ongo Niua who only reported 50 per cent. The reason the number was so low in the Ongo Niua was because this target area was only visited in the 2nd quarter, where half the total sample were enumerated (to make up for the sample loss in the first quarter), and was not visited again in quarter 3 and 4.
The reason behind the high response rates in other areas was due to the updated lists for selected census blocks excluding vacant dwellings. As such, it was mostly refusals that impacted on the final response rates.
The reason behind the high response rates in other areas was due to the updated lists for selected census blocks excluding vacant dwellings. As such, it was mostly refusals that impacted on the final response rates.
Data Collection
Dates of Data Collection (YYYY/MM/DD)
| Start date | End date | Cycle |
|---|---|---|
| 2009-02-16 | 2009-03-01 | Round 1 |
| 2009-05-04 | 2009-05-29 | Round 2 |
| 2009-08-03 | 2009-08-28 | Round 3 |
| 2009-11-02 | 2009-11-27 | Round 4 |
Mode of data collection
Face-to-face [f2f]
Supervision
The fieldwork was supported by 9 senior staff of the Statistics Department who acted as supervisors (including the two out-based staff who work in Vava’u).
The duties of supervisors include:
(i) Ensure that all schedules and materials are distributed to interviewers according to the instructions of the time specified by the HIES team.
(ii) Assist interviewers with the listing exercise of all private dwellings for their selected census block.
(iii) Assist interviewers with the systematic sampling of 12 private dwellings from their updated list.
(iv) Ensure that the interviewer understands which household he/she is responsible for and that none are left out.
(v) Visit interviewers on a regular basis during the whole process of fieldwork to make sure they are carrying out their responsibilities correctly and consistently
(vi) During the first week of the first round, accompany each interviewer to the household to give more confident to the interviewers.
(vii) Make sure all forms from their interviewers are accounted for at the end of each 2 week diary keeping period.
(viii) Check for completeness of all questionnaires and deal with any problems that might arise in the field.
(ix) Ensure the household envelope has been correctly filled in.
(x) Dispatch all completed questionnaires (in sealed envelopes) to the Statistics Office after he/she is fully satisfied that;
(a) All the entries of the questionnaires are properly completed.
(b) All the households in the sample selected and all members of the household are covered.
The duties of supervisors include:
(i) Ensure that all schedules and materials are distributed to interviewers according to the instructions of the time specified by the HIES team.
(ii) Assist interviewers with the listing exercise of all private dwellings for their selected census block.
(iii) Assist interviewers with the systematic sampling of 12 private dwellings from their updated list.
(iv) Ensure that the interviewer understands which household he/she is responsible for and that none are left out.
(v) Visit interviewers on a regular basis during the whole process of fieldwork to make sure they are carrying out their responsibilities correctly and consistently
(vi) During the first week of the first round, accompany each interviewer to the household to give more confident to the interviewers.
(vii) Make sure all forms from their interviewers are accounted for at the end of each 2 week diary keeping period.
(viii) Check for completeness of all questionnaires and deal with any problems that might arise in the field.
(ix) Ensure the household envelope has been correctly filled in.
(x) Dispatch all completed questionnaires (in sealed envelopes) to the Statistics Office after he/she is fully satisfied that;
(a) All the entries of the questionnaires are properly completed.
(b) All the households in the sample selected and all members of the household are covered.
Type of Research Instrument
There were 4 main survey schedules used to collect the information for the survey were published in English:
1) Household Questionnaire
2) Individual Questionnaire - Part 1
3) Individual Questionnaire - Part 2
4) Individual Diary (x2)
Household Questionnaire
This questionnaire is primarily used to collect information on large expenditure items, but also collects information about the dwelling characteristics. In total there are 14 sections to this uestionnaire which cover:
1 Dwelling Characteristics
2 Household Possessions
3 Dwelling Tenure
4 Construction of Dwellings
5 Household Bills
6 Transport Expenses
7 Major Consumer Durables
8 Education/Recreation
9 Medical & Health
10 Overseas Travel
11 Special Events
12 Subsistence Activity Sales
13 Remittances
14 Contributions to Church/Village/School
As stated above, the first section is devoted to collecting information about key dwelling characteristics, whereas the second section collects information on household possessions. Sections 3-11, and Section 14, focus on expenses the household incurs, whereas Section 13 focuses on remittances both paid by and received by the household. Finally, Section 12 collects information from households about the income they generate from subsistence activities. This section is the main question collecting income from the household questionnaire, as was included here as it was considered more appropriate to collect this data at the household level. The front page of this Questionnaire is also used for collecting the Roster of Household Members.
Individual Questionnaire - Part 1
This questionnaire collects basic demographic information about each individual in the household, including:
• Relationship to Household Head
• Sex
• Age
• Ethnicity
• Marital Status
Also collected in this form is information about health problems each individual may have encountered in the last 3 months, followed by education information. For the education section, if a person is currently attending an education institution, then current level is asked, whereas if the person attended an education institution but no longer attends, then the highest level completed is collected. The last main section of this form collects information about labour force and is only asked of individuals aged 10 years and above. These questions aim to classify each person in scope for this section as either:
• In the Labour Force - Employed
• In the Labour Force - Unemployed
• Not in the Labour Force
Individual Questionnaire - Part 2
This questionnaire is focused on collecting information from individuals regarding their income. There are eight sections to this questionnaire of which six are devoted to income. They include:
1 Wages and Salary
2 Self-Employment
3 Previous Jobs
4 Ad-hoc Jobs
5 Pensions/Welfare Benefits
6 Other Income
7 Loan Information
8 Contributions to Benefit Schemes
As stated above, the first six sections of this questionnaire focus on income. Section 7 collects information pertaining to loans for i) households, ii) cars, iii) special events and iv) other, and finally the last question is an expense related question covering contributions to benefit schemes which was considered best covered at an individual level.
Individual Diary
The last form used for the survey was the Individual Diary which each individual aged 10 years and over was required to fill in for two weeks (two one-week diaries).
Each diary had 4 sections covering the following:
1) Items Purchased: This section had a separate page for each day and was for recording all items bought in a store, street vendors, market or any other place (including credit)
2) Home Grown/Produced Items: This section was for recording home grown/produced items consisting of items such as food grown at home or at the family plantation, self caught or gathered fish and homemade handicrafts and other goods grown and produced at home. Information is recorded for these items consumed by the household which they produced themselves, these items they
gave away as a gift, and these items they received as a gift.
3) Gifts Given and Received: This section of the diary is for recording gifts given and received including both cash and purchased goods (but not home produced). If any member of the household receives a gift that meets this criteria during the diary keeping period from someone who is not a member of their household it is recorded here.
4) Winnings from Gambling: The last section of the Diary is for recording all winnings from gambling during the diary keeping period.
1) Household Questionnaire
2) Individual Questionnaire - Part 1
3) Individual Questionnaire - Part 2
4) Individual Diary (x2)
Household Questionnaire
This questionnaire is primarily used to collect information on large expenditure items, but also collects information about the dwelling characteristics. In total there are 14 sections to this uestionnaire which cover:
1 Dwelling Characteristics
2 Household Possessions
3 Dwelling Tenure
4 Construction of Dwellings
5 Household Bills
6 Transport Expenses
7 Major Consumer Durables
8 Education/Recreation
9 Medical & Health
10 Overseas Travel
11 Special Events
12 Subsistence Activity Sales
13 Remittances
14 Contributions to Church/Village/School
As stated above, the first section is devoted to collecting information about key dwelling characteristics, whereas the second section collects information on household possessions. Sections 3-11, and Section 14, focus on expenses the household incurs, whereas Section 13 focuses on remittances both paid by and received by the household. Finally, Section 12 collects information from households about the income they generate from subsistence activities. This section is the main question collecting income from the household questionnaire, as was included here as it was considered more appropriate to collect this data at the household level. The front page of this Questionnaire is also used for collecting the Roster of Household Members.
Individual Questionnaire - Part 1
This questionnaire collects basic demographic information about each individual in the household, including:
• Relationship to Household Head
• Sex
• Age
• Ethnicity
• Marital Status
Also collected in this form is information about health problems each individual may have encountered in the last 3 months, followed by education information. For the education section, if a person is currently attending an education institution, then current level is asked, whereas if the person attended an education institution but no longer attends, then the highest level completed is collected. The last main section of this form collects information about labour force and is only asked of individuals aged 10 years and above. These questions aim to classify each person in scope for this section as either:
• In the Labour Force - Employed
• In the Labour Force - Unemployed
• Not in the Labour Force
Individual Questionnaire - Part 2
This questionnaire is focused on collecting information from individuals regarding their income. There are eight sections to this questionnaire of which six are devoted to income. They include:
1 Wages and Salary
2 Self-Employment
3 Previous Jobs
4 Ad-hoc Jobs
5 Pensions/Welfare Benefits
6 Other Income
7 Loan Information
8 Contributions to Benefit Schemes
As stated above, the first six sections of this questionnaire focus on income. Section 7 collects information pertaining to loans for i) households, ii) cars, iii) special events and iv) other, and finally the last question is an expense related question covering contributions to benefit schemes which was considered best covered at an individual level.
Individual Diary
The last form used for the survey was the Individual Diary which each individual aged 10 years and over was required to fill in for two weeks (two one-week diaries).
Each diary had 4 sections covering the following:
1) Items Purchased: This section had a separate page for each day and was for recording all items bought in a store, street vendors, market or any other place (including credit)
2) Home Grown/Produced Items: This section was for recording home grown/produced items consisting of items such as food grown at home or at the family plantation, self caught or gathered fish and homemade handicrafts and other goods grown and produced at home. Information is recorded for these items consumed by the household which they produced themselves, these items they
gave away as a gift, and these items they received as a gift.
3) Gifts Given and Received: This section of the diary is for recording gifts given and received including both cash and purchased goods (but not home produced). If any member of the household receives a gift that meets this criteria during the diary keeping period from someone who is not a member of their household it is recorded here.
4) Winnings from Gambling: The last section of the Diary is for recording all winnings from gambling during the diary keeping period.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Specially recruited staff | SDT | Statistics Department Tonga |
Data Processing
Cleaning Operations
Batch edits in CSPro were performed on the data after data entry was completed. The batch edits were aimed at identifying any values falling outside acceptable ranges, as well as other inconsistencies in the data. As this process was done at the batch level, questionnaires were often referred to and manual changes to the data were performed to amend identified errors.
One significant problem which was identified during this process was the incorrect coding of phone card purchase to the purchase of actual phones. As there were many such cases, an automatic code change was applied to any purchase of phones which was less than $40 - recoding them to purchase of phone cards.
One significant problem which was identified during this process was the incorrect coding of phone card purchase to the purchase of actual phones. As there were many such cases, an automatic code change was applied to any purchase of phones which was less than $40 - recoding them to purchase of phone cards.
Other Processing
All data entry, including editing, edit checks and queries, was done using CSPro (Census Survey Processing System) - the technical assistance was provided by the Secretariat of the Pacific Community (SPC). Preparation of the data for final tables was also done using this software, although tables were produced in excel.
Prior to this, all data coding of questionnaires was carried out by staff from the Statistics Department, ideally at the completion of each round. The data entry then took place, once again by staff from the Statistics Department, straight after completion of the coding. All data was double entered to minimize errors at this stage of the survey. Unfortunately due to other work commitments by the staff involved, the process of coding and entering the data was delayed for the first few rounds, causing some concerns with overall delays. To address this, the Statistics Department employed three additional staff to assist with the coding of questionnaires.
The coding and data entry was all completed by around mid March, 2010.
Prior to this, all data coding of questionnaires was carried out by staff from the Statistics Department, ideally at the completion of each round. The data entry then took place, once again by staff from the Statistics Department, straight after completion of the coding. All data was double entered to minimize errors at this stage of the survey. Unfortunately due to other work commitments by the staff involved, the process of coding and entering the data was delayed for the first few rounds, causing some concerns with overall delays. To address this, the Statistics Department employed three additional staff to assist with the coding of questionnaires.
The coding and data entry was all completed by around mid March, 2010.
Data Appraisal
Estimates of Sampling Error
Sampling errors refer to those errors that are implicit in any sample survey, where only a portion of the population is covered. Non-sampling errors refer to all other types of error. These can arise at any stage of the survey process. Examples of activities that are likely to increase the level of non-sampling error are: failing to select a proper sample, poor questionnaire design, weak field supervision, inaccurate data entry, insufficient data editing, or failure to analyze or report on the data correctly. If a census of all the households in Tonga were carried out, there would be no sampling error (but probably increased non-sampling error).
Because of the complex nature of the sample design, it was considered more appropriate to calculate approximate standard errors - these were calculated using the jack-knife variance estimation procedure. It was not possible to calculate sampling errors for all estimates in this report, so just some sample errors for key estimates of expenditure and income were produced for selected geographical areas. This in itself should give users a guide as to what can be expected from results with respect to sampling errors.
The procedure for addressing this was to firstly calculate the variance associate with key estimates, convert these to standard errors, and then represent these standard errors as a percentage of the estimate. Such a figure is referred to as a relative standard error (RSE) as is useful for comparing the quality of different size estimates from a survey.
Please refer to Section 4.2 of the HIES 2009 Report for the estimates of RSE's.
The RSEs for Total Consumption Expenditure for Tonga was 3.3 per cent, suggesting it is a very reliable figure from a sample error perspective. The corresponding RSE for urban and rural estimate of Total Consumption Expenditure is also quite low at 5.4 per cent and 4.1 per cent respectively. The RSEs for individual expenditure groups within Consumption Expenditure are a little higher, especially within the island divisions, and as such should be used with care.
For the estimates of Non-Consumption Expenditure, the RSEs are a little higher, but not too many exceed the point where the estimates are not considered usable.
The RSEs for Total Household Income for Tonga was 5.0 per cent, suggesting once again it is a very reliable figure from a sample error perspective. The corresponding RSE for urban and rural estimate of Total Household Income went up a little higher, but still remain good quality estimates. Their corresponding RSEs were at 8.2 per cent and 6.3 per cent respectively. The table also shows that the RSEs for individual income groups within Household Income differed quite significantly depending on the income category. Estimates of “business income”, “property income” and “welfare,npf & child support” showed to be a lot more unreliable, due to the variation of responses between households for this type of income. The RSEs for the income groups “home produce consumed” and “wage and salary – current job“ proved to be a lot more reliable.
The RSEs for the section on Irregular Gifts Received, were a little higher, but not to the point where the information was not considered usable.
Because of the complex nature of the sample design, it was considered more appropriate to calculate approximate standard errors - these were calculated using the jack-knife variance estimation procedure. It was not possible to calculate sampling errors for all estimates in this report, so just some sample errors for key estimates of expenditure and income were produced for selected geographical areas. This in itself should give users a guide as to what can be expected from results with respect to sampling errors.
The procedure for addressing this was to firstly calculate the variance associate with key estimates, convert these to standard errors, and then represent these standard errors as a percentage of the estimate. Such a figure is referred to as a relative standard error (RSE) as is useful for comparing the quality of different size estimates from a survey.
Please refer to Section 4.2 of the HIES 2009 Report for the estimates of RSE's.
The RSEs for Total Consumption Expenditure for Tonga was 3.3 per cent, suggesting it is a very reliable figure from a sample error perspective. The corresponding RSE for urban and rural estimate of Total Consumption Expenditure is also quite low at 5.4 per cent and 4.1 per cent respectively. The RSEs for individual expenditure groups within Consumption Expenditure are a little higher, especially within the island divisions, and as such should be used with care.
For the estimates of Non-Consumption Expenditure, the RSEs are a little higher, but not too many exceed the point where the estimates are not considered usable.
The RSEs for Total Household Income for Tonga was 5.0 per cent, suggesting once again it is a very reliable figure from a sample error perspective. The corresponding RSE for urban and rural estimate of Total Household Income went up a little higher, but still remain good quality estimates. Their corresponding RSEs were at 8.2 per cent and 6.3 per cent respectively. The table also shows that the RSEs for individual income groups within Household Income differed quite significantly depending on the income category. Estimates of “business income”, “property income” and “welfare,npf & child support” showed to be a lot more unreliable, due to the variation of responses between households for this type of income. The RSEs for the income groups “home produce consumed” and “wage and salary – current job“ proved to be a lot more reliable.
The RSEs for the section on Irregular Gifts Received, were a little higher, but not to the point where the information was not considered usable.
Data Appraisal
Non-sampling errors refer to all other errors which can take place during the course of the survey, which impact on the accuracy of survey results. Unlike the sampling error, it is very difficult to measure the magnitude of the non-sampling error, and as such, users are often left with information on the types of errors which can go wrong and the likelihood of such errors occurring within the survey, and to what extent. A brief explanation below provides this information for each of the key types of non-sampling error identified in the Tonga 2009 HIES.
Selection Bias
The sampling procedure adopted for the survey in all island divisions was a commonly used two-stage approach which involved the selection of census blocks for the first stage and a fixed number of households at the second stage. Where some selection bias was expected to be introduced, was through the removal of remote areas from the sample frame due to the high costs and difficulties of covering these areas. These areas only represented about 3.5 per cent of the total population for Tonga, so the impact of their removal was considered very minimal.
Non-response Bias
Non-response Bias is the bias generated in estimates as a result of selected households not responding to the survey for a variety of reasons. Without knowing information about the non- responding households, it is difficult to determine the extent of the bias generated by non- response. What can be said however, is that the higher the response rates, the lower the bias.
The response rates for this survey were very high for all island divisions, with the exception of Ongo Niua. For Ongo Niua, the plan was to visit each of the two islands twice, enumerating 24 households on each visit, to each island. Due to transport issues, only one of the islands was visited, and 48 households were enumerated on that visit, impacting on the quality of the representation achieved for this island. Due to the small population of Ongo Niua, this problem was not expected to cause significant problems at the national level.
Selection Bias
The sampling procedure adopted for the survey in all island divisions was a commonly used two-stage approach which involved the selection of census blocks for the first stage and a fixed number of households at the second stage. Where some selection bias was expected to be introduced, was through the removal of remote areas from the sample frame due to the high costs and difficulties of covering these areas. These areas only represented about 3.5 per cent of the total population for Tonga, so the impact of their removal was considered very minimal.
Non-response Bias
Non-response Bias is the bias generated in estimates as a result of selected households not responding to the survey for a variety of reasons. Without knowing information about the non- responding households, it is difficult to determine the extent of the bias generated by non- response. What can be said however, is that the higher the response rates, the lower the bias.
The response rates for this survey were very high for all island divisions, with the exception of Ongo Niua. For Ongo Niua, the plan was to visit each of the two islands twice, enumerating 24 households on each visit, to each island. Due to transport issues, only one of the islands was visited, and 48 households were enumerated on that visit, impacting on the quality of the representation achieved for this island. Due to the small population of Ongo Niua, this problem was not expected to cause significant problems at the national level.
Data access
Contact
| Name | Affiliation | URI | |
|---|---|---|---|
| Government Statistician | Tonga Department of Statistics | [email protected] | http//www.stats.gov.to |
Confidentiality Declaration
All data supplied in the Tonga Household Income and Expenditure Survey remains strictly confidential in accordance with the Tonga Statistics Act, 1978. All information will be used solely for statistica purposes ONLY.
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by Tonga Statistics Department.
2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files.
3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of Tonga Statistics Department.
Conditions
Licensed datasets, accessible under conditions.
Citation requirement
"Tonga Statistics Department, Household Income and Expenditure Survey 2009 (HIES 2009), Version 01 of the licensed datasets (April 2001), provided by the Pacific Data Library. http://pdl.spc.int/index.php/home"
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the Statistics Department Tonga and the Secretariat of the Pacific Community bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Copyright
(c) 2010, Statistics Department Tonga & SPC
Contacts
Contact
| Name | Affiliation | URI | |
|---|---|---|---|
| Tonga Statistics Department | Government of Tonga | [email protected] | https://tongastats.gov.to/about-us/contact-us/ |
Metadata production
Document ID
DDI_SPC_TON_2009_HIES_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Winston Fainga'anuku | WF | Tonga Statistics Department | Documentation of the study |
| Statistics for Development Division | SDD | Pacific Community | Review of the existing documentation |
Date of Production
2012-07-02
Document version
Version 01 (July 2012): This is the first attempt at documenting the 2009 Tonga Household Income and Expenditure Survey. Done at Tonga by the Tonga Statistics Department.
Version 02 (April 2019): Review of the existing documentation. Done by Statistics for Development Division in Noumea, New Caledonia.
Version 02 (April 2019): Review of the existing documentation. Done by Statistics for Development Division in Noumea, New Caledonia.