Household Income and Expenditure Survey 2019, National Sustainable Development Plan Baseline Survey 2019
Vanuatu, 2019 - 2020
Under Development
Vanuatu National Statistics Office
Identification
IDNO
SPC_VUT_2019_HIES_v01_M
Title
Household Income and Expenditure Survey 2019, National Sustainable Development Plan Baseline Survey 2019
Subtitle
National Sustainable Development Plan Baseline Survey 2019
Translated Title
Sevei Blong Inkam Mo Expendija Blong Haoshol Long Vanuatu 2019
Country
| Name | Country code |
|---|---|
| Vanuatu | VUT |
Abstract
The National Sustainable Development Plan (NSDP) Baseline Survey 2019 is an expanded Household Income and Expenditure Survey (HIES) and is inclusive of health educational, cultural, and productive dimensions previously uncollected or in need of updating. The results of this survey will inform directly more than 30 key indicators listed in the NSDP M&E (Monitoring and Evaluation) Framework, as well as more than 40 of the listed indicators for the United Nations Sustainable Development Goals (SDGs). The NSDP Baseline Survey presents an opportunity as well for Vanuatu to establish a comprehensive Melanesian Wellbeing baseline as well as an updated baseline for the calculation of the Consumer Price Index (CPI) and revising National Accounts.
Kind of Data
Sample survey data [ssd]
Version
Version number
Version 01: Final clean, labelled and de-identified version of the Master file.
Version Date
2020-05-12
Version Notes
Version 03 of the raw dataset.
Scope
Keywords
| Keyword |
|---|
| Expenditure |
| Income |
| Household |
| Individual |
| CPI |
| Well-being |
| Satisfaction |
| Education |
| Economic activities |
| Health |
| Culture |
| COICOP |
| PACCOI |
| ISCO |
| ISIC |
| Water |
| Sanitation |
| Energy |
| Lighting |
| Agriculture |
| Fisheries |
| Handicraft |
Coverage
Geographic Coverage
National coverage. Below are the details of this national coverage:
1. National (Vanuatu);
2. Provinces (Torba, Sanma, Penama, Malampa, Shefa, Tafea);
4. Area Councils (Torres Area council right to Futuna & Aneityum Area Council);
5. Villages / Towns;
6. Urban/Rural.
1. National (Vanuatu);
2. Provinces (Torba, Sanma, Penama, Malampa, Shefa, Tafea);
4. Area Councils (Torres Area council right to Futuna & Aneityum Area Council);
5. Villages / Towns;
6. Urban/Rural.
Unit of Analysis
Household and Individual.
Universe
All de jure residents.
Producers and sponsors
Authoring entity/Primary investigators
| Agency Name | Affiliation |
|---|---|
| Vanuatu National Statistics Office | Ministry of Finance and Economic Management |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Statistics for Development Division | Pacific Community (SPC) | Technical Assistance in Planning, Questionnaire Design, Training, and Monitoring. |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Vanuatu Government | Funding | |
| Government of India | Funding | |
| United Nations Development Programme | UNDP | Funding |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Department of Strategic Policy, Planning and Aid Coordination | Government of Vanuatu | Questionnaire design consultation |
| World Bank | Questionnaire design consultation | |
| International Monetary Fund (IMF) | Questionnaire design consultation | |
| Food and Agriculture Organization (FAO) | Questionnaire design consultation | |
| International Labour Organization (ILO) | Questionnaire design consultation |
Sampling
Sampling Procedure
i) The only variable considered is per capita total household expenditure (variable of interest), as in addition to being one of the main indicators derived from the Household Income and Expenditure Survey (HIES), it is likely highly correlated with many other variables of interest (e.g. poverty). From the 2010 HIES dataset, using this variable of interest, a list of relevant indicators were calculated, those indicators provide information on:
- (a)the status of the household expenditure distribution within each province,
- (b) The efficiency provided by the 2010 HIES sample design
- (c) The accuracy of the estimates calculated from the 2010 HIES dataset (especially the per capita household expenditure, our variable or interest)
ii) The original dataset has been trimmed using the variable of interest, the lowest and the highest percentiles (the 1% households with the lowest and highest per capita total household expenditure) were removed from the analysis (outliers). The dataset ends up with 4,289 households (given 4,377 households were completed).
iii) The 2010 Vanuatu HIES sample was based on a stratified multi stages selection
- Stratification: geographical provinces (by urban / rural locations)
- First stage of selection: Enumerations Areas (EAs) with probability of selection proportional to size
- Second stage: households, with uniform probability of selection within the EAs
iv) The mean and standard deviation indicate the status of the variable of interest within each strata. The intracluster correlation (p), and the design effect (DEFF) highlight the efficiency of the sampling strategy, and the standard error/relative standard error (SE/RSE) of the variable of interest show its accuracy.
v) The purpose of this analysis is to get some insights from the 2010 HIES sample design in order to improve the 2019 survey. There is no point to improve the sample size in strata where the sample is not efficient (the gain in accuracy will be minor compared to the related cost).
vi) The challenge in the 2019 Vanuatu baseline survey:
- Meet precision targets in each strata (provincial level) including Penama where Ambae island has been evacuated at the time of the sample design.
- Acceptable sample size (due to budget constraints)
- Following international recommendations (12 months of field operation)
- Enhance the monitoring and supervision of the field staff and simplify management of the logistics in the field
==> Optimize the variance/cost ratio of the survey design
vii) Table 1 from the Document Sample Design (provided as External Resources) presents the Vanuatu 2010 HIES survey specifications, efficiency and accuracy in each strata (for the variable of interest). It shows that some improvements can be done in Torba, and Shefa rural (where the RSE is higher than 5%), and it shows a high intraclass correlation in Malampa, Shefa rural and Tafea (that lead to a high design effect in those stratas). In Torba, the high design effect comes from the high number of households interviewed in each selected EA (on average 33 households per selected EA in this strata were interviewed).
- Torba: the sample size is good, there is just a need to reduce the number of households to interview within each strata (and in order to keep a similar sample size the number of EAs to select in the province will be increased)
- Malampa: given the high intracluster correlation in this province, a higher number of EAs to select is required (with the same number of households per EA to interview).
- Shefa rural: keep the same number of households to interview within each EA, and increase the number of EA to select (this will lead to a higher sample size)
- Tafea: similar to Malampa province, the high intraclass correlation indicates that the number of EAs to select has to be increased (therefore the sample size as well).
The sample size has to be increased in Malampa, Shefa rural and Tafea, for the rest, the 2019 design will have to be similar as 2010 (in order to provide at least the same level of accuracy).
viii) The 2019 Vanuatu base line survey follows the international recommendations in terms of data collection schedule (12-month coverage) and considers a better management and supervision of the field staff. In this context, the field staff will work by team, given that:
- A team is made of 1 supervisor (team leader) and 2 or 3 interviewers
- Each interviewer will be responsible for 5 interview per round
- A round of survey is a 1 week period
- 1 EA is covered during 1 round, after the round completion, the team moves to the next EA for the next round.
- A team complete 32 rounds during the 12 month field operation period (roughly every 2 rounds/2 weeks) of work is followed by 1 round/1 week of rest).
ix) Table 3 from the Document Sample Design (provided as External Resources) presents a survey schedule starting February 2019 and ending February 2020. During this period of 32 working weeks (corresponding to 32 different selected EAs) the teams will be on the field (a 3 weeks period of rest during Christmas period).
x) The number of interviewer by team and number of team by province will determine the total sample size within each province. A team made of 3 interviewers can achieve 480 households over the period, while a team of 2 interviewers can achieve only 320 cases.
xi) The intraclass correlation is used to calculate the precision loss due to clustering. Like the standard deviation, the intracluster correlation is considered to be a true population parameter, and therefore transferable between designs. We have to accept the hypothesis that this correlation factor has not changed during the period 2010-2019, and therefore can be used to predict DEFF and RSE for the next survey given an adjusted design (based on the conclusions provided by the 2010 design). Table 2 from the Document Sample Design (provided as External Resources) predicts the design effect and sampling error of the variable of interest given the new sample design that is based on:
- the sample size within each strata
- the number of teams within each strata
- the number of interviewers per team
In order to allow more flexibility in the sample size, it is preferable to set up some teams of 3 interviewers, that can achieve 480 households, which represent a good sample size for Torba and Sanma urban and some teams of 2 interviewers that will achieve 320 households each (2 teams will be required in other provinces).
xii) The proposed design in Table 2 from the Document Sample Design (provided as External Resources) shows a total sample size of 4,640 households and a higher level of accuracy of the estimate of the variable of interest in all the stratas. Only Shefa rural shows a RSE higher than 5%, which will be still acceptable. The high intraclass correlation in Shefa rural impacts the variance of the estimates and lead to an increase the sample size or a decrease of the number of households to interview per EA which is logistically and financially not recommended.
- (a)the status of the household expenditure distribution within each province,
- (b) The efficiency provided by the 2010 HIES sample design
- (c) The accuracy of the estimates calculated from the 2010 HIES dataset (especially the per capita household expenditure, our variable or interest)
ii) The original dataset has been trimmed using the variable of interest, the lowest and the highest percentiles (the 1% households with the lowest and highest per capita total household expenditure) were removed from the analysis (outliers). The dataset ends up with 4,289 households (given 4,377 households were completed).
iii) The 2010 Vanuatu HIES sample was based on a stratified multi stages selection
- Stratification: geographical provinces (by urban / rural locations)
- First stage of selection: Enumerations Areas (EAs) with probability of selection proportional to size
- Second stage: households, with uniform probability of selection within the EAs
iv) The mean and standard deviation indicate the status of the variable of interest within each strata. The intracluster correlation (p), and the design effect (DEFF) highlight the efficiency of the sampling strategy, and the standard error/relative standard error (SE/RSE) of the variable of interest show its accuracy.
v) The purpose of this analysis is to get some insights from the 2010 HIES sample design in order to improve the 2019 survey. There is no point to improve the sample size in strata where the sample is not efficient (the gain in accuracy will be minor compared to the related cost).
vi) The challenge in the 2019 Vanuatu baseline survey:
- Meet precision targets in each strata (provincial level) including Penama where Ambae island has been evacuated at the time of the sample design.
- Acceptable sample size (due to budget constraints)
- Following international recommendations (12 months of field operation)
- Enhance the monitoring and supervision of the field staff and simplify management of the logistics in the field
==> Optimize the variance/cost ratio of the survey design
vii) Table 1 from the Document Sample Design (provided as External Resources) presents the Vanuatu 2010 HIES survey specifications, efficiency and accuracy in each strata (for the variable of interest). It shows that some improvements can be done in Torba, and Shefa rural (where the RSE is higher than 5%), and it shows a high intraclass correlation in Malampa, Shefa rural and Tafea (that lead to a high design effect in those stratas). In Torba, the high design effect comes from the high number of households interviewed in each selected EA (on average 33 households per selected EA in this strata were interviewed).
- Torba: the sample size is good, there is just a need to reduce the number of households to interview within each strata (and in order to keep a similar sample size the number of EAs to select in the province will be increased)
- Malampa: given the high intracluster correlation in this province, a higher number of EAs to select is required (with the same number of households per EA to interview).
- Shefa rural: keep the same number of households to interview within each EA, and increase the number of EA to select (this will lead to a higher sample size)
- Tafea: similar to Malampa province, the high intraclass correlation indicates that the number of EAs to select has to be increased (therefore the sample size as well).
The sample size has to be increased in Malampa, Shefa rural and Tafea, for the rest, the 2019 design will have to be similar as 2010 (in order to provide at least the same level of accuracy).
viii) The 2019 Vanuatu base line survey follows the international recommendations in terms of data collection schedule (12-month coverage) and considers a better management and supervision of the field staff. In this context, the field staff will work by team, given that:
- A team is made of 1 supervisor (team leader) and 2 or 3 interviewers
- Each interviewer will be responsible for 5 interview per round
- A round of survey is a 1 week period
- 1 EA is covered during 1 round, after the round completion, the team moves to the next EA for the next round.
- A team complete 32 rounds during the 12 month field operation period (roughly every 2 rounds/2 weeks) of work is followed by 1 round/1 week of rest).
ix) Table 3 from the Document Sample Design (provided as External Resources) presents a survey schedule starting February 2019 and ending February 2020. During this period of 32 working weeks (corresponding to 32 different selected EAs) the teams will be on the field (a 3 weeks period of rest during Christmas period).
x) The number of interviewer by team and number of team by province will determine the total sample size within each province. A team made of 3 interviewers can achieve 480 households over the period, while a team of 2 interviewers can achieve only 320 cases.
xi) The intraclass correlation is used to calculate the precision loss due to clustering. Like the standard deviation, the intracluster correlation is considered to be a true population parameter, and therefore transferable between designs. We have to accept the hypothesis that this correlation factor has not changed during the period 2010-2019, and therefore can be used to predict DEFF and RSE for the next survey given an adjusted design (based on the conclusions provided by the 2010 design). Table 2 from the Document Sample Design (provided as External Resources) predicts the design effect and sampling error of the variable of interest given the new sample design that is based on:
- the sample size within each strata
- the number of teams within each strata
- the number of interviewers per team
In order to allow more flexibility in the sample size, it is preferable to set up some teams of 3 interviewers, that can achieve 480 households, which represent a good sample size for Torba and Sanma urban and some teams of 2 interviewers that will achieve 320 households each (2 teams will be required in other provinces).
xii) The proposed design in Table 2 from the Document Sample Design (provided as External Resources) shows a total sample size of 4,640 households and a higher level of accuracy of the estimate of the variable of interest in all the stratas. Only Shefa rural shows a RSE higher than 5%, which will be still acceptable. The high intraclass correlation in Shefa rural impacts the variance of the estimates and lead to an increase the sample size or a decrease of the number of households to interview per EA which is logistically and financially not recommended.
Data Collection
Dates of Data Collection (YYYY/MM/DD)
| Start date | End date | Cycle |
|---|---|---|
| 2019-02-18 | 2020-02-17 | Data collection |
Mode of data collection
Computer Assisted Personal Interview [capi]
Supervision
A total of 19 interviewers and 13 supervisors were required for undertaking this survey.
Type of Research Instrument
The questionnaire was developed in English using the World Bank software Survey Solutions. This questionnaire is divided into 18 modules that are detailed below.
-Introduction (geographic areas, list of household members)
-Module 1: Demographic characteristics: ethnicity, marital status;
-Module 2: Wellbeing: culture and wellbeing, sports;
-Module 3: Education: language, traditional knowledge and skills, school attendance and attainment;
-Module 4: Health: illness, meals, functioning difficulties;
-Module 5: Individual expenses: communication, narcotics, other;
-Module 6: Labour force and individual income: activities, income, allowance, cash transfer amount;
-Module 7: Civic responsibility and satisfaction;
-Module 8: Household details: Dwelling characteristics, energy, water, transport;
-Module 9: Household assets: land, robbery, furniture, asset details;
-Module 10: Other household items and services: home maintenance and construction, vehicles, vehicle details, international private travel, domestic private travel, household services and taxes, financial support, other household expenditures;
-Module 11: Ceremonies;
-Module 12: Remittances;
-Module 13: Shocks;
-Module 14: Productive sector activity: livestock and aquaculture, fishing seafood collection and hunting, agriculture farming activities, handicraft;
-Module 15: Food recall;
-Module 16: Non-food recall;
-Module 17: Food away from home;
-Module 18: Food security.
-Introduction (geographic areas, list of household members)
-Module 1: Demographic characteristics: ethnicity, marital status;
-Module 2: Wellbeing: culture and wellbeing, sports;
-Module 3: Education: language, traditional knowledge and skills, school attendance and attainment;
-Module 4: Health: illness, meals, functioning difficulties;
-Module 5: Individual expenses: communication, narcotics, other;
-Module 6: Labour force and individual income: activities, income, allowance, cash transfer amount;
-Module 7: Civic responsibility and satisfaction;
-Module 8: Household details: Dwelling characteristics, energy, water, transport;
-Module 9: Household assets: land, robbery, furniture, asset details;
-Module 10: Other household items and services: home maintenance and construction, vehicles, vehicle details, international private travel, domestic private travel, household services and taxes, financial support, other household expenditures;
-Module 11: Ceremonies;
-Module 12: Remittances;
-Module 13: Shocks;
-Module 14: Productive sector activity: livestock and aquaculture, fishing seafood collection and hunting, agriculture farming activities, handicraft;
-Module 15: Food recall;
-Module 16: Non-food recall;
-Module 17: Food away from home;
-Module 18: Food security.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Vanuatu National Statistics Office | VNSO | Ministry of Finance and Economic Management |
Data Processing
Cleaning Operations
Data editing is done using the software Stata.
Other Processing
Data entry is done using the World Bank's software Survey Solutions.
Data access
Contact
| Name | Affiliation | URI |
|---|---|---|
| Vanuatu National Statistics Office | Ministry of Finance and Economic Management | https://vnso.gov.vu/index.php/contact-us |
Conditions
Licensed datasets, accessible under conditions.
Citation requirement
"Vanuatu National Statistics Office, Household Income and Expenditure Survey 2019-2020 (HIES 2019), Version 01 of the licensed dataset (May 2020), provided by the Microdata Library. https://microdata.pacificdata.org/index.php/home"
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Contacts
Contact
| Name | Affiliation | URI |
|---|---|---|
| Vanuatu National Statistics Office | Ministry of Finance and Economic Management | https://vnso.gov.vu/index.php/contact-us |
Metadata production
Document ID
DDI_SPC_VUT_2019_HIES_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Vanuatu National Statistics Office | VNSO | Documentation of the study | |
| Statistics for Development Division | SDD | Pacific Community (SPC) | Review of the documentation |
Date of Production
2019-05-20
Document version
-Version 01 (May 2019): This is the first attempt at documenting the 2019-2020 Household Income and Expenditure Survey (HIES) of Vanuatu. Done by Vanuatu National Statistics Office (VNSO).
-Version 02 (May 2020): This is the review of the existing documentation of Vanuatu's 2019-2020 Household Income and Expenditure Survey (HIES). Done by Statistics for Development Division from the Pacific Community (SPC) at Noumea, New Caledonia.
-Version 02 (May 2020): This is the review of the existing documentation of Vanuatu's 2019-2020 Household Income and Expenditure Survey (HIES). Done by Statistics for Development Division from the Pacific Community (SPC) at Noumea, New Caledonia.