Agriculture Census 2006-2008
Vanuatu, 2006 - 2008
Vanuatu National Statistics Office
Identification
IDNO
SPC_VUT_2006_AGC_v01_M
Title
Agriculture Census 2006-2008
Translated Title
Vanuatu Akrikalja Senses 2006
Country
| Name | Country code |
|---|---|
| Vanuatu | VUT |
Abstract
The Agriculture Census 2007 was the third undertaken in Vanuatu for the purpose of compiling information on agriculture, forestry and fisheries resources. Data collected will be used to formulate plans, policies and programs for the development and improvement of these sectors. This census was conducted by the Vanuatu National Statistics Office (VNSO), a centralized organization mainly responsible for the collection and dissemination of important statistics in the country by means of censuses of population, agriculture, household income and expenditure surveys, business surveys, collection of imports and exports data, etc. However, owing to limited resources, the VNSO cannot accommodate requests for extra data needed by other government and private sectors: hence, these data may have to be collected independently.
Agricultural statistics in Vanuatu are produced in two ways: through census/ survey and through administrative records. The census/survey provides baseline or benchmark information for planners and policymakers while the data from administrative records are used to keep track of changes and development in specific aspects of agriculture.
Agricultural statistics in Vanuatu are produced in two ways: through census/ survey and through administrative records. The census/survey provides baseline or benchmark information for planners and policymakers while the data from administrative records are used to keep track of changes and development in specific aspects of agriculture.
Kind of Data
Census/enumeration data [cen]
Version
Version number
Version 01: Cleaned, labelled and de-identified version of the Master file.
Version Date
2008-09-30
Scope
Topic Classification
| Topic | Vocabulary | URI |
|---|---|---|
| housing [10.1] | CESSDA | http://www.nesstar.org/rdf/common |
| censuses [14.1] | CESSDA | http://www.nesstar.org/rdf/common |
| plant and animal distribution [9.4] | CESSDA | http://www.nesstar.org/rdf/common |
| agricultural, forestry and rural industry [2.1] | CESSDA | http://www.nesstar.org/rdf/common |
Keywords
| Keyword |
|---|
| Agriculture Census |
| Agriculture |
| Livestock |
| Poultry |
| Fishing |
| Forestry |
| Crop |
| Garden |
| Trees |
Coverage
Geographic Coverage
National coverage.
The Agriculture Census (Phase I and II) was undertaken in eighteen main islands of Vanuatu which are: namely, Banks. Torres, Malo, Santo, Ambae, Maewo, Pentecost, Malekula, Ambrym, Paama, Epi, Shepherds, Efate, Erromango, Tanna, Aneityum, Aniwa and Futuna.
The Agriculture Census (Phase I and II) was undertaken in eighteen main islands of Vanuatu which are: namely, Banks. Torres, Malo, Santo, Ambae, Maewo, Pentecost, Malekula, Ambrym, Paama, Epi, Shepherds, Efate, Erromango, Tanna, Aneityum, Aniwa and Futuna.
Unit of Analysis
Households and individuals about their agricultural involvements.
Universe
The Survey covers all rural households
· Crop gardening
· Kava sub-holding
· Coconut sub-holding
· Cocoa sub-holding
· Coffee sub-holding
· Vanilla sub-holding
· Pepper sub-holding
· Cattle sub-holding
· Other livestock keeping
· Household fishing
· Household forestry-related activity.
· Crop gardening
· Kava sub-holding
· Coconut sub-holding
· Cocoa sub-holding
· Coffee sub-holding
· Vanilla sub-holding
· Pepper sub-holding
· Cattle sub-holding
· Other livestock keeping
· Household fishing
· Household forestry-related activity.
Producers and sponsors
Authoring entity/Primary investigators
| Agency Name | Affiliation |
|---|---|
| Vanuatu National Statistics Office | Vanuatu Government |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Statistics and Demography Program | South Pacific Community | Technical Assistance |
| Food Agriculture Organisation | United Nations | Technical Assistance |
| Nirmana Pty Ltd | Private Consulation Agency | Data Analysis & Report Writing |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| New Zealand Aid Agency | NZAid | Principal Funder |
| European Union | EU | Funder |
| Australian Aid Agency | AusAID | Funder |
| Food and Agriculture Organisation | FAO | Funder |
| Vanuatu Government | VANGOV | Funder |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Mr. Pioni Willie | Vanuatu National Statistics Office | National Project Coordinator |
| Mrs. Alice Sami | Vanuatu National Statistics Office | Deputy National Project Coordinator |
| Mrs. Aspinol Amos | Vanuatu National Statistics Office | Administration & FinanceOfficer |
Sampling
Sampling Procedure
Sampling method
The 18 major islands were classified as:
• small - number of households engaged in agricultural activities less than 500 (Torres, Paama, Erromango, Aniwa, Aneityum and Futuna);
• medium - number of households engaged in agricultural activities 500-1,999 (Banks, Malo, Maewo, Ambrym, Epi and Shepherds); and
• large - number of households operating agricultural activities 2,000 or more (Efate, Malekula, Ambae, Pentecost and Tanna).
In determining the number of households to be interviewed in each island and in each enumeration area (EA):
-for small islands, all households were listed and the identified households engaged in agricultural activities were enumerated;
-for medium-sized islands, one-third of the sample EAs in these islands were selected and all households were listed and those found to be engaged in agricultural activities were interviewed; and
-for large islands, one-third of the total EAs were selected in each island and all households listed. Of households found to have a crop garden, coconut sub-holding or kava sub-holding, one-third were selected to be further interviewed. In addition, all households listed and involved in the subholding of cattle and cash crops like cocoa, coffee (for Tanna only), vanilla and pepper (10 or more plants) were also enumerated.
The 18 major islands were classified as:
• small - number of households engaged in agricultural activities less than 500 (Torres, Paama, Erromango, Aniwa, Aneityum and Futuna);
• medium - number of households engaged in agricultural activities 500-1,999 (Banks, Malo, Maewo, Ambrym, Epi and Shepherds); and
• large - number of households operating agricultural activities 2,000 or more (Efate, Malekula, Ambae, Pentecost and Tanna).
In determining the number of households to be interviewed in each island and in each enumeration area (EA):
-for small islands, all households were listed and the identified households engaged in agricultural activities were enumerated;
-for medium-sized islands, one-third of the sample EAs in these islands were selected and all households were listed and those found to be engaged in agricultural activities were interviewed; and
-for large islands, one-third of the total EAs were selected in each island and all households listed. Of households found to have a crop garden, coconut sub-holding or kava sub-holding, one-third were selected to be further interviewed. In addition, all households listed and involved in the subholding of cattle and cash crops like cocoa, coffee (for Tanna only), vanilla and pepper (10 or more plants) were also enumerated.
Response Rate
100%.
Weighting
5.1 Estimation Procedure (General Underlying Estimation Concepts)
For any survey, estimates for total of a variable is computed using the general equation:
^ n
X = ?wixi ,where w is the weight of each ultimate sampling unit, x is the
I=1 observation, and n is the number of samples.
The general equation used to compute the total of any variable x in the 2007 Census of Agriculture is given below:
^ n m n
X = ?? (N/n)[Hproj/(?(N/n)Mi)](Mi'/mi')(mi'/mi)xij eq. (1)
I=1 j=1 i=1
Where:
^
X - the estimated total for variable x
N - total number of EAs in the stratum, i.e., group of islands
n - number of sample EAs in the stratum
Mi - total number of households in EA i from 2006 listing of households (frame)
Mi' - total number of households engaged in agriculture in EA i
mi' - total number of households listed in listing form (with 10 or more trees,
etc.) in EA i.
mi - total number of sample households in EA i.
Hproj - projected number of households in the stratum (see section for the
estimation of projected households)
The weight of each household or questionnaire in sample EA i is:
wi = (N/ni)[Hproj/(?(N/ni)Mi)](Mi'/mi')(mi'/mi) eq. (2)
5.2 Derivation of the Weights used in this Survey
Since the enumeration procedure is to list all households in each target EA - target EA means all EAs in small island group, 1/3 of all EAs in medium and large island groups, the weight should be:
wi = (N/n)(Mi/mi)[Hproj/(?(N/n)(Mi/mi)Mi)] eq. (3)
Where N/n is the inverse of the probability that the EA would be selected and M/m is the inverse of the probability that the household would be selected. But since Mi = mi, then these two numbers cancel each other out hence the equation can be written as:
wi = (N/n)[Hproj/(?(N/n)Mi)] eq. (4)
The equation term Hproj/(?(N/n)Mi is the adjustment factor due to non-coverage or adjustment to the projected number of households in the stratum. This factor can be excluded if the variability in the size of all EAs is low, but for the sampling design employed in this survey, the factor cannot be removed because the resulting estimate of the number of households without the adjustment factor is much less compared to the 2006 census of agriculture. This is due to high variability in the size of sample EAs in each stratum.
For Small Island Group, all EAs were enumerated, i.e., N = n, hence the equation could be reduced to just the adjustment factor.
wi = Hproj/(?Mi) è Hproj / M, where M is the total number of households in
the Stratum.
This adjustment factor should no longer be needed for this stratum had the listing and enumeration been done correctly. Even though the instruction is to list all households, i.e., each household must have Form 1 or listing form, the actual procedure done was that, only those households engaged in agriculture with 10 or more trees and/or with cattle were listed. Hence, there is no way that the total number of households could be known in this stratum. This is the reason for including the adjustment factor in the weight of the households in this stratum. Another adjustment factor is added in the weight due to reason that will be discussed in the succeeding paragraph, i.e., weights of Medium Island Group. The actual weight used for small island group is:
wi = (Hproj / M) (Mi'/mi')
Note that this is just a special case of equation (2) where N = n, and mi' = mi.
In case of Medium Island Group where all households in sample EAs were supposedly listed, the weight should be the same as equation (4) had all households in the EA have their respective questionnaire. Unfortunately, after analyzing the frequency distribution of households by sample EAs, the numbers were found to be much less than the counts of household in the 2006 Census of Agriculture or the 2006 Listing of Households. The reason is that only those households with 10 trees or more and, etc. were enumerated. When equation (4) was applied to generate the total number of households, the result gives only approximately 60% of the projected number of households. The reason is that the resulting count is the number of households with 10 trees or more and, etc. and not the total number of households in the stratum. These figures would definitely be very difficult to explain to data users - considering that this is supposed to be a census of all households and not a census of those with 10 trees or more … To solve the problem, another adjustment factor is included in the weight, that is, M'/m' where M' is the total number of households engaged in agriculture from the 2006 listing of households and m' is the number of households with 10 trees or more and etc. In layman terms, the total number of households found to be engaged in agriculture in 2006 listing of households in the EA is distributed proportionately to each questionnaire in the file. The effect of this technique is higher estimates since those households engaged with less than 10 trees, etc. (that is, households excluded in the frame) have been included in the estimation. The weight used for medium island group is:
wi = (N/n)[Hproj/(?(N/n)Mi)] (Mi'/mi') eq. (5)
Note that this is a special case of equation (2) where mi' = mi.
Estimation procedure for Large Island Group used weight similar to the above equation but another factor is included. The adjustment factor is mi' / m, where m is the number of sample households. Since mi' will cancel out, the simplified equation is given below:
wi = (N/n)[Hproj/(?(N/n)Mi)] (Mi'/mi) eq. (6)
The weight derived using the above equation (equation 6) is attached to all sample households only while weight derived using equation (5) is attached to all questionnaires (set of forms or cases) in the file. As mentioned above, sample households are those questionnaires with household form, i.e., all questionnaires in small and medium island groups and sample household questionnaires in large island group. The data item name of sample household weight is SWEIGHT, while all forms weight is DWEIGHT. Hence DWEIGHT is computed using equation (5) while equation (6) is used to compute SWEIGHT.
5.3 Using the Weights
As described above, SWEIGHT should be applied to all households (questionnaires) with household forms. In addition, this should be applied when generating totals for Kava and Coconut sub-holdings characteristics.
On the other hand, DWEIGHT should be used when tabulating Cocoa, Vanilla, Pepper, and Cattle sub-holdings characteristics.
Note that when cross tabulation is to be done for variables from these two different weighting groups (mixed), the sample weight SWEIGHT should be used.
5.4 Computation of the projected number of households
As described in the previous section, the number of households as of the first day of the enumeration (1st day of August, 2007) is needed in the weighting procedure. The practice in other countries is that official population projection is used, but since Vanuatu does not have this projection, and since required data are not available to be able to generate the population projection using internationally accepted procedure, an estimate was generated. The procedure for the estimation of the number of households is enumerated below.
1. Projected total population in the country for August, 2007 was computed using the growth rate between the last census of population conducted in November, 1999 and the listing of households which was conducted in May, 2006. The growth rate is 2.63 percent.
2. The total population counts for Urban and Rural areas were estimated using ratio and proportion, which resulted to 52,366 and 176,458 respectively. The main rationale for these prorated estimates is that it is more accurate to use the growth rate for the total population compared to estimates based on individual (i.e., provincial) growth rates.
3. Using the same rationale above, these estimates were distributed to their respective provincial areas using ratio and proportion.
4. The number of households in each province (urban/rural) was computed by dividing the population estimate with the average household size. The household size used is the one generated from the census of agriculture where the weights used is the basic weight, i.e., N/n*M/m. The rationale for using the average household size from the survey is that, when compared to the household size from the 1996 listing of households, it was found out that the figures are very different. If the average household size from 1996 listing of households would be used, the result to the weighted (final) population count would be unpredictable. Other reasons are: a) the sample is large enough to provide statistically accurate means and percentages, b) the definition of household membership used in the 1996 listing of households is not the same as in the 2007 census.
5. These numbers of households in all provinces (Urban / Rural) were added to come up with the final estimates for the total number of households in urban and rural areas in Vanuatu.
6. The final estimate for the number of households in each province was computed by prorating the final estimate for Vanuatu into all provinces using ratio and proportion.
7. In the same manner, the projected number of households in each stratum, i.e., small-island, medium-island, and large-island groups, was computed using ratio and proportion.
For any survey, estimates for total of a variable is computed using the general equation:
^ n
X = ?wixi ,where w is the weight of each ultimate sampling unit, x is the
I=1 observation, and n is the number of samples.
The general equation used to compute the total of any variable x in the 2007 Census of Agriculture is given below:
^ n m n
X = ?? (N/n)[Hproj/(?(N/n)Mi)](Mi'/mi')(mi'/mi)xij eq. (1)
I=1 j=1 i=1
Where:
^
X - the estimated total for variable x
N - total number of EAs in the stratum, i.e., group of islands
n - number of sample EAs in the stratum
Mi - total number of households in EA i from 2006 listing of households (frame)
Mi' - total number of households engaged in agriculture in EA i
mi' - total number of households listed in listing form (with 10 or more trees,
etc.) in EA i.
mi - total number of sample households in EA i.
Hproj - projected number of households in the stratum (see section for the
estimation of projected households)
The weight of each household or questionnaire in sample EA i is:
wi = (N/ni)[Hproj/(?(N/ni)Mi)](Mi'/mi')(mi'/mi) eq. (2)
5.2 Derivation of the Weights used in this Survey
Since the enumeration procedure is to list all households in each target EA - target EA means all EAs in small island group, 1/3 of all EAs in medium and large island groups, the weight should be:
wi = (N/n)(Mi/mi)[Hproj/(?(N/n)(Mi/mi)Mi)] eq. (3)
Where N/n is the inverse of the probability that the EA would be selected and M/m is the inverse of the probability that the household would be selected. But since Mi = mi, then these two numbers cancel each other out hence the equation can be written as:
wi = (N/n)[Hproj/(?(N/n)Mi)] eq. (4)
The equation term Hproj/(?(N/n)Mi is the adjustment factor due to non-coverage or adjustment to the projected number of households in the stratum. This factor can be excluded if the variability in the size of all EAs is low, but for the sampling design employed in this survey, the factor cannot be removed because the resulting estimate of the number of households without the adjustment factor is much less compared to the 2006 census of agriculture. This is due to high variability in the size of sample EAs in each stratum.
For Small Island Group, all EAs were enumerated, i.e., N = n, hence the equation could be reduced to just the adjustment factor.
wi = Hproj/(?Mi) è Hproj / M, where M is the total number of households in
the Stratum.
This adjustment factor should no longer be needed for this stratum had the listing and enumeration been done correctly. Even though the instruction is to list all households, i.e., each household must have Form 1 or listing form, the actual procedure done was that, only those households engaged in agriculture with 10 or more trees and/or with cattle were listed. Hence, there is no way that the total number of households could be known in this stratum. This is the reason for including the adjustment factor in the weight of the households in this stratum. Another adjustment factor is added in the weight due to reason that will be discussed in the succeeding paragraph, i.e., weights of Medium Island Group. The actual weight used for small island group is:
wi = (Hproj / M) (Mi'/mi')
Note that this is just a special case of equation (2) where N = n, and mi' = mi.
In case of Medium Island Group where all households in sample EAs were supposedly listed, the weight should be the same as equation (4) had all households in the EA have their respective questionnaire. Unfortunately, after analyzing the frequency distribution of households by sample EAs, the numbers were found to be much less than the counts of household in the 2006 Census of Agriculture or the 2006 Listing of Households. The reason is that only those households with 10 trees or more and, etc. were enumerated. When equation (4) was applied to generate the total number of households, the result gives only approximately 60% of the projected number of households. The reason is that the resulting count is the number of households with 10 trees or more and, etc. and not the total number of households in the stratum. These figures would definitely be very difficult to explain to data users - considering that this is supposed to be a census of all households and not a census of those with 10 trees or more … To solve the problem, another adjustment factor is included in the weight, that is, M'/m' where M' is the total number of households engaged in agriculture from the 2006 listing of households and m' is the number of households with 10 trees or more and etc. In layman terms, the total number of households found to be engaged in agriculture in 2006 listing of households in the EA is distributed proportionately to each questionnaire in the file. The effect of this technique is higher estimates since those households engaged with less than 10 trees, etc. (that is, households excluded in the frame) have been included in the estimation. The weight used for medium island group is:
wi = (N/n)[Hproj/(?(N/n)Mi)] (Mi'/mi') eq. (5)
Note that this is a special case of equation (2) where mi' = mi.
Estimation procedure for Large Island Group used weight similar to the above equation but another factor is included. The adjustment factor is mi' / m, where m is the number of sample households. Since mi' will cancel out, the simplified equation is given below:
wi = (N/n)[Hproj/(?(N/n)Mi)] (Mi'/mi) eq. (6)
The weight derived using the above equation (equation 6) is attached to all sample households only while weight derived using equation (5) is attached to all questionnaires (set of forms or cases) in the file. As mentioned above, sample households are those questionnaires with household form, i.e., all questionnaires in small and medium island groups and sample household questionnaires in large island group. The data item name of sample household weight is SWEIGHT, while all forms weight is DWEIGHT. Hence DWEIGHT is computed using equation (5) while equation (6) is used to compute SWEIGHT.
5.3 Using the Weights
As described above, SWEIGHT should be applied to all households (questionnaires) with household forms. In addition, this should be applied when generating totals for Kava and Coconut sub-holdings characteristics.
On the other hand, DWEIGHT should be used when tabulating Cocoa, Vanilla, Pepper, and Cattle sub-holdings characteristics.
Note that when cross tabulation is to be done for variables from these two different weighting groups (mixed), the sample weight SWEIGHT should be used.
5.4 Computation of the projected number of households
As described in the previous section, the number of households as of the first day of the enumeration (1st day of August, 2007) is needed in the weighting procedure. The practice in other countries is that official population projection is used, but since Vanuatu does not have this projection, and since required data are not available to be able to generate the population projection using internationally accepted procedure, an estimate was generated. The procedure for the estimation of the number of households is enumerated below.
1. Projected total population in the country for August, 2007 was computed using the growth rate between the last census of population conducted in November, 1999 and the listing of households which was conducted in May, 2006. The growth rate is 2.63 percent.
2. The total population counts for Urban and Rural areas were estimated using ratio and proportion, which resulted to 52,366 and 176,458 respectively. The main rationale for these prorated estimates is that it is more accurate to use the growth rate for the total population compared to estimates based on individual (i.e., provincial) growth rates.
3. Using the same rationale above, these estimates were distributed to their respective provincial areas using ratio and proportion.
4. The number of households in each province (urban/rural) was computed by dividing the population estimate with the average household size. The household size used is the one generated from the census of agriculture where the weights used is the basic weight, i.e., N/n*M/m. The rationale for using the average household size from the survey is that, when compared to the household size from the 1996 listing of households, it was found out that the figures are very different. If the average household size from 1996 listing of households would be used, the result to the weighted (final) population count would be unpredictable. Other reasons are: a) the sample is large enough to provide statistically accurate means and percentages, b) the definition of household membership used in the 1996 listing of households is not the same as in the 2007 census.
5. These numbers of households in all provinces (Urban / Rural) were added to come up with the final estimates for the total number of households in urban and rural areas in Vanuatu.
6. The final estimate for the number of households in each province was computed by prorating the final estimate for Vanuatu into all provinces using ratio and proportion.
7. In the same manner, the projected number of households in each stratum, i.e., small-island, medium-island, and large-island groups, was computed using ratio and proportion.
Data Collection
Dates of Data Collection (YYYY/MM/DD)
| Start date | End date |
|---|---|
| 2006-10-01 | 2008-10-30 |
Time periods (YYYY/MM/DD)
| Start date | End date | Cycle |
|---|---|---|
| 2006-05-01 | 2007-08-01 | Phase 1: Listing of Agriculture activities |
| 2007-09-01 | Phase 2: Sample surveys |
Mode of data collection
Face-to-face [f2f]
Supervision
With a view to collecting data with high precision, officers and staff members of the VNSO worked as trainers during Phase I while the main census project staff (both VNSO and the Ministry of Agriculture, Quarantine, Forestry and Fisheries (MAQFF)) were responsible for supervising data collection during Phase II. Under their guidance and supervision six census coordinators performed duties as provincial coordinators in both phases. These provincial coordinators were assisted by provincial agriculture officers and hired supervisors working at the island level who were responsible for recruitment, training and supervision of the activities of field level enumerators for Phases I and II.
Type of Research Instrument
The Questionnaire of the 2006-2008 Agriculture Census of Vanuatu was published in English and divided into 9 forms.
Form 1.1: Household
Form 1.2: Crop Garden
Form 1.3: Kava Plants Sub-Holding
Form 1.4: Coconut Farming
Form 2: Cocoa Trees Sub-Holding
Form 3: Coffee Trees Sub-Holding
Form 4: Vanilla Plants Sub-Holding
Form 5: Pepper Plants Sub-Holding
Form 6: Cattle Sub-Holding
Form 7: Commercial Farm/Holding
Form A: List of Agriculture Activities
Form B1: Control Sheet for all Small and Medium Sized-Islands.
Form 1.1: Household
Form 1.2: Crop Garden
Form 1.3: Kava Plants Sub-Holding
Form 1.4: Coconut Farming
Form 2: Cocoa Trees Sub-Holding
Form 3: Coffee Trees Sub-Holding
Form 4: Vanilla Plants Sub-Holding
Form 5: Pepper Plants Sub-Holding
Form 6: Cattle Sub-Holding
Form 7: Commercial Farm/Holding
Form A: List of Agriculture Activities
Form B1: Control Sheet for all Small and Medium Sized-Islands.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Vanuatu National Statistics Office | VNSO | Vanuatu Government |
Data Processing
Cleaning Operations
Coding, processing and tabulation were completed by mid-September 2006.
Eight data entry operators were hired by the project to do the data encoding of the Phase I of the project. This was the first-hands on as far as the software is concerned for all the data entry operators. Before the actual data entry, the data processing expert had all eight operators plus the supervisors on a training session for a few days. At the end of the training session, they were familiar with the software and then started the actual data encoding. The processing of data for Phase I of the project took the entire month of June 2006 to be completed.
During the Phase II of the project, the expert set up the system and trained the local staff on system operation for two weeks and then left for his home country. Since the project staff and the data entry operators who were hired were already familiar with CsPro, the whole data processing was done without the presence of the consultant. The expert later came for his final mission to prepare the data for tabulation and generate the required tables using the table specifications for that purpose.
The machine data processing of the forms was done using CsPro. Data encoding, data cleaning and tabulation were done using data entry, batch edit and cross tab applications respectively. Control and management of the data entry of the forms and data cleaning of the batch files were done using SCIPS (Survey / Census Integrated Processing System), a Visual Basic 6 (VB6) program developed by the expert designed to integrate the different phases of data capture and data cleaning of any survey/census. The program facilitates the assignment of folios to keyers that resulted to automatic recording of the data capture status of each batch/folio and eliminated errors in the encoding of the geographic identification codes. It also made the data cleaning easier since SCIPS enabled the users to correct errors found by the data consistency and completeness check programs without printing the generated error list.
Eight data entry operators were hired by the project to do the data encoding of the Phase I of the project. This was the first-hands on as far as the software is concerned for all the data entry operators. Before the actual data entry, the data processing expert had all eight operators plus the supervisors on a training session for a few days. At the end of the training session, they were familiar with the software and then started the actual data encoding. The processing of data for Phase I of the project took the entire month of June 2006 to be completed.
During the Phase II of the project, the expert set up the system and trained the local staff on system operation for two weeks and then left for his home country. Since the project staff and the data entry operators who were hired were already familiar with CsPro, the whole data processing was done without the presence of the consultant. The expert later came for his final mission to prepare the data for tabulation and generate the required tables using the table specifications for that purpose.
The machine data processing of the forms was done using CsPro. Data encoding, data cleaning and tabulation were done using data entry, batch edit and cross tab applications respectively. Control and management of the data entry of the forms and data cleaning of the batch files were done using SCIPS (Survey / Census Integrated Processing System), a Visual Basic 6 (VB6) program developed by the expert designed to integrate the different phases of data capture and data cleaning of any survey/census. The program facilitates the assignment of folios to keyers that resulted to automatic recording of the data capture status of each batch/folio and eliminated errors in the encoding of the geographic identification codes. It also made the data cleaning easier since SCIPS enabled the users to correct errors found by the data consistency and completeness check programs without printing the generated error list.
Data Appraisal
Estimates of Sampling Error
The number of households to be interviewed is based on the sampling methodology that is used in the census. The 15 major islands were classified as:
1. small - if the number of households engaged in agricultural activities is less than 500; in this case, Torres, Paama and Erromango are under this category.
2. medium - if the number of households engaged in agricultural activities is between 500 - 1,999; Banks, Malo, Maewo, Ambrym, Epi and Shepherds belong to this group.
3. large - if the number of households operating agricultural activities is 2,000 or more; Santo, Efate, Malekula, Ambae, Pentecost and Tanna were considered to be large islands.
In selecting the number of households to be interviewed in each island, the following was carried out:
a. For Erromango, Torres and Paama, all households were listed and those households engaged in agricultural activities were enumerated;
b. For Banks, Malo, Maewo, Ambrym, Epi and Shepherds, 1/3 of the sample EAs in these islands were selected and all households were listed and those engaged in agricultural activities were interviewed for their involvement in these activities; and
c. For Santo, Efate, Malekula, Ambae, Pentecost and Tanna, 1/3 of the total EAs were also selected in each island and all households were listed in these islands, after which only 1/3 of the households engaged in agricultural activities were further interviewed if they were involved in crop garden, coconut sub-holding and kava sub-holding. In addition to this, all households in the selected EAs of these islands that were involved in the sub-holding of cattle and cash crops (with 10 trees or more) like cocoa, coffee (for Tanna only), vanilla and pepper were enumerated.
1. small - if the number of households engaged in agricultural activities is less than 500; in this case, Torres, Paama and Erromango are under this category.
2. medium - if the number of households engaged in agricultural activities is between 500 - 1,999; Banks, Malo, Maewo, Ambrym, Epi and Shepherds belong to this group.
3. large - if the number of households operating agricultural activities is 2,000 or more; Santo, Efate, Malekula, Ambae, Pentecost and Tanna were considered to be large islands.
In selecting the number of households to be interviewed in each island, the following was carried out:
a. For Erromango, Torres and Paama, all households were listed and those households engaged in agricultural activities were enumerated;
b. For Banks, Malo, Maewo, Ambrym, Epi and Shepherds, 1/3 of the sample EAs in these islands were selected and all households were listed and those engaged in agricultural activities were interviewed for their involvement in these activities; and
c. For Santo, Efate, Malekula, Ambae, Pentecost and Tanna, 1/3 of the total EAs were also selected in each island and all households were listed in these islands, after which only 1/3 of the households engaged in agricultural activities were further interviewed if they were involved in crop garden, coconut sub-holding and kava sub-holding. In addition to this, all households in the selected EAs of these islands that were involved in the sub-holding of cattle and cash crops (with 10 trees or more) like cocoa, coffee (for Tanna only), vanilla and pepper were enumerated.
Data Appraisal
Consultants have not provided documents regarding this aspect of data quality.
Data access
Contact
| Name | Affiliation | URI | |
|---|---|---|---|
| Vanuatu National Statistics Office | VNSO | [email protected] | http://www.vnso.gov.vu |
Confidentiality Declaration
Confidentiality of the respondent is the VNSO's responsibility:
1. Not to take no copies for the forms outside of office.
2. Not publish any names.
Conditions
Currently there is no access policy to access this data but the Government Statistician will look into this issue and put inplace some data access policies.
Citation requirement
"National Statistics Office of Vanuatu, Agriclture Census 2006-2008 (AGC 2006), Version 01 of the licensed dataset (September 2008), 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.
Copyright
Vanuatu Government
Contacts
Contact
| Name | Affiliation | URI | |
|---|---|---|---|
| Vanuatu National Statistics Office | Government of Vanuatu | [email protected] | http://www.vnso.gov.vu |
Metadata production
Document ID
DDI_SPC_VUT_2006_AGC_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Vanuatu National Statistics Office | VNSO | Vanuatu Government | Documentation of the study |
| Statistics for Development Division | SDD | Pacific Community | Review of the documentation |
Date of Production
2008-10-31
Document version
Version 01 (March 2009): Done during a training provided by the Pacific Community (SPC). Done by Vanuatu National Statistics Office.
Version 02 (July 2019): Review of the existing documentation. Done by Statistics for Development Division at Noumea, New Caledonia.
Version 02 (July 2019): Review of the existing documentation. Done by Statistics for Development Division at Noumea, New Caledonia.