PHL_2009_APS_v01_EN_M_v01_A_OCS
Aquaculture Production Survey 2009
Name | Country code |
---|---|
Philippines | PHL |
Agricultural Survey [ag/oth]
Prior to this survey round, the last conduct of APS was in the 4th quarter of the 2008 round.
In carrying out its responsibility of generating statistics on volume and value of aquaculture production, the Fisheries Statistics Division (FSD) of the Bureau of Agricultural Statistics (BAS) conducts probability and non-probability surveys. The Quarterly Aquaculture Surveys (QAS) is the non-probability survey conducted on a regular basis. The survey design involves computing for the average percent change from the same quarter last year reported by the sample respondents and then applying the same to the provincial level same quarter last year estimate in order to derive the estimate for the current quarter. The samples are taken from 5 X 5 sampling design, i.e., five (5) sample operators from top five (5) producing municipalities. On the other hand, Aquaculture Production Survey (APS) generates the production estimates based on one-stage stratified sampling design. Unfortunately, this probability survey is not financially sustainable on a quarterly basis. It should be noted that estimates from the probability survey are intended as baseline data for computing the percent changes derived from non-probability survey. Although quarterly estimates are subjected to a series of data review and analysis before final estimates are released, it is imperative to determine the levels of production estimates through a periodic probability survey.
Primarily, the Aquaculture Production Survey (APS) aims to generate statistics on volume and value of aquaculture production by province. Specifically, it aims to gather information on:
a. Volume and value of production by species cultured, by aquafarm type and by environment,
b. Area harvested; and
c. Management and culture system of the aquafarm.
Sample survey data [ssd]
Entreprises
The survey form gathers information on the following:
National Coverage
The survey covered all aquafarm types.
Name | Affiliation |
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Bureau of Agricultural Statistics (BAS) | Department of Agriculture |
Name | Role |
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Bureau of Fisheries and Aquatic Resources | Provides funds for the conduct of fisheries surveys |
The APS adopted a one-stage stratified sampling design. By aquafarm type, all operators from municipalities with at least 80% cumulative share to total aquafarm area were stratified into three (3) strata using area as the stratification variable. The boundary between strata was determined by the distribution of data. If the number of aquafarms in a stratum is less than or equal to fifteen (15), all aquafarms were taken as a sample. Sample aquafarms were selected through systematic random sampling procedure.
A slight modification in the sampling design was employed. For this survey round, sample aquafarms were selected only from the municipalities with at least 80% cumulative share to provincial area. This was done to simplify field operations and ensure that sample aquafarms from these municipalities were more or less productive.
Aquafarm weights were computed as the quotient of total number of aquafarms and number of sample aquafarms in the stratum.
Start | End | Cycle |
---|---|---|
2009-11-30 | 2009-12-11 | 4th Quarter |
Initially, the survey returns were manually edited to ensure completeness and accuracy. During this stage, survey returns are checked for completeness from the list of samples. For each of the questionnaires, entries should be complete and numeric entries should be in proper unit of measurement and decimal places. After encoding, the entries are then again inspected and reviewed for completeness, accuracy and consistency with other items.
An APS data processing work sheet was developed using MS Excel 2003 to process the APS survey returns. The results were then encoded in the Aquaculture Data Generation System (AquaDataGen). The AquaDataGen was developed for the data processing requirements of Quarterly Aquacutlure Survey (QAS). This system is decentralized in the provinces but regional and national summary can also be derived. The AquaDataGen has the facility for data entry, data review and validation.
Is signing of a confidentiality declaration required? | Confidentiality declaration text |
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yes | The Bureau of Agricultural Statistics (BAS) strictly observes the confidentiality of data. As stated in the BAS' survey questionnaires and the forms relevant to the conduct of any statistical inquiry, data provided by the respondents shall be used solely for statistical purposes. |
The datasets of this study are categorized under licensed files. Access to licensed datasets is through request and is only granted to Data Users/Researchers with a legally registered sponsoring agency (university, company, research centre, national or international organization, etc.).
The Data Users/Researchers must agree to comply with the following:
As specified in the agreement under access conditions, users are required to cite the source of data in accordance with the citation requirement provided with the dataset. The citation requirement for this study is as follows:
"Bureau of Agricultural Statistics, Quarterly Aquaculture Survey, Version 2 of the licensed dataset (August 31, 2009), provided by the BAS Electronic Archiving and Network Services. http://beans.bas.gov.ph"
The data users/researchers acknowledge that the BAS and the agency funding the study bear no liabilities and responsibilities for any particular, indirect, or consequential damages or any damages, whatsoever resulting from loss of use, or of data in connection with the use or for interpretations or inferences based upon such uses.
Name | Affiliation | |
---|---|---|
Chief, Fisheries Statistics Division | Bureau of Agricultural Statistics | [email protected] |
Romeo S. Recide | BAS | [email protected] |
DDI_PHL_2009_APS_v01_EN_M_v01_A_OCS_FAO
Name | Affiliation | Role |
---|---|---|
Office of the Chief Statistician | Food and Agriculture Organization | Metadata adapted for FAM |
Reinelda P. Adriano | Bureau of Agricultural Statistics | Documentation of the study |
PHL_2009_APS_v01_EN_M_v01_A_OCS_v01