PHL_2009_PPS_v01_EN_M_v01_A_OCS
Palay Production Survey 2009
Name | Country code |
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Philippines | PHL |
Agricultural Survey [ag/oth]
The Palay Production Survey (PPS) 2009 covered the April 2009, July 2009, October 2009 and January 2010 Rounds of the 55th year of the quarterly survey conducted by the Bureau of Agricultural Statistics (BAS). PPS is one of the two modules of the Palay and Corn Production Survey (PCPS). The other module is the Corn Production Survey (CPS).
The generation of production statistics on palay and corn through the quarterly Rice and Corn Production (RCPS), now known as the Palay and Corn Production Survey (PCPS) dates back to as early as 1954 when BAS was still a division (Agricultural Economics Division) of the then Department of Agriculture and Natural Resources (DANR).
The RCPS has for its predecessors, the Crops and Livestock Survey (CLS), 1954-1968; the Integrated Agricultural Survey (IAS), 1968-1985; and the Rice and Corn Survey (RCS), 1985-1993. Prior to 1986, the RCS employed a two-stage stratified sampling design with municipality as the domain. In 1986, the RCS adopted a three-stage sampling design with province as the domain. In 1989, the RCPS design evolved from a statistical research undertaken jointly by the Philippine Statistical Association (PSA) and BAS under a grant from the USAID. It was conceived as an improvement to the RCS with a completely different sampling frame and design.
BAS officially adopted the new RCPS design in July 1994. The design used the results of the 1991 Census of Agriculture (CA) as basis for sampling frame and is still being implemented up to the present. Despite the long history of this quarterly survey, the Bureau continuously improves its design and contents. Thus, in 2007, an updating of the list of farming households in the PPS sample barangays was made. Consequently, a new set of sample households was drawn. Likewise, modification in the contents of the survey was made and implemented in December 2007 (January 2008 round). Also, starting this round, the name of the survey was changed to Palay and Corn Production Survey (PCPS).
The improved Palay Production Survey, January 2008 Round, underwent further changes on sample status and terms and concepts used. Hence, revisions of the questionnaire were made and a supplementary manual of instruction was provided for the PPS April 2008 Round.
In October 2008, with funding support from the GMA Rice Program, the Enhanced Information System for Palay (EISP) was implemented. This project aimed to to develop and maintain a comprehensive quarterly report containing all the data elements generated from the PPS. The EISP presents information on palay production, area and yield by ecosystem and seed class. It also contains data on source and adequacy of irrigation water, usage of fertilizers, chemicals and seeds, disposition and utilization of production, and information on farmers' awareness and participation in the GMA Rice Program. All this information was disaggregated at the provincial level.
The Palay Production Survey is one of the two modules of the Palay and Corn Production Survey (PCPS), formerly known as the Rice and Corn Production Survey (RCPS).
The Palay Production Survey (PPS) 2009 was a quarterly survey conducted by the Bureau of Agricultural Statistics (BAS). It aimed to generate estimates on palay production, area and yield and other related information at the provincial level. It was conducted in four rounds, namely: January, April, July and October. Each round generated estimates for the immediate past quarter and forecasts for the next two quarters. Results of the survey served as inputs to planners and policy makers on matters concerning the rice industry.
Sample survey data [ssd]
Households
The scope of the Palay Production Survey includes:
National Coverage
Farming households in palay producing barangays.
Name | Affiliation |
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Bureau of Agricultural Statistics | Department of Agriculture |
Name | Role |
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Bureau of Agricultural Statistics | Funding |
The sampling procedure used in the Palay Production Survey 2009 (PPS 2009) was first implemented in 1994. This was a replicated two-stage stratified sampling design with province as the domain, barangay as the primary sampling unit (PSU) and farming household as the secondary sampling unit (SSU).
The results of the 1991 Census of Agriculture and Fisheries (CAF 1991) served as sampling frame at the PSU and SSU levels. In the said census, the largest barangay in a municipality was taken with certainty while a 50 percent sampling rate was used for selecting the remaining barangays in the municipality. This scheme effectively resulted in the generation of two sub universes: a sub universe of barangays with probability of selection equal to one (these barangays were called 'certainty barangays') and another sub universe of barangays with probability of selection equal to 0.5. This characteristic of the CAF 1991 data was used in the selection of sample barangays for the PPS.
The barangays were arrayed in ascending order based on palay area then stratified such that the aggregate palay area of the barangays belonging to one stratum is more or less equal to the aggregate palay area of the barangays in any other stratum. Ten strata were formed for major palay producing provinces and five for minor producing provinces. In all these provinces, the last stratum consisted of the certainty barangays per CAF 1991 design.
For each stratum, four (4) sample barangays were drawn independently using probability proportional to size (PPS) sampling with the barangay's palay area as size measure. This resulted with four (4) independent sets of barangays (i.e., four replicates) for the province. Systematic sampling was used in drawing the sample farming households in each sample barangay.
For economic reasons, sample size per barangay was limited to a minimum of four (4) and a maximum of twenty-five (25). To correct for this limitation of the design, the use of household weights was instituted. A detailed discussion of weighting in the PPS is included in the survey's estimation procedure attached as a technical document.
In November 2007, an updating of the list of farming households in all palay sample barangays nationwide was done to address the problem of non-response due to transfer of residence, stoppage of farm operation, passing away of operator etc. Consequently, a new set of sample households was drawn.
Absent respondents such as refusals, not at home, unknown and transferred to another barangay were treated as missing and were replaced at the central office for the next quarter's survey. The replacement samples were taken from the list of replacements (farming households) for the barangay and were reflected in the list of sample households for the next round.
Response rate refers to the ratio of sample households who responded to the survey to the total number of sample households, expressed as a percentage. For Palay Production Survey (PPS), responding samples include farming households who are into palay farming (code 10), those who are into other agricultural activities or with no agricultural activities during the reference period (code 20).
The PPS 2009 response rates were as follows:
Sample weights were applied to all variables at the household-level. These were determined as a function of the uniform raising factor for the province, denoted by Rk, and the adjusted household weights.
Rk was initially computed from the following characteristics: average total area planted to corn per stratum, average total area planted to corn per barangay, average number of farming households per barangay, average number of sample farming households per barangay and average number of sample barangays per stratum.
Sample size for the sample barangay was determined based on the following information: Rk, total number of farm households in the sample barangay, total corn area of the sample barangay, aggregate corn area in the stratum and number of sample barangays in the stratum.
For operational purposes, sample size per barangay was limited to a minimum of four (4) and a maximum of 25. To correct for this limitation, the use of a uniform sample weight for all sample households in the same sample barangay was instituted. Household weights were determined as a function of the computed sample size and the 'desired' sample size for the barangay, that is:
a) 1.00 if the computed sample size was between 4 and 25,
b) less than 1.00 if computed sample size was less than 4,
c) more than 1.00 if computed sample size was more than 25, and
d) based on computed sample size and number of farming households in the barangay if computed sample size was less than 25 and said sample size was greater than total number of farming households in the barangay.
Household weights were encoded together with other household level data. During table generation, weighting adjustment was done to correct for sampling unit non-response due to the following reasons:
Weighting adjustment was done for each sample barangay, whenever applicable. This was calculated by multiplying the original household weight by the reciprocal of the response rate. Response rate is the ratio of the number of sample households who responded to the survey (either corn household and non-corn household) to the total number of sample households in the barangay. Calculation of the final weight was done afterwards, by multiplying the adjusted weight by the uniform raising factor Rk.
Details of the above discussion except for weighting adjustment procedures, are contained in the document describing the Palay Production Survey (PPS) sampling methodology provided attached as a technical document.
Start | End | Cycle |
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2009-04-01 | 2009-04-10 | April 2009 Round |
2009-07-01 | 2009-07-10 | July 2009 Round |
2009-10-01 | 2009-10-10 | October 2009 Round |
2009-12-01 | 2009-12-10 | January 2010 Round |
Prior to data encoding, the accomplished survey returns were manually edited and coded. Manual editing was the checking of responses to the Palay Production Survey (PPS) questionnaire in terms of acceptability and validity. This activity was aimed at improving the quality of data collected by the CDCs. It involved the checking of data items based on criteria like completeness of data, consistency with other data items and data ranges. Coding was the assignment of alpha-numeric codes to questionnaire items to facilitate encoding.
Encoded data were subjected to computerized editing using a customized editing program. The editing program took into consideration the validation criteria such as validity, completeness and consistency with other data items. This activity was done to capture invalid entries that were overlooked during manual editing. An error listing was produced as output of the process. The errors reflected in said lists were verified vis-à-vis the questionnaires. The data files were updated based on the corrections made. Editing and updating were performed iteratively until a clean, error-free data file was generated.
Completeness check was done to compare the data file against a master file of barangays to check if the sample barangays have been completely surveyed or not. This activity was done after a clean, error-free data file was generated.
To ensure the quality of its statistical services, the BAS has mainstreamed in its statistical system for generating production statistics, a quarterly data review and validation process. This is undertaken at the provincial, regional and national levels to incorporate the impact of events not captured in the survey.
The data review process starts at the data collection stage and continues up to the processing and tabulation of results. However, data examination is formalized during the provincial data review since it is at this stage where the data at the province-level is analyzed as a whole. The process involves analyzing the survey data in terms of completeness, consistency among variables, trend and concentration of the data and presence of extreme observations. Correction of spotted errors in the data is done afterwards. The output of the process is a clean data file used in the re-computation of survey estimates.
The estimates generated from the clean data set are thoroughly analyzed and validated with auxiliary information to incorporate the impact of information and events not captured by the survey. These information include results of the Monthly Palay and Corn Survey Report (MPCSR), historical data series, report on weather condition, area and crop condition, irrigation, levels of inputs usage, supply and demand, marketing of agricultural products, and information on rice and corn program implementation.
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, Palay Production Survey, Version v2.0 of the licensed dataset (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 | URL | |
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Director | Bureau of Agricultural Statistics | [email protected] | http://beans.bas.gov.ph |
DDI_PHL_2009_PPS_v01_EN_M_v01_A_OCS_FAO
Name | Affiliation | Role |
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Office of Chief Statistician | Food and Agriculture Organization | Metadata adapted for FAM |
Jacinta U. Estrada | Bureau of Agricultural Statistics | Documentation of the study |
Minda C. Mangabat | Bureau of Agricultural Statistics | Reviewer |
Maura S. Lizarondo | Bureau of Agricultural Statistics | Reviewer |
PHL_2009_PPS_v01_EN_M_v01_A_OCS_v01