Palay Production Survey 2009
Philippines, 2009
Reference ID
PHL-BAS-PPS-2009-v2.0
Producer(s)
Bureau of Agricultural Statistics
Collection(s)
Metadata
Created on
Sep 14, 2021
Last modified
Sep 14, 2021
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Identification
Palay Production Survey 2009
Name | Abbreviation |
---|---|
Philippines | PHL |
PHL-BAS-PPS-2009-v2.0
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.
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]
Farming households;
Palay areas operated by farming households
Palay areas operated by farming households
Version
v2.0 Household level data edited at Central Office, not anonymized.
2009-08-15
v0- is the raw, unedited household level data
v1.0 -is the household level data edited at provincial level, not anonymized, for internal use
v2.0- is the household level data edited at Central Office, not anonymized, for internal use
v1.0 -is the household level data edited at provincial level, not anonymized, for internal use
v2.0- is the household level data edited at Central Office, not anonymized, for internal use
Coverage
National
80 provinces in 16 Regions (National Capital Region not included)
80 provinces in 16 Regions (National Capital Region not included)
Barangay
Farming households;
Palay areas operated by farming households
Palay areas operated by farming households
Farming households in palay producing barangays.
Producers and sponsors
Name | Abbreviation | Role |
---|---|---|
Bureau of Agricultural Statistics | BAS |
Name | Affiliation | Role | |
---|---|---|---|
National Statistical Coordination Board | Survey clearance |
Sampling
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 barangas 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.
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 barangas 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:
April 2009 Round - 91.54%
July 2009 Round - 90.93%
October 2009 Round - 94.21%
January 2010 Round - 92.76%
The PPS 2009 response rates were as follows:
April 2009 Round - 91.54%
July 2009 Round - 90.93%
October 2009 Round - 94.21%
January 2010 Round - 92.76%
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:
- refusal of target respondent or any othe knowledgable household member to be interviewed
-sample barangay was not accessible during the survey period
-entire household was temporarily away during the survey operation-
-sample household has transferred residence to another barangay
- sample household's residence could not be located / unknown in the sample barangay
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.
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:
- refusal of target respondent or any othe knowledgable household member to be interviewed
-sample barangay was not accessible during the survey period
-entire household was temporarily away during the survey operation-
-sample household has transferred residence to another barangay
- sample household's residence could not be located / unknown in the sample barangay
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.
Data Collection
Start | End | Cycle |
---|---|---|
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 |
Start | End | Cycle |
---|---|---|
2009-01-01 | 2009-03-31 | April 2009 Round (Final)) |
2009-04-01 | 2009-06-30 | April 2009 Round (Forecast based on standing crop) |
2009-07-01 | 2009-09-30 | April 2009 Round (Forecast based on planting intention) |
2009-04-01 | 2009-06-30 | July 2009 Round (Final) |
2009-07-01 | 2009-09-30 | July 2009 Round (Forecast based on standing crop) |
2009-10-01 | 2009-12-31 | July 2009 Round (Forecast based on planting intention) |
2009-07-01 | 2009-09-30 | October 2009 Round (Final) |
2009-10-01 | 2009-12-31 | October 2009 Round (Forecast based on standing crop) |
2010-01-01 | 2010-03-31 | October 2009 Round (Forecast based on planting intention) |
2009-10-01 | 2009-12-31 | January 2010 Round (Final) |
2010-01-01 | 2010-03-31 | January 2010 Round (Forecast based on standing crop) |
2010-04-01 | 2010-06-30 | January 2010 Round (Forecast on planting intention) |
Face-to-face [f2f]
Field supervision was undertaken by the Provincial Operations Center (POC) staff in their respective munitipalities of assignments. The Provincial Agricultural Statistics Officer (PASO) served as overall supervisor in the province, while the Regional Agricultural Statistics Officer (RASO) was the overall supervisor in the region. Central Office technical staff also made field visits in some provinces to observe the field operations.
Among the responsibilities of the supervisor were the conduct of CDC training prior to data collection, doing spotchecking and backchecking activities during and after data collection, editing of completed returns, addressing of problems encountered by the CDCs under him/her supervision and reporting to Central Office the significant findings that may contribute to the analysis of the survey results.
Among the responsibilities of the supervisor were the conduct of CDC training prior to data collection, doing spotchecking and backchecking activities during and after data collection, editing of completed returns, addressing of problems encountered by the CDCs under him/her supervision and reporting to Central Office the significant findings that may contribute to the analysis of the survey results.
The Palay Production Survey 2009 was written in English. It was a structured questionnaire that can accomodate data for five sample households. It evolved from modifications of the 2007 questionnaire based on the emerging data needs of the Rice Program. The new questionnaire was implemented in the January 2008 Round with the following features: more detailed sample status categories, items on production and area by seed type, inclusion of items on application of organic fertilizer and pesticides usage, additional items on palay disposition and utilization and awareness and availment of Ginintuang Masaganang Ani (GMA) Rice Program benefits and services.
The questionnaire was divided into the following blocks:
Block A- Sample identification
Block B- Sample particulars
Block C- Information of paddy (palay) harvested
C1- Palay area, production and irrigation information
C2- Information on yield enhancing and protecting inputs
Block D- Palay disposition and utilization
Block E- Palay production forecast (on standing crop)
Block F- Palay planting intentions
Block G- Respondent's assessment of the household's Palay production
Block H- Farmer's participation in Ginintuang Masaganang Ani (GMA) Rice Program
Block I- Data collector, supervisor, PASO and encoder identification
A detailed description of these blocks are provided in Technical Documents.
The questionnaire was divided into the following blocks:
Block A- Sample identification
Block B- Sample particulars
Block C- Information of paddy (palay) harvested
C1- Palay area, production and irrigation information
C2- Information on yield enhancing and protecting inputs
Block D- Palay disposition and utilization
Block E- Palay production forecast (on standing crop)
Block F- Palay planting intentions
Block G- Respondent's assessment of the household's Palay production
Block H- Farmer's participation in Ginintuang Masaganang Ani (GMA) Rice Program
Block I- Data collector, supervisor, PASO and encoder identification
A detailed description of these blocks are provided in Technical Documents.
Name | Abbreviation | Affiliation |
---|---|---|
Bureau of Agricultural Statistics | BAS | Department of Agriculture |
Data Processing
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.
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.
Data Appraisal
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.
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.
Data access
Name | Affiliation | URI | |
---|---|---|---|
Director | Bureau of Agricultural Statistics | http://beans.bas.gov.ph | info@bas.gov.ph |
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:
1. Fill up a Data Access Agreement that will be provided.
2. Copies of the restricted data or any data created on the basis of the original data will not be copied or made available to anyone other than those mentioned in this Data Access Agreement, unless formally authorized by the BAS.
3. The data will only be processed for the stated statistical purpose in the agreement and not for investigation of specific individuals or organizations. Data will not in any way be used for any administrative, proprietary or law enforcement purposes.
4. The dataset must not be made to match with other datasets.
5. The Data Users/Researchers shall not attempt to identify any individual person, family, business, enterprise or organization. If such a unique disclosure is made inadvertently, no use will be made as to the identity of any person or establishment discovered. The identification will not be revealed to any other person not included in the Data Access Agreement.
6. The Data Users/Researchers must observe security measures to prevent unauthorized access to licensed microdata acquired from the BAS. The microdata must be destroyed upon the completion of their research. Destruction of the microdata will be confirmed in writing by the Data Users/Researchers to the BAS.
7. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the BAS/BAS Electronic Archiving and Network Services (BEANS) will cite the source of data in accordance with the citation requirement provided with the dataset.
8. If there are any changes or additional requirements in the orginal request, the Data User/Researcher must apply for another request.
9. Breaches of the Data Access Agreement will be taken seriously and the BAS will take action against those responsible for the lapses if wilful or accidental. Failure to comply with the directions of the BAS will be deemed to be a major breach of the agreement and may involve recourse to legal proceedings. The BAS will maintain and share with partner data archives a record of those individuals and organizations which are responsible for breaching the terms of the Data Access Agreement and will impose sanctions on release of future data to these parties.
The Data Users/Researchers must agree to comply with the following:
1. Fill up a Data Access Agreement that will be provided.
2. Copies of the restricted data or any data created on the basis of the original data will not be copied or made available to anyone other than those mentioned in this Data Access Agreement, unless formally authorized by the BAS.
3. The data will only be processed for the stated statistical purpose in the agreement and not for investigation of specific individuals or organizations. Data will not in any way be used for any administrative, proprietary or law enforcement purposes.
4. The dataset must not be made to match with other datasets.
5. The Data Users/Researchers shall not attempt to identify any individual person, family, business, enterprise or organization. If such a unique disclosure is made inadvertently, no use will be made as to the identity of any person or establishment discovered. The identification will not be revealed to any other person not included in the Data Access Agreement.
6. The Data Users/Researchers must observe security measures to prevent unauthorized access to licensed microdata acquired from the BAS. The microdata must be destroyed upon the completion of their research. Destruction of the microdata will be confirmed in writing by the Data Users/Researchers to the BAS.
7. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the BAS/BAS Electronic Archiving and Network Services (BEANS) will cite the source of data in accordance with the citation requirement provided with the dataset.
8. If there are any changes or additional requirements in the orginal request, the Data User/Researcher must apply for another request.
9. Breaches of the Data Access Agreement will be taken seriously and the BAS will take action against those responsible for the lapses if wilful or accidental. Failure to comply with the directions of the BAS will be deemed to be a major breach of the agreement and may involve recourse to legal proceedings. The BAS will maintain and share with partner data archives a record of those individuals and organizations which are responsible for breaching the terms of the Data Access Agreement and will impose sanctions on release of future data to these parties.
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"
"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"
Disclaimer and copyrights
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.
Copyright 2009 © Bureau of Agricultural Statistics, All rights reserved.
contacts
Name | Affiliation | URI | |
---|---|---|---|
Director | Bureau of Agricultural Statistics | info@bas.gov.ph | http://beans.bas.gov.ph |