Monthly Palay and Corn Situation Reporting System 2017
Philippines, 2017
Reference ID
PHL-PSA-MPCSRS-2017-v1.0
Producer(s)
Philippine Statistics Authority (PSA)
Metadata
Created on
Jun 14, 2022
Last modified
Jun 14, 2022
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Identification
Monthly Palay and Corn Situation Reporting System 2017
Name | Abbreviation |
---|---|
Philippines | PHL |
PHL-PSA-MPCSRS-2017-v1.0
The Palay and Corn Production Survey (PCPS) is one of the major agricultural surveys conducted by the Philippine Statistics Authority (PSA). This is conducted in two modules, the Palay Production Survey (PPS) and the Corn Production Survey (CPS). The data gathered from both modules include actual harvests for the current period and forecasts for the next quarters based on standing crop and planting intention. Forecast data are subject to changes depending on weather conditions, inputs and outputs, prices and other factors which contribute largely to the deviations of the actual data from the early forecasts. In such case, a close monitoring of the growing conditions and actual plantings of the crop is deemed necessary. This is done through the Monthly Palay and Corn Situation Reporting System (MPCSRS).
The MPCSRS primarily aims to:
1. Update the estimate of the current quarter based on standing crop and forecast for the next quarter based on planting intentions; and
2. Provide monthly updates on area and production of palay and corn across the country.
The MPCSRS primarily aims to:
1. Update the estimate of the current quarter based on standing crop and forecast for the next quarter based on planting intentions; and
2. Provide monthly updates on area and production of palay and corn across the country.
Sample survey data [ssd]
Palay and corn farming households
Version
V1.0: Division edits for preliminary estimates computation (raw, first output)
2017-04-01
Scope
Topic | Vocabulary | URI |
---|---|---|
Agriculture, forestry, fisheries | Philippine Statistics Authority |
keyword | URI |
---|---|
Palay | |
Corn | |
Reproductive | |
Vegetative | |
Maturing | |
Ecosystem | |
Area | |
Production | |
Standing crop | |
Planting intentions |
Coverage
The survey covers all provinces (except Batanes) and two (2) chartered cities (Davao City and Zamboanga City).
Barangay level aggregation
Palay and corn farming households
Farming households
Producers and sponsors
Name | Abbreviation | Role |
---|---|---|
Government of the Philippines | GOP | Full funding |
Sampling
The MPCSRS is a sub-sample of the Palay and Corn Production Survey (PCPS) which employs a two-stage stratified sampling design with the barangay as the primary sampling unit (psu) and the household as the secondary sampling unit (ssu). One replicate of the PCPS sample barangays is selected to represent MPCSRS sample barangays covering farming households.
Under the enhanced MPCSRS, the number of sample barangays is pre-determined in the province using one replicate (any of the four or combination of replicates) of the PCPS as samples, such that:
For major palay provinces, one replicate consisting of ten (10) barangays is taken from the PPS samples
For major corn provinces, one replicate consisting of ten (10) barangays is taken from the CPS samples
For minor palay or corn provinces, one replicate consisting of five (5) barangays are taken as samples.
In each barangay, 4-25 sample households are taken as select. The selection of the sample households is the same with that of the PCPS.
Under the enhanced MPCSRS, the number of sample barangays is pre-determined in the province using one replicate (any of the four or combination of replicates) of the PCPS as samples, such that:
For major palay provinces, one replicate consisting of ten (10) barangays is taken from the PPS samples
For major corn provinces, one replicate consisting of ten (10) barangays is taken from the CPS samples
For minor palay or corn provinces, one replicate consisting of five (5) barangays are taken as samples.
In each barangay, 4-25 sample households are taken as select. The selection of the sample households is the same with that of the PCPS.
MPCSRS response rate for palay samples is 99%, while response rate for corn samples is 95%
Sample weights are applied to all variables at the household-level. These are determined as a function of the uniform raising factor for the province, denoted by Rk, and the adjusted household weights.
Rk is computed from the following characteristics: average total area planted to palay/corn per stratum, average total area planted to palay/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 is determined based on the following information: Rk, total number of farm households in the sample barangay, total palay/corn area of the sample barangay, aggregate palay/corn area in the stratum and number of sample barangays in the stratum.
For operational purposes, sample size per barangay is 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 is instituted. Household weights are 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 is between 4 and 25;
b) less than 1.00 if computed sample size is less than 4
c) more than 1.00 if computed sample size is more than 25,and
d) based on computed sample size and number of farming households in the barangay if computed sample size is less than 25 and said sample size is greater than total number of farming households in the barangay.
Household weights are encoded together with other household level data. In the course of data table generation, weighting adjustment is being done to correct for unit non-response such as refusals, not-at-home, unknown and transferred to another barangay.
Computation of adjusted household weights as well as the final weight is done for each sample barangay. The adjusted weight is calculated as the product of the original household weight and the inverse of the actual response rate for the barangay. Afterwards, the final weight is determined by multiplying the adjusted weight by Rk.
Rk is computed from the following characteristics: average total area planted to palay/corn per stratum, average total area planted to palay/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 is determined based on the following information: Rk, total number of farm households in the sample barangay, total palay/corn area of the sample barangay, aggregate palay/corn area in the stratum and number of sample barangays in the stratum.
For operational purposes, sample size per barangay is 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 is instituted. Household weights are 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 is between 4 and 25;
b) less than 1.00 if computed sample size is less than 4
c) more than 1.00 if computed sample size is more than 25,and
d) based on computed sample size and number of farming households in the barangay if computed sample size is less than 25 and said sample size is greater than total number of farming households in the barangay.
Household weights are encoded together with other household level data. In the course of data table generation, weighting adjustment is being done to correct for unit non-response such as refusals, not-at-home, unknown and transferred to another barangay.
Computation of adjusted household weights as well as the final weight is done for each sample barangay. The adjusted weight is calculated as the product of the original household weight and the inverse of the actual response rate for the barangay. Afterwards, the final weight is determined by multiplying the adjusted weight by Rk.
Data Collection
Start | End | Cycle |
---|---|---|
2017-02-01 | 2017-02-05 | February 2017 |
2017-03-01 | 2017-03-05 | March 2017 |
2017-05-01 | 2017-05-05 | May 2017 |
2017-06-01 | 2017-06-05 | June 2017 |
2017-08-01 | 2017-08-05 | August 2017 |
2017-09-01 | 2017-09-05 | September 2017 |
2017-11-01 | 2017-11-05 | November 2017 |
Start | End | Cycle |
---|---|---|
2017-01-01 | 2017-03-31 | February 2017 round (Q1 updates on standing crop) |
2017-04-01 | 2017-06-30 | February 2017 round (Q2 updates on planting intentions) |
2017-01-01 | 2017-03-31 | March 2017 round (Q1 updates on standing crop) |
2017-04-01 | 2017-06-30 | March 2017 round (Q2 updates on planting intentions) |
2017-04-01 | 2017-06-30 | May 2017 round (Q2 updates on standing crop) |
2017-07-01 | 2017-09-30 | May 2017 round (Q3 updates on planting intentions) |
2017-04-01 | 2017-06-30 | June 2017 round (Q2 updates on standing crop) |
2017-07-01 | 2017-09-30 | June 2017 round (Q3 updates on planting intentions) |
2017-07-01 | 2017-09-30 | August 2017 round (Q3 updates on standing crop) |
2017-10-01 | 2017-12-31 | August 2017 round (Q4 updates on planting intentions) |
2017-07-01 | 2017-09-30 | September 2017 round (Q3 updates on standing crop) |
2017-10-01 | 2017-12-31 | September 2017 round (Q4 updates on planting intentions) |
2017-10-01 | 2017-12-31 | November 2017 round (Q4 updates on standing crop) |
2018-01-01 | 2018-03-31 | November 2017 round (Q1 2018 updates on planting intentions) |
Face-to-face [f2f]
In the field, the Regional Director (RD) is responsible for the monitoring and supervision of the survey of all provinces within the region. At the provincial level, the overall supervisor is the Provincial Statistical Officer (PSO). The Supervising Statistical Officer, aside from his/her assignment as assistant supervisor in the province, may be given a specific area of supervision, upon the discretion of the PSO. On the other hand, the Provincial Office (PO) staff are tapped to gather the needed information for the survey.
The role of the field supervisor are as follows:
1. Conduct orientation training for Statistical Researchers' (SRs).
2. Prepare a documentation of the proceedings of the orientation training.
3. Determine respective assignments of SRs under his/her supervision.
4. Conduct spot-checking of the SRs under his/her supervision.
5. Address problems and gray areas reported by the SRs.
6. Monitor the progress of SRs' work.
7. Perform field editing of accomplished survey returns.
8. Ensure that all sample households in the barangays are interviewed.
9. Conduct back-checking of SRs' output.
10. Review and validate the survey results.
The role of the field supervisor are as follows:
1. Conduct orientation training for Statistical Researchers' (SRs).
2. Prepare a documentation of the proceedings of the orientation training.
3. Determine respective assignments of SRs under his/her supervision.
4. Conduct spot-checking of the SRs under his/her supervision.
5. Address problems and gray areas reported by the SRs.
6. Monitor the progress of SRs' work.
7. Perform field editing of accomplished survey returns.
8. Ensure that all sample households in the barangays are interviewed.
9. Conduct back-checking of SRs' output.
10. Review and validate the survey results.
The MPCSR questionnaire contains three major blocks, namely, Block A, Block B (includes sub-block B1 and sub-block B2), and Block C.
Block A (Sample Identification) refers to information on the names and codes for the region, province, municipality and barangay. the stratum and replicate numbers that identifies the sample household.
Block B (Update of Current Quarter Area and Production of Standing Crop / Planting Intentions) identifies the enumeration area code, household serial number, name of the sample agricultural operator, sample status and the name of the respondent are defined.
Sub-Block Block B1 (Current Quarter's Area and Production based on Standing Crop) refers to the quarter's forecast data of the previous PCPS survey round and the data update based on the the indications from the sample farmer's present crop situation, including the stage of the crop growth. It also includes plausible reason/s or changes in the latest quarter's forecast.
Sub-Block B2 (Update on the Current Quarter's Planting Intentions) refers to the actual plantings with breakdown by stage of crop growth from the beginning of the quarter up to the cut-off date of each survey/reporting month.
Block C (Statistical Researcher and PSO Identification) gathers information about the Statistical Researcher amd the Provincial Statistics Officer. It specifically contains thier names, signature, and dates of accomplishing the questionnaire.
Block A (Sample Identification) refers to information on the names and codes for the region, province, municipality and barangay. the stratum and replicate numbers that identifies the sample household.
Block B (Update of Current Quarter Area and Production of Standing Crop / Planting Intentions) identifies the enumeration area code, household serial number, name of the sample agricultural operator, sample status and the name of the respondent are defined.
Sub-Block Block B1 (Current Quarter's Area and Production based on Standing Crop) refers to the quarter's forecast data of the previous PCPS survey round and the data update based on the the indications from the sample farmer's present crop situation, including the stage of the crop growth. It also includes plausible reason/s or changes in the latest quarter's forecast.
Sub-Block B2 (Update on the Current Quarter's Planting Intentions) refers to the actual plantings with breakdown by stage of crop growth from the beginning of the quarter up to the cut-off date of each survey/reporting month.
Block C (Statistical Researcher and PSO Identification) gathers information about the Statistical Researcher amd the Provincial Statistics Officer. It specifically contains thier names, signature, and dates of accomplishing the questionnaire.
Name | Abbreviation | Affiliation |
---|---|---|
Philippine Statistics Authority | PSA | National Economic and Development Authority |
Data Processing
From the accomplished questionnaires, the SR should perform examination of data entries and manual editing to ensure the completeness, consistency, and correctness of entries before data encoding. This is also called the data review process. Checks for completeness and consistency of data which should be considered during manual editing are provided in the Manual of Operations for Statistical Researchers.
Data Appraisal
The estimates generated from the clean MPCSR data are reviewed at the provincial level before submitting to the Central Office. At the Central Office, the estimates are subjected to review and validation.
Data access
Name | Affiliation | URI | |
---|---|---|---|
National Statistician | Philippine Statistics Authority (PSA) | info@psa.gov.ph | www.psa.gov.ph |
Disclaimer and copyrights
(c) 2016, Philippine Statistics Authority
contacts
Name | Affiliation | URI | |
---|---|---|---|
Crops Statistics Division (CSD) | Philippine Statistics Authority (PSA) | csd.staff@psa.gov.ph | www.psa.gov.ph |
Knowledge Management and Communication Division (KMCD) | Philippine Statistics Authority (PSA) | info@psa.gov.ph | www.psa.gov.ph |