Survey on Costs and Returns of Palay Production 2022
Philippines, 2022 - 2023
Reference ID
PHL-PSA-SCR-2022-V2.0
Producer(s)
Philippine Statistics Authority
Collection(s)
Metadata
Created on
Jan 19, 2024
Last modified
Jan 19, 2024
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Identification
Survey on Costs and Returns of Palay Production 2022
Name | Abbreviation |
---|---|
Philippines | PHL |
PHL-PSA-SCR-2022-V2.0
The SCR of palay production generates data on the cost structure of palay production, and average use of materials and labor inputs, measures of profitability, and other socio-economic characteristics of palay farming in the country. It also serves as benchmark data which are needed in the annual updating of the database on costs and returns of palay production.
The general objective of the survey is to generate data on costs and returns of producing palay. Specifically, the survey aims to:
· establish an up-to-date production costs structure;
· determine indicators of profitability such as gross and net returns, returns above cash costs, returns above variable costs, etc.;
· come up with benchmark/updated data sets on average use of material and labor inputs; and,
· generate other related socio-economic variables.
Data on production costs and returns has been gaining more attention because of its varied uses and applications for policy analysts, national accounts compilers, farmers, and other entrepreneurs in the agriculture sector.
For palay farmers, data on production costs and returns can serve as a basis for their planning and programming activities. They can use this data in selecting the most profitable set of crops to plant during a particular season.
For both government and non-government planners and policymakers, data on production costs and returns can be used in designing appropriate programs and projects to boost the growth and development of the palay industry. Also, other important applications of data on production costs and returns are in the financial and insurance markets. In particular, financial institutions require feasibility studies in every investment portfolio. Doing a feasibility study needs data on production costs and returns. On the other hand, this data can serve as a solid basis in determining appropriate insurance premium rates.
The general objective of the survey is to generate data on costs and returns of producing palay. Specifically, the survey aims to:
· establish an up-to-date production costs structure;
· determine indicators of profitability such as gross and net returns, returns above cash costs, returns above variable costs, etc.;
· come up with benchmark/updated data sets on average use of material and labor inputs; and,
· generate other related socio-economic variables.
Data on production costs and returns has been gaining more attention because of its varied uses and applications for policy analysts, national accounts compilers, farmers, and other entrepreneurs in the agriculture sector.
For palay farmers, data on production costs and returns can serve as a basis for their planning and programming activities. They can use this data in selecting the most profitable set of crops to plant during a particular season.
For both government and non-government planners and policymakers, data on production costs and returns can be used in designing appropriate programs and projects to boost the growth and development of the palay industry. Also, other important applications of data on production costs and returns are in the financial and insurance markets. In particular, financial institutions require feasibility studies in every investment portfolio. Doing a feasibility study needs data on production costs and returns. On the other hand, this data can serve as a solid basis in determining appropriate insurance premium rates.
Sample survey data [ssd]
Palay farming households with harvests during the reference period from the list of samples in the 2022 PPS.
Version
Version 2.0 - This version includes datasets documentation
2024-01
Scope
Topic | Vocabulary | URI |
---|---|---|
Agriculture, forestry, fisheries | Philippine Statistics Authority |
Coverage
All palay producing (81) provinces nationwide excluding NCR.
Palay farming households with harvests during the reference period from the list of samples in the 2022 PPS.
The list of samples from the 2022 Palay Production Survey (PPS) serves as the sampling frame in the selection of palay farming households who harvested palay.
Producers and sponsors
Name | Abbreviation | Role |
---|---|---|
Department of Agriculture - Bureau of Agricultural Research | DA-BAR |
Sampling
The domain of the survey is the province. The SCR employs a one-stage sampling with a selection of palay farming households that harvested palay from the list of samples of the 2022 PPS. The PPS on the other hand employs a two-stage sampling design with palay producing barangay as the primary sampling unit (PSU) and palay farming household as the secondary sampling unit (SSU). Since the sampling frame of SCR is also a survey, the sampling weights of PPS were considered in the estimation of final weights for the SCR, which is further discussed in this section.
Sample Size Determination
Fifty (50) percent of the total samples from the first quarter of 2021 PPS per province is the sample size of the SCR.
Sample Allocation
If the number of palay farming households that harvested palay is less than the target sample size in a province, all the palay farming households with harvest in the province are selected. Otherwise, the following allocation of samples is used:
-All palay farming households that harvested palay in each sample barangay were selected if the number of palay farming households with harvest is less than or equal to ten (10).
-Ten (10) palay farming households that harvested palay per sample barangay were selected if the number of palay farming households with harvest is greater than ten (10).
Sample Selection
Palay farming households with harvest during the reference period from the list of samples in the 2022 PPS are selected using simple random sampling.
Sample Size Determination
Fifty (50) percent of the total samples from the first quarter of 2021 PPS per province is the sample size of the SCR.
Sample Allocation
If the number of palay farming households that harvested palay is less than the target sample size in a province, all the palay farming households with harvest in the province are selected. Otherwise, the following allocation of samples is used:
-All palay farming households that harvested palay in each sample barangay were selected if the number of palay farming households with harvest is less than or equal to ten (10).
-Ten (10) palay farming households that harvested palay per sample barangay were selected if the number of palay farming households with harvest is greater than ten (10).
Sample Selection
Palay farming households with harvest during the reference period from the list of samples in the 2022 PPS are selected using simple random sampling.
For the July 2022 survey round the response rate was 96.4 percent while for the January 2023 round, it was 97.2 percent.
Refer to page 5 (Survey Weights) of the 2022 SCR of Palay Production Manual of Operations for the detailed survey weights calculation.
Data Collection
Start | End | Cycle |
---|---|---|
2022-07-18 | 2022-08-12 | First Round |
2023-02-06 | 2023-02-17 | Second Round |
Start | End | Cycle |
---|---|---|
2022-01-02 | 2020-06-30 | July Round |
2022-07-01 | 2022-12-30 | January Round |
Face-to-face [f2f]
The selected staff from Regional Statistical Services Offices (RSSOs), Provincial Statistical Offices (PSOs), and Central Office (CO) served as the field supervisors. They ensured that the field data collection ran smoothly and within the set schedule. These assigned personnel were tasked to do the following: observe the hired SRs, make follow-ups, spot-check the hired SRs, edit the completed questionnaires, and back-check the work of the hired SRs. All these activities were intended to ensure the quality of data that were collected.
The questionnaire was structured and written in English. It was designed in tabular form and some in question type format. The data items/variables in the questionnaire were based on the previous questionnaires with some modifications and additions.
The questionnaire was pre-tested in Nueva Ecija and Iloilo. The survey including the questionnaire undergone Statistical Survey Review and Clearance System (SSRCS) before implementation.
The questionnaire consisted of 13 pages covering 15 blocks as follows:
A. Geographic Information
- This block collected information on the geographic location where the sample palay farm is located.
B. Sample Identification
- This block gathered the demographic characteristics of the sample farmer.
C. Basic Characteristics of the Farm
- This block collected about the palay farm/s operated by the sample farmer i.e., number of farm parcels operated, area planted and harvested, month planted/harvested, tenurial status of the focus parcel, type of seeds planted, seed variety, and its sources.
D. Farm Investments
- This block captured information on all investment items owned and used/utilized by the sample farmer in palay production during the last completed harvest within the reference period.
E. Material Inputs
- This block gathered information on the usage and costs of material inputs (quantity, mode of acquisition of seeds/planting materials, fertilizers, soil ameliorants, foliar, and pesticides) of the sample farmer in his/her palay production during the last completed harvest within the reference period.
F. Labor Inputs
- This block gathered information pertaining to labor utilization in the production of palay during the reference period. It has integrated gender concerns, thus, the need to determine whether labor inputs were provided by Male or Female farm workers. The sources of labor are operator, family, exchange labor (bayanihan), and hired labor. The latter may include permanent workers, contract labor, or a “pakyaw” system wherein the performance of multiple farming activities is contracted for a certain amount.
G. Other Production Costs
- This block gathered other items of production costs incurred on the focus parcel during the reference period. Payments may be cash or non-cash. In case of non-cash payments or payments in kind, convert the total value of goods to a cash equivalent. Examples of other production costs are land tax, land/lease rental, rentals of machines, animals, tools and equipment, rental value of owned land/animal, fuel and oil, transport cost of inputs, interest payment on crop loan, electricity cost, landowner's share, sacks (per cropping), tying materials/need (per cropping), etc.
H. Production and Disposition
- This block gathered information on the gross volume of palay harvest in the focus parcels during the last completed cropping period (January to June 2022 for First Round and July to December 2022 for Second Round) as well as the breakdown by which this harvested volume was disposed (i.e. sold/to be sold, harvester's share, thresher's share, other laborer's share, landowner's share, land/lease rental, for home consumption, given away, paid to creditor, used / to be used for seeds/feeds, etc.).
I. Production Related Information
- This block gathered information on the problems affecting palay production in focus parcels during the reference period.
J. Marketing Related Information
-This block gathered information on the problems encountered in marketing palay during the reference period.
K. Access To Credit
-This block gathered information on access to credit of the sample farmer/operator for use in palay production during the reference period (in cash or in kind).
L. Farmer's Participation in Palay Program
-This block collected information on the farmer's participation in the palay program and projects.
M. Other Information
- This block gathered information relative to the perceived effect of climate change on palay production and the sample farmer/operator's membership in any farmers' organization and benefits they received from the organization.
N. Plans and Recommendations
- This block compiled the plans and recommendations of the sample farmer for the improvement of his/her palay production.
O. Interview/Survey Particulars
- This block contained the names and signatures of the Statistical Researcher (SR), and the Provincial Focal Person (PFP).
Refer to page 33 (Chapter 6. Instructions in Accomplishing SCR Forms) of the 2022 SCR of Palay Production Manual of Operations for detailed information.
The questionnaire was pre-tested in Nueva Ecija and Iloilo. The survey including the questionnaire undergone Statistical Survey Review and Clearance System (SSRCS) before implementation.
The questionnaire consisted of 13 pages covering 15 blocks as follows:
A. Geographic Information
- This block collected information on the geographic location where the sample palay farm is located.
B. Sample Identification
- This block gathered the demographic characteristics of the sample farmer.
C. Basic Characteristics of the Farm
- This block collected about the palay farm/s operated by the sample farmer i.e., number of farm parcels operated, area planted and harvested, month planted/harvested, tenurial status of the focus parcel, type of seeds planted, seed variety, and its sources.
D. Farm Investments
- This block captured information on all investment items owned and used/utilized by the sample farmer in palay production during the last completed harvest within the reference period.
E. Material Inputs
- This block gathered information on the usage and costs of material inputs (quantity, mode of acquisition of seeds/planting materials, fertilizers, soil ameliorants, foliar, and pesticides) of the sample farmer in his/her palay production during the last completed harvest within the reference period.
F. Labor Inputs
- This block gathered information pertaining to labor utilization in the production of palay during the reference period. It has integrated gender concerns, thus, the need to determine whether labor inputs were provided by Male or Female farm workers. The sources of labor are operator, family, exchange labor (bayanihan), and hired labor. The latter may include permanent workers, contract labor, or a “pakyaw” system wherein the performance of multiple farming activities is contracted for a certain amount.
G. Other Production Costs
- This block gathered other items of production costs incurred on the focus parcel during the reference period. Payments may be cash or non-cash. In case of non-cash payments or payments in kind, convert the total value of goods to a cash equivalent. Examples of other production costs are land tax, land/lease rental, rentals of machines, animals, tools and equipment, rental value of owned land/animal, fuel and oil, transport cost of inputs, interest payment on crop loan, electricity cost, landowner's share, sacks (per cropping), tying materials/need (per cropping), etc.
H. Production and Disposition
- This block gathered information on the gross volume of palay harvest in the focus parcels during the last completed cropping period (January to June 2022 for First Round and July to December 2022 for Second Round) as well as the breakdown by which this harvested volume was disposed (i.e. sold/to be sold, harvester's share, thresher's share, other laborer's share, landowner's share, land/lease rental, for home consumption, given away, paid to creditor, used / to be used for seeds/feeds, etc.).
I. Production Related Information
- This block gathered information on the problems affecting palay production in focus parcels during the reference period.
J. Marketing Related Information
-This block gathered information on the problems encountered in marketing palay during the reference period.
K. Access To Credit
-This block gathered information on access to credit of the sample farmer/operator for use in palay production during the reference period (in cash or in kind).
L. Farmer's Participation in Palay Program
-This block collected information on the farmer's participation in the palay program and projects.
M. Other Information
- This block gathered information relative to the perceived effect of climate change on palay production and the sample farmer/operator's membership in any farmers' organization and benefits they received from the organization.
N. Plans and Recommendations
- This block compiled the plans and recommendations of the sample farmer for the improvement of his/her palay production.
O. Interview/Survey Particulars
- This block contained the names and signatures of the Statistical Researcher (SR), and the Provincial Focal Person (PFP).
Refer to page 33 (Chapter 6. Instructions in Accomplishing SCR Forms) of the 2022 SCR of Palay Production Manual of Operations for detailed information.
Name | Abbreviation | Affiliation |
---|---|---|
Philippine Statistics Authority | PSA | National Economic and Development Authority (NEDA) |
Data Processing
Editing and coding of survey returns were done at the PSOs upon submission of the accomplished questionnaires by the SRs. The PSO staff served as editors.
Refer to the 2022 SCR of Palay Production Manual of Operation for more information.
Refer to the 2022 SCR of Palay Production Manual of Operation for more information.
Data access
Name | Affiliation | URI | |
---|---|---|---|
National Statistician | Philippine Statistics Authority | info@psa.gov.ph | www.psa.gov.ph |
Authorization to use this data is granted only to the client or data user and persons within its organization, if applicable. Under no circumstances shall the client reproduce, distribute, sell or lend the entire data or parts thereof to any other data user apart from himself or that of authorized employees in his organization. The PSA shall hold the data user fully responsible for safeguarding the data from any unauthorized access or use.
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the PSA.
2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified in the dataset.
3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately reported to the PSA.
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the PSA.
2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified in the dataset.
3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately reported to the PSA.
Philippine Statistics Authority, Survey on Costs and Returns of Palay Production 2022, Version 2.0, provided by the PSA Data Archive. www.psada.psa.gov.ph
Disclaimer and copyrights
The data users/researchers acknowledge that the PSA and DA-BAR 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.
(c) 2023, Philippine Statistics Authority
contacts
Name | Affiliation | URI | |
---|---|---|---|
Agricultural Accounts Division | Philippine Statistics Authority | aad.staff@psa.gov.ph | www.psa.gov.ph |
Registers and Database Management Division | Philippine Statistics Authority | rdmd.staff@psa.gov.ph | www.psa.gov.ph |
Knowledge Management and Communications Division | Philippine Statistics Authority | kmcd.staff@psa.gov.ph | www.psa.gov.ph |