Agricultural Wage Rate Survey 2019
Philippines, 2019 - 2020
Reference ID
PHL-PSA-AWRS-2019-V2.0
Producer(s)
Philippine Statistics Authority (PSA)
Collection(s)
Metadata
Created on
Feb 22, 2024
Last modified
Feb 22, 2024
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Identification
Agricultural Wage Rate Survey 2019
Name | Abbreviation |
---|---|
Philippines | PHL |
PHL-PSA-AWRS-2019-V2.0
This survey aims to generate estimates of average wage rates of agricultural farm workers, specifically for the four major crops: palay, corn, coconut, and sugarcane. This is to establish basis for computing the average wage rate in agriculture and subsequently, a composite wage rate index for agriculture. Specifically, the survey aims to:
· determine the national and regional averages and variations on wage rates by type of labor (i.e., man labor, man-animal and man-machine) for the different farm operations;
· generate gender-based data for wage rates; and,
· determine the extent of women's participation in agricultural production activities.
· determine the national and regional averages and variations on wage rates by type of labor (i.e., man labor, man-animal and man-machine) for the different farm operations;
· generate gender-based data for wage rates; and,
· determine the extent of women's participation in agricultural production activities.
Sample Survey Data [SSD]
Sample households that hired farm workers within the reference period and knowledgeable on the farm activities of palay, corn, coconut, and sugarcane were the unit of analysis of the survey.
Version
V2: Final dataset
2020-10-19
Scope
Topic | Vocabulary | URI |
---|---|---|
Labor cost | Philippine Statistics Authority | |
Labor utilization | Philippine Statistics Authority |
Coverage
National and Regional - covering producing provinces of the four crops. Data collection for AWRS palay includes all provinces (except Batanes,Davao Occidental and Sulu), 51 provinces for corn, 46 provinces for coconut and 19 provinces for sugarcane. AWRS palay and corn excludes Batanes since the province is not covered in the Palay and Corn Production Survey (PCPS) given that AWRS utilizes the samples of PCPS. In the case of Sulu, there were reports that palay farmers did not employ hired laborers in palay farming activity.
Sample households that hired farm workers within the reference period and knowledgeable on the farm activities of palay, corn, coconut, and sugarcane were the unit of analysis of the survey.
Filipino farmers of Palay, Corn, Coconut, and Sugarcane who had a complete cropping cycle within the reference period.
Producers and sponsors
Name | Abbreviation | Role |
---|---|---|
Government of the Philippines | GOP | Full Funding |
Sampling
A. Sampling Frame
For palay and corn, Agricultural Wage Rate Survey (AWRS) uses the Palay and Corn Production Survey (PCPS) as the sampling frame. For coconut and sugarcane, the lists of farm operators are generated by the Provincial Statistics Offices (PSOs) based on the available data and interview of Key Informants.
B. Sampling Design, Statistical Unit and Sample Size
AWRS employs quota sampling design. The statistical unit is the household that hired farm workers during the reference period. For palay and corn, sample sizes are set at 20 for major producing provinces and 15 for minor producing provinces. For coconut and sugarcane, sample sizes are set at 15 based from the Philippine Coconut Authority (PCA) and Sugar Regulatory Administration (SRA), respectively.
In case the number of samples in the list is less than the quota (15 or 20), it should be updated by selecting additional samples. The procedures in selecting the additional sample households are listed below:
1. For palay and corn, look for other PCPS sample households within the same barangay that hired farm workers during the reference period;
2. If none, consider sample households in other PCPS sample barangays;
3. If the PCPS samples are exhausted and none of the households hired farm workers during the reference period, look for non-PCPS barangays and select additional sample households that hired farm workers to complete the quota of 15 or 20 households for the province;
4. For coconut and sugarcane, the additional samples are identified purposively.
For palay and corn, Agricultural Wage Rate Survey (AWRS) uses the Palay and Corn Production Survey (PCPS) as the sampling frame. For coconut and sugarcane, the lists of farm operators are generated by the Provincial Statistics Offices (PSOs) based on the available data and interview of Key Informants.
B. Sampling Design, Statistical Unit and Sample Size
AWRS employs quota sampling design. The statistical unit is the household that hired farm workers during the reference period. For palay and corn, sample sizes are set at 20 for major producing provinces and 15 for minor producing provinces. For coconut and sugarcane, sample sizes are set at 15 based from the Philippine Coconut Authority (PCA) and Sugar Regulatory Administration (SRA), respectively.
In case the number of samples in the list is less than the quota (15 or 20), it should be updated by selecting additional samples. The procedures in selecting the additional sample households are listed below:
1. For palay and corn, look for other PCPS sample households within the same barangay that hired farm workers during the reference period;
2. If none, consider sample households in other PCPS sample barangays;
3. If the PCPS samples are exhausted and none of the households hired farm workers during the reference period, look for non-PCPS barangays and select additional sample households that hired farm workers to complete the quota of 15 or 20 households for the province;
4. For coconut and sugarcane, the additional samples are identified purposively.
Data Collection
Start | End | Cycle |
---|---|---|
2019-07-08 | 2019-07-19 | Last completed cropping cycle for Palay and Corn 1st Semester |
2020-01-14 | 2020-01-31 | Last completed cropping cycle for Palay and Corn 2nd Semester |
2020-01-14 | 2020-01-31 | Last completed cropping cycle for Coconut and Sugarcane Annual |
Start | End | Cycle |
---|---|---|
2019-01-01 | 2019-06-30 | January -June of the Current year for Palay & Corn |
2019-07-01 | 2019-12-31 | July-December of the previous year for Palay and Corn |
2019-01-01 | 2019-12-31 | January -December of the previous Year for Coconut & Sugarcane |
Face-to-face [f2f]
The Regional Statistical Service Office (RSSO) and Provincial Statistical Office (PSO) Staff serve as supervisors and ensure that the field operations run smoothly and within schedule. The responsibilities of the PSO Staff include the following:
1. Conduct orientation/training
2. Determine the workload of the SRs under his/her supervision
3. Conduct spot-checking
4. Address problems and gray areas reported by the SRs
5. Monitor the progress of SRs' work
6. Perform editing of survey returns
7. Conduct back-checking
8. Prepare field supervision report
1. Conduct orientation/training
2. Determine the workload of the SRs under his/her supervision
3. Conduct spot-checking
4. Address problems and gray areas reported by the SRs
5. Monitor the progress of SRs' work
6. Perform editing of survey returns
7. Conduct back-checking
8. Prepare field supervision report
Each of the four questionnaires used in AWRS was structured and written in English. These were designed in tabular form and some in question type format. The questionnaire for commodities such as palay, corn, coconut, and sugarcane consisted of six pages that collects information on the farm information of the sample household, employment and wages paid by activity, by sex, by type of labor used and the bases of payment.
These questionnaires were basically the same except for specific information on farm characteristics. For example, Palay Questionnaire asked for the ecosystem, Corn Questionnaire asked for crop type while Coconut and Sugarcane Questionnaires asked for the area planted and harvested only. In terms of production, the Corn Questionnaire asked for the quantity of shelled corn and green corn produced within the reference period. In the Coconut Questionnaire, three types of production were asked namely, copra, matured and green nut (young coconut). Meanwhile, Palay and Sugarcane Questionnaires had no other form of production.
For the question pertaining to Employment and Wages Paid by Sex (Item 4.0 in the questionnaires), only the applicable farm activities relative to the commodities were indicated in each questionnaire. Although there were same farm activities being conducted across the four commodities, distinct farm activities were prioritized and sorted based on the hierarchy of the activity respective to the commodity.
Refer to related materials AWRS Questionnaires.
These questionnaires were basically the same except for specific information on farm characteristics. For example, Palay Questionnaire asked for the ecosystem, Corn Questionnaire asked for crop type while Coconut and Sugarcane Questionnaires asked for the area planted and harvested only. In terms of production, the Corn Questionnaire asked for the quantity of shelled corn and green corn produced within the reference period. In the Coconut Questionnaire, three types of production were asked namely, copra, matured and green nut (young coconut). Meanwhile, Palay and Sugarcane Questionnaires had no other form of production.
For the question pertaining to Employment and Wages Paid by Sex (Item 4.0 in the questionnaires), only the applicable farm activities relative to the commodities were indicated in each questionnaire. Although there were same farm activities being conducted across the four commodities, distinct farm activities were prioritized and sorted based on the hierarchy of the activity respective to the commodity.
Refer to related materials AWRS Questionnaires.
Name | Abbreviation | Affiliation |
---|---|---|
Philippine Statistics Authority | PSA | National Economic and Development Authority |
Data Processing
The editing and coding manual for AWRS covers general and specific instructions that serve as guide to the field supervisors in checking the completeness, consistency and acceptability of data items in the accomplished questionnaires.
It is highly recommended that these guidelines must be READ and STRICTLY followed in order to improve the quality of data that enter into the computerized processing system.
Refer to related materials AWRS Editing and Coding Guidelines for more information.
It is highly recommended that these guidelines must be READ and STRICTLY followed in order to improve the quality of data that enter into the computerized processing system.
Refer to related materials AWRS Editing and Coding Guidelines for more information.
Data access
Name | Affiliation | URI | |
---|---|---|---|
National Statistician | Philippine Statistics Authority | info@psa.gov.ph | www.psa.gpv.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 be 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 be reported to the PSA.
Philippine Statistics Authority, Agricultural Wage Rate Survey 2019 (AWRS 2019), Version 2.0 (October 2020), provided by the PSA Data Archive. www.psa.gov.ph/psada
Disclaimer and copyrights
The data users/researchers acknowledge that the PSA 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.
(c) 2019, Philippine Statistics Authority
contacts
Name | Affiliation | URI | |
---|---|---|---|
Agricultural Accounts Division | Philippne Statistics Authority | aad.staff@psa.gov.ph | psa.gov.ph |
Knowledge Management and Communication Division | Philippne Statistics Authority | info@psa.gov.ph | psa.gov.ph |
Registers and Database Management Division | Philippne Statistics Authority | rdmd.staff@psa.gov.ph | psa.gov.ph |