The Philippine Statistics Authority (PSA) – La Union Provincial Statistical Office conducts the 4^th Quarter 2023 Crops Production Survey (CrPS) from 16 to 30 November 2023 in various households and establishments across the province. The survey aims to gather comprehensive data on the production of crops other than palay and corn, providing valuable insights for agricultural development and policy formulation.

The CrPS will collect data on three key aspects of crop production: production volume, area planted and harvested, and the number of bearing trees, hills, or vines. The survey covers a wide range of crops, categorized into three commodity groupings: Vegetables and Root Crops, Fruit Crops, and Non-food and Industrial Crops.

The data gathered from the CrPS will serve as crucial inputs for the Performance of Agricultural Report (PAR) and the calculation of the Gross Domestic Product (GDP). This information will inform planners, policy and decision makers, administrators, and other agriculture stakeholders, including the National Economic Development Authority (NEDA), the Department of Agriculture (DA), the Bureau of Plant Industry (BPI), and the Philippine Council for Agriculture and Fisheries (PCAF), in developing effective plans, policies, and programs for the agricultural sector.

PSA-La Union hired and trained 10 Statistical Researchers (SRs) who will visit 143 sample barangays throughout the province, covering 850 households and six establishments. The SRs will work closely with the Local Government Units (LGUs) to ensure the smooth and efficient conduct of the survey. PSA-La Union strongly encourages the support and cooperation of LGUs and sample respondents in this important undertaking.

PSA-La Union assures the public that all data collected during the survey will be treated with strict confidentiality as mandated by Republic Act 10625. The information gathered will be used solely for statistical purposes and will not be shared with any unauthorized individuals or entities.

SGD. DANITES E. TEÑIDO, PhD 
Chief Statistical Specialist

MAQ/MFC