The average domestic wholesale price of bangus or milkfish in the Philippines amounted to about 156.15 Philippine pesos per kilogram in 2024, down from the previous year. The wholesale price of bangus fluctuated increased since 2018.

In 2023, the average domestic retail price of bangus or milkfish in the Philippines was approximately ****** Philippine pesos per kilogram, an increase of over ** Philippine pesos from the previous year. The retail price of bangus has overall increased over the past decade. Milkfish is among the most expensive type of fish in the Philippines, with tulingan or frigate tuna being the most expensive fish type.

Philippines Retail Price: Bangus: CAR: Baguio City data was reported at 160.000 PHP/kg in 09 Nov 2018. This records a decrease from the previous number of 180.000 PHP/kg for 02 Nov 2018. Philippines Retail Price: Bangus: CAR: Baguio City data is updated weekly, averaging 120.000 PHP/kg from Dec 2013 (Median) to 09 Nov 2018, with 254 observations. The data reached an all-time high of 180.000 PHP/kg in 02 Nov 2018 and a record low of 100.000 PHP/kg in 12 Dec 2014. Philippines Retail Price: Bangus: CAR: Baguio City data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.P001: Retail Price: Selected Agricultural Commodities.

Philippines Retail Price: Bangus: Region 10: Cagayan de Oro City data was reported at 160.000 PHP/kg in 13 Jul 2018. This stayed constant from the previous number of 160.000 PHP/kg for 06 Jul 2018. Philippines Retail Price: Bangus: Region 10: Cagayan de Oro City data is updated weekly, averaging 130.000 PHP/kg from Dec 2013 (Median) to 13 Jul 2018, with 236 observations. The data reached an all-time high of 160.000 PHP/kg in 13 Jul 2018 and a record low of 120.000 PHP/kg in 07 Nov 2014. Philippines Retail Price: Bangus: Region 10: Cagayan de Oro City data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.P001: Retail Price: Selected Agricultural Commodities.

Philippines Retail Price: Bangus: Region 11: Davao City data was reported at 160.000 PHP/kg in 09 Nov 2018. This records a decrease from the previous number of 170.000 PHP/kg for 02 Nov 2018. Philippines Retail Price: Bangus: Region 11: Davao City data is updated weekly, averaging 120.000 PHP/kg from Dec 2013 (Median) to 09 Nov 2018, with 254 observations. The data reached an all-time high of 170.000 PHP/kg in 02 Nov 2018 and a record low of 100.000 PHP/kg in 28 Oct 2016. Philippines Retail Price: Bangus: Region 11: Davao City data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.P001: Retail Price: Selected Agricultural Commodities.

Philippines Retail Price: Bangus: Region 2: Tuguegarao City data was reported at 160.000 PHP/kg in 13 Jul 2018. This stayed constant from the previous number of 160.000 PHP/kg for 06 Jul 2018. Philippines Retail Price: Bangus: Region 2: Tuguegarao City data is updated weekly, averaging 130.000 PHP/kg from Dec 2013 (Median) to 13 Jul 2018, with 237 observations. The data reached an all-time high of 170.000 PHP/kg in 31 Jan 2014 and a record low of 110.000 PHP/kg in 21 Mar 2014. Philippines Retail Price: Bangus: Region 2: Tuguegarao City data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.P001: Retail Price: Selected Agricultural Commodities.

Abstract

The viability of any agricultural endeavor is one of the main concerns of planners and policy makers in the agricultural and fishery sector. In support of this concern, goals and strategies are geared towards increasing productivity and profitability. Thus, there is a need for adequate and relevant marketing information which would include marketing structure, cost and margins, prices and other marketing-related information.

The Bureau of Agricultural Statistics (BAS) recognizes the need for such marketing information and has incorporated the generation of such in its data system. While data on prices has been regularly-generated, the other marketing information are collected periodically. These are limited to selected types of crop, livestock and fishery commodities.

The main objective of the study is to determine the marketing structure of milkfish. Specifically, it aims to: 1) Identify the key players in the milkfish industry, 2) Determine the components of marketing costs of milkfish by type of marketing participants, 3) Determine the marketing practices of milkfish operators and traders, 4) Determine the flow of commodities and channels of distribution; and 5) Compare marketing costs across trading centers.

Geographic coverage

Regional Coverage

Analysis unit

Individuals

Universe

All marketing costs of milkfish farm operators and traders.

Kind of data

Sample survey data [ssd]

Sampling procedure

The study covered four (4) major milkfish supply areas and five (5) demand areas. For supply areas, the provinces covered were Pangasinan, Bulacan, Capiz and Iloilo, while demand areas included Baguio City, Isabela, Pampanga, Aklan, and Metro Manila. Supply provinces were chosen based on their significant contribution to the total milkfish production in the country. On the average, these provinces accounted for 44% of the country's milkfish production during the last five (5) years. Demand provinces, however, were identified as the distribution and consumption areas of milkfish produced from the supply provinces. These provinces were identified during the interview phase in the supply areas.

The selection of sample milkfish farm operators and traders was guided by the following procedures:

a) Milkfish Farm Operators: From the identified milkfish farm operators taken from the Costs and Returns Survey (CRS), the research team purposively selected 20 sample farm operators who have undertaken pre-marketing activities prior to the marketing of milkfish. These pre-marketing activities include hauling, sorting, chilling, packing, etc. that were done by the operator before selling the commodity. Selection of the 20 sample farm operators was done either by equally distributing the samples among the sample producing barangays or by distributing the samples among the top producing barangays only.

However, if the sample respondents from the CRS have not identified milkfish farm operators who had undertaken pre-marketing activities, the 20 sample farm operators were chosen from the top two (2) producing barangays within the top two (2) producing municipalities identified by the traders in each province. Five (5) respondents were chosen in each barangay or a total of 20 respondents.

b) Traders: Adopting the snowball sampling techniques, the team interviewed traders identified by sample farm operators as buyers of milkfish. The traders interviewed were asked to whom and where they sell the milkfish they procured so that the interviewee has the information for the next traders to be interviewed or the destination of the commodity. This approach accumulates the data gathered from one trader respondent to other respondents at different levels of commodity marketing system.

A minimum of three (3) and maximum of five (5) respondents per type of marketing participants were interviewed per trading site.

For additional information relevant to the study, the research team also interviewed other key players knowledgeable to the marketing structure of milkfish. This is an addition to the information taken from the previous interview.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Data editing was done at various stages: a) Right after data collection to check the completeness and consistencies of entries; b) During data processing c) After the consolidation and generation of output tables

The data were processed manually by four (4) staff at the Central Office. The processors were tasked to edit and process all the entries on the questionnaires for the supply and demand areas assigned to them.

Each processor was provided with two separate tabulation worksheets, one for the operators and the other for traders. These tabulation worksheets were designed according to the contents of the questionnaires which include the profile or socio-economic characteristics of the respondents, the production and marketing practices in case of the operators, marketing practices of the traders and the components of marketing costs such as labor, transportation, supplies and materials and other operating expenses.

Frequency counts and percentages were determined for the profile and marketing procatices of the respondents. For marketing costs, average cost per kilogram for each item, per activity and per type of marketing participants were estimated for each supply and demand area.

After all the data were processed, these were consolidated and entered to the output tables in Microsoft Excel formats.

Since data processing was done manually without using any software, microdata are not available for public access.

Data appraisal

The data presented in the output tables were reviewed and compared across areas covered by the study. Data analysis and report preparation were done accordingly.