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1704101PublishedVol 6 · Issue 8

Forecasting Monthly Prices of Selected Fish Commodities in National Capital Region in the Philippines through ARIMA Modeling

Judy Ann M. Ibarra Cheldee Kimberly P. Sumo Patrice C. Valdra

Subject area: Management and Commerce  ·  Area of research: Business and Management

Abstract

The researchers aim to analyze the behavior of the prices of selected fish commodities in National Capital Region like bangus (milkfish), tilapia (cichlid fish), galunggong (blue mackerel scad), alumahan (long-jawed mackerel), tambakol (yellowfin tuna), dalagangbukid (mountain maiden), alimasag (crab), pusit (squid), hipon (shrimp) and lato (sea grapes) from data gathered for the years 2016-2022. A total of 84 observations and 10 variables are used in this research. The data were gathered from the Bureau of Fisheries and Aquatic Resources. This study used an application of EVIEWS to forecast prices of these selected fish commodities from 2023-2027 using the ARIMA model (Autoregressive Integrated Moving Average). The researchers followed a research paradigm to be applied to the data to come up with the expected output. The study showed the best ARIMA models for bangus ARIMA (1,1,1), tilapia ARIMA (1,1,1) galunggong ARIMA(1,1,1), alumahan ARIMA (1,1,1), tambakolARIMA(1,2,1), dalagangbukid ARIMA (8,1,8), alimasag ARIMA (6,1,6), pusit ARIMA (12,1,12), hipon ARIMA (1,1,1), and lato ARIMA (3,1,3). This study will be of importance in assessing future prices that affect the economy.

Keywords

ARIMA, EViews, Fishery, Forecasting, Prices

How to cite this paper

Judy Ann M. Ibarra, Cheldee Kimberly P. Sumo, Patrice C. Valdra "Forecasting Monthly Prices of Selected Fish Commodities in National Capital Region in the Philippines through ARIMA Modeling" Iconic Research And Engineering Journals Volume 6 Issue 8 2023 Page 120-129
Judy Ann M. Ibarra, Cheldee Kimberly P. Sumo, Patrice C. Valdra "Forecasting Monthly Prices of Selected Fish Commodities in National Capital Region in the Philippines through ARIMA Modeling" Iconic Research And Engineering Journals, vol. 6, no. 8, Feb. 2023
Judy Ann M. Ibarra, Cheldee Kimberly P. Sumo, Patrice C. Valdra (2023). Forecasting Monthly Prices of Selected Fish Commodities in National Capital Region in the Philippines through ARIMA Modeling. Iconic Research And Engineering Journals, 6(8).
Judy Ann M. Ibarra, Cheldee Kimberly P. Sumo, Patrice C. Valdra "Forecasting Monthly Prices of Selected Fish Commodities in National Capital Region in the Philippines through ARIMA Modeling" Iconic Research And Engineering Journals, vol. 6, no. 8, Feb. 2023.
@article{1704101,
      author = {Judy Ann M. Ibarra, Cheldee Kimberly P. Sumo, Patrice C. Valdra},
      title = {Forecasting Monthly Prices of Selected Fish Commodities in National Capital Region in the Philippines through ARIMA Modeling},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {8},
      pages = {120-129},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1704101.pdf},
      abstract = {The researchers aim to analyze the behavior of the prices of selected fish commodities in National Capital Region like bangus (milkfish), tilapia (cichlid fish), galunggong (blue mackerel scad), alumahan (long-jawed mackerel), tambakol (yellowfin tuna), dalagangbukid (mountain maiden), alimasag (crab), pusit (squid), hipon (shrimp) and lato (sea grapes) from data gathered for the years 2016-2022. A total of 84 observations and 10 variables are used in this research. The data were gathered from the Bureau of Fisheries and Aquatic Resources. This study used an application of EVIEWS to forecast prices of these selected fish commodities from 2023-2027 using the ARIMA model (Autoregressive Integrated Moving Average). The researchers followed a research paradigm to be applied to the data to come up with the expected output. The study showed the best ARIMA models for bangus ARIMA (1,1,1), tilapia ARIMA (1,1,1) galunggong ARIMA(1,1,1), alumahan ARIMA (1,1,1), tambakolARIMA(1,2,1), dalagangbukid ARIMA (8,1,8), alimasag ARIMA (6,1,6), pusit ARIMA (12,1,12), hipon ARIMA (1,1,1), and lato ARIMA (3,1,3). This study will be of importance in assessing future prices that affect the economy.},
      keywords = {ARIMA, EViews, Fishery, Forecasting, Prices},
      month = {February},
  }