Time Series Forecasting Using Holt-Winters Exponential Smoothing: Application to Abaca Fiber Data

Mary Cris F. Pleños

Problems of World Agriculture / Problemy Rolnictwa Światowego, 2022, vol. 22, issue 2

Abstract: This study utilized the data on abaca fiber production and used Holt-Winters model to forecast the abaca fiber production since the studied variable is characterized by a fairly strong intensity of seasonality. For the construction of forecasts, additive and multiplicative models were used. The most accurate forecasts were selected on the basis of Mean Square Error, Root Mean Square Error, Mean Absolute Percentage Error, and Mean Absolute Scaled Error. It was found that the multiplicative method had a higher accuracy, hence it was utilized to forecast the production for the next three years. According to the findings, the anticipated fiber production for 2021-2023 showed an increase up to the second quarter, but then declining afterwards.

Keywords: Agribusiness; Crop Production/Industries; Research Methods/ Statistical Methods (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/329703/files/artykul-2.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:polpwa:329703

DOI: 10.22004/ag.econ.329703

Access Statistics for this article

More articles in Problems of World Agriculture / Problemy Rolnictwa Światowego from Warsaw University of Life Sciences Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().