Open AccessForecasting Korean Arrivals in the Philippines
Author(s) -
Enrique Raphael Versoza,
Sofia Elaine Romarate,
Jacque Bon-Isaac Aboy
Publication year - 2020
Publication title -
international journal of innovative science and research technology
Language(s) - English
Resource type - Journals
ISSN - 2456-2165
DOI - 10.38124/ijisrt20sep081
Subject(s) - autoregressive integrated moving average , tourism , econometrics , geography , value (mathematics) , moving average , time series , statistics , climatology , meteorology , economics , mathematics , geology , archaeology
This paper investigates the rise of South Korean tourism in the Philippines from 2014 to 2018 and explain its behavior year-to-year, and the other part is to forecast it’s growth or decline in the next following years; all of this is done through a Seasonal ARIMA (SARIMA) modelling framework. Results reveal that Korean arrivals were best modelled through a ARIMA(1,0,0)(2,1,0)₁₂ model, with residuals that are randomly distributed and contain no autocorrelations and an AICc value of -36.18, the lowest among the tested variations of the model, the model is the most appropriate to forecast the data for a 3-year period.