Forecasting International Tourism Demand in Malaysia Using Box Jenkins Sarima Application
Yahaya Ibrahim, Bangi Selangor
Abstract
Yahaya Ibrahim, Bangi Selangor
Abstract
The main aim of this paper is to generate one-period-ahead forecasts of international tourism demand for Malaysia. An appropriate ARIMA model or well known as Box-Jenkins model has been applied in this paper to generate the forecast of international tourism demand. Before selecting an appropriate model, formal stationary tests has been applied in this paper and finds that, the series are stationary at level. Secondly, in order to get a good estimation, this paper has identified the autoregressive (AR) and moving average (MA) of the entire period of the data. Therefore, the future demand of tourism is forecast based on the combination of AR and MA, which known as ARMA model. In this paper, the competing models have been thoroughly investigated when the model adequacy has been checked before the best combination of ARIMA model was selected. Thus, the best fitted ARIMA (1,0,1) with seasonal effects or well known as SARIMA approaches has been suggested through this study and the forecasting process is based on this combination. The forecasts generated by the ARIMA model suggest that Malaysia will face increasing tourism demand for the period of 2009:Q1-2009:Q4. Besides that, this paper found the Box-Jenkins model has offered valuable insights and provide reliable forecasts of tourism demand for Malaysia.
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The main aim of this paper is to generate one-period-ahead forecasts of international tourism demand for Malaysia. An appropriate ARIMA model or well known as Box-Jenkins model has been applied in this paper to generate the forecast of international tourism demand. Before selecting an appropriate model, formal stationary tests has been applied in this paper and finds that, the series are stationary at level. Secondly, in order to get a good estimation, this paper has identified the autoregressive (AR) and moving average (MA) of the entire period of the data. Therefore, the future demand of tourism is forecast based on the combination of AR and MA, which known as ARMA model. In this paper, the competing models have been thoroughly investigated when the model adequacy has been checked before the best combination of ARIMA model was selected. Thus, the best fitted ARIMA (1,0,1) with seasonal effects or well known as SARIMA approaches has been suggested through this study and the forecasting process is based on this combination. The forecasts generated by the ARIMA model suggest that Malaysia will face increasing tourism demand for the period of 2009:Q1-2009:Q4. Besides that, this paper found the Box-Jenkins model has offered valuable insights and provide reliable forecasts of tourism demand for Malaysia.
Key concepts: Autoregressive integrated moving average, Box–Jenkins, Tourism, Econometrics, Demand forecasting, Moving average, Autoregressive model, Order (exchange)