Forecasting Foreign Tourist Arrivals to India Using Time Series Models
Volume 16, Issue 4 (2018), pp. 702–722
Pub. online: 4 August 2022
Type: Research Article
Open Access
Published
4 August 2022
4 August 2022
Abstract
This study aims to compare various quantitative models to forecast monthly foreign tourist arrivals (FTAs) to India. The models which are considered here include vector error correction (VEC) model, Naive I and Naive II models, seasonal autoregressive integrated moving average (SARIMA) model and Grey models. A model based on combination of single forecast values using simple average (SA) method has also been applied. The forecasting performance of these models have been compared under mean absolute percentage error (MAPE) and U-statistic (Ustat) criteria. Empirical findings suggest that the combination model gives better forecast of FTAs to India relative to other individual time series models considered here.