Bhattacharya, Kaushik (2011): Role of Rules of Thumb in Forecasting Foreign Tourist Arrival: A Case Study of India.
Download (316kB) | Preview
The paper examines forecast performances of some popular rules of thumb vis-à-vis more sophisticated time series models in the specific context of foreign tourist arrival in India. Among all forecasting approaches attempted in the study, exponential smoothing (ES) and ARIMA provided the best short-term forecasts, closely followed by autoregressive distributed lag (ADL) models. These results are largely in agreement with cross-country findings on tourism forecast. Foreign tourist arrival data in India, however, displayed a regularity that did not change substantially even in the face of major global or local events. Given the regularity, our study suggests that rules of thumb can play an important practical part in short-term forecasts of tourist arrival in India. Our study, however, reveals that forecasts from such thumb rules could be improved substantially through simple residual corrections and incorporation of other information available in the public domain.
|Item Type:||MPRA Paper|
|Original Title:||Role of Rules of Thumb in Forecasting Foreign Tourist Arrival: A Case Study of India|
|English Title:||Role of Rules of Thumb in Forecasting Foreign Tourist Arrival: A Case Study of India|
|Keywords:||Tourism, Tourist Arrival, Forecasting, Rules of Thumb, Exponential Smoothing, ARIMA, ADL|
|Subjects:||C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes
L - Industrial Organization > L8 - Industry Studies: Services > L83 - Sports ; Gambling ; Restaurants ; Recreation ; Tourism
|Depositing User:||Kaushik Bhattacharya|
|Date Deposited:||31. Jan 2011 20:25|
|Last Modified:||30. Dec 2015 19:35|
Chan YM, 1993: ‘Forecasting tourism: a sine wave time series regression approach’, Journal of Travel Research, 32, 58–60.
Chu FL, 1998: ‘Forecasting tourism: a combined approach’, Tourism Management, 19, 515–520.
Frechtling DC, 2001: Forecasting Tourism Demand: Methods and Strategies, Butterworth-Heinemann.
Goh C and R Law, 2002: ‘Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention’, Tourism Management, 23, 499–510.
Lim C, 2001: ‘Monthly seasonal variations: Asian tourism to Australia’, Annals of Tourism Research, 28, 68–82.
Meese R and K Rogoff, 1983: ‘Empirical exchange rate models of the 1970s: do they fit out of sample?’ Journal of International Economics,14, 3 – 24.
Qu H and HQ Zhang, 1996: ‘Projecting international tourist arrivals in East Asia and the Pacific to the year 2005’, Journal of Travel Research, 35, 27–34.
Witt SF and CA Witt, 1995a: Modeling and Forecasting Demand in Tourism, San Diego: Academic Press.
Witt SF and CA Witt, 1995b: ‘Forecasting tourism demand: a review of empirical research’, International Journal of Forecasting, 11, 447–475.
Wong KKF, 1997: ‘The relevance of business cycles in forecasting international tourist arrivals’, Tourism Management, 18, 581–586.