Forecasting with X-12-ARIMA and ARFIMA: International Tourist Arrivals to India
Abstract
Econometric forecasting involves the application of statistical and mathematical models to forecast future economic developments. This study focuses on forecasting methods based on both X-12-ARIMA seasonal adjustment and an autoregressive fractionally integrated moving average (ARFIMA). Secondary data based on facts and figures that have already been recorded were utilized to forecast international tourist arrivals to India, 2007-2010. From this period the results confirm that the best forecasting method for India based on the X-12-ARIMA seasonal adjustment consisting of X-12-ARIMA(0,1,2)(0,1,1), X-12-ARIMA(0,1,1)(0,1,1) and X-12-ARIMA(2,1,0)(0,1,1) and the best forecasting method based on ARFIMA(p,d,q) method consisting of ARFIMA(1,0.1906,1), ARFIMA(1,0.2562,1), ARFIMA (1,0.2635,1) and ARFIMA(1,0.2951,1). Furthermore these methods predict that international tourism arrivals to India, 2007-2010 will increase at a positive growth rate. If these results can be generalized to a series of future year, then a recommendation from the study under taken should enable both public sector and private sector policy makers to develop a strategic tourism plan to focus on the increasing numbers of international tourist arrivals to India.Download Info
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Article provided by University of Petrosani, Romania in its journal Annals of the University of Petrosani, Economics.
Volume (Year): 9 (2009)
Issue (Month): 3 ()
Pages: 147-162
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Web page: http://www.upet.ro/
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Keywords: India; international tourism; X-12-ARIMA method; ARFIMA method; best forecasting methods;References
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