International Tourists Arrival to Thailand: Forecasting by Non-Linear Model

被引:10
作者
Chaitip, Prasert [1 ]
Chaiboonsri, Chukiat [1 ]
机构
[1] Chiang Mai Univ, Fac Econ, Chiang Mai 50000, Thailand
来源
INTERNATIONAL CONFERENCE ON APPLIED ECONOMICS (ICOAE 2014) | 2014年 / 14卷
关键词
Non-linear; Markov Switching Vector Autoregressive (MS-VAR) Model; AR-bootstrap; AR-Maximum Entropy Bootstrap; Thailand; high seasonal; low seasonal; MAXIMUM-ENTROPY BOOTSTRAP; TIME-SERIES; NEURAL-NETWORK; VOLATILITY; MARKET;
D O I
10.1016/S2212-5671(14)00691-1
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
The aim of this study is to provide non-linear forecasting models for prediction of the international tourist arrival to Thailand by using data from period 1998-2014(Feb.). The seasonal unit root test (HEGY-test extent version) was carried out to test this data. Based on this testing is found that the number of international tourist arrivals to Thailand was affected by seasonal unit root process for during period of this study. Therefore, both the MS-VAR model and AR model are employed to predict this data for future of Thailand. The empirical results from this research was concluded that in high seasonal period can be use AR (2)-MLE, AR (2)-MLE-bootstrapping, and AR(1)-ME-bootstrapping to predict the number of international tourist arrivals to Thailand for future years. However, in low seasonal period only AR(1)-ME-bootstrapping can be used to predict the number of international tourist arrival to Thailand for future years. (C) 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
引用
收藏
页码:100 / 109
页数:10
相关论文
共 33 条
[1]  
[Anonymous], 2006, SAINS MALAYSIANA J
[2]  
[Anonymous], TIME SERIES R METRIC
[3]  
[Anonymous], MODELING FIANACIAL T
[4]  
[Anonymous], TAIL APPROXIMATIONS
[5]  
[Anonymous], 2005, ANAL FINANCIAL TIME, DOI DOI 10.1002/0471746193
[6]   A hybrid neural network cybernetic system for quantifying cross-market dynamics and business forecasting [J].
Ao, S. I. .
SOFT COMPUTING, 2011, 15 (06) :1041-1053
[7]   A non-linear tourism demand forecast combination model [J].
Cang, Shuang .
TOURISM ECONOMICS, 2011, 17 (01) :5-20
[9]  
Chang Chiao-Yi, 2009, INT RES J FINANCE EC
[10]  
Chiang TC., 2001, Rev. Quant. Financ. Account, V17, P301, DOI DOI 10.1023/A:1012296727217