• Theara CHHORN Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand Sovannaphum Life Assurance PLC, Phnom Penh, Cambodia


Time series seasonally displays toward either an autoregressive or moving average process where persist in seasonality fluctuation. The paper examines the relationship of tourism demand with controlling an exogenous exchange rate using seasonal ARIMA model. The empirical results reveal that HEGY test for seasonal unit roots with lower and upper panel indicates the statistical significance which explains the failure of rejection of having unit roots at different frequencies. The estimated outcomes from tourism demand model specify that per capita income and exchange rate have the power in explaining tourism demand measured as tourist arrivals. In particular to forecasting model and due to the lower statistical value of RMSE and MAE displays that the SARIMAX (4, 1, 1) – (1, 1, 1)12 model is the best accuracy model to perform the long run ex-ante forecasting of tourism demand. This suggests tourism policy maker to pay more reflection in formulating the policy toward the exogenous factors in line with the uncertainty and unobserved seasonality.


Breitung, J., and Franses, P. 1998. On Phillips-Perron-Type Tests for Seasonal Unit Roots. Econometric Theory, 14(2): 200-221. Available at:
[2] Seetanah, B., Sannassee, R. and Sawkut Rojid 2015. The impact of relative prices on tourism demand for Mauritius: An empirical analysis, Development Southern Africa, 32(3): 363-376, DOI: 10.1080/0376835X.2015.1010717
[3] Box, G. a. 1970. Time series analysis: Forecasting and control. San Francisco: Holden-Day. DOI:10.1002/9781118619193
[4] Crouch, G. I. 1995. A meta-analysis of tourism demand. Annals of Tourism Research, 22(1): 103-118. DOI:
[5] Depalo, D. 2009. A seasonal unit-root test with Stata. The Stata Journal, 9(3): 422–438. Available at:
[6] Quadri, D. L. and Zheng, T. 2010. A Revisit to the Impact of Exchange Rates on Tourism Demand: The Case Of Italy. The Journal of Hospitality Financial Management, 18(2): 47-60. DOI:
[7] Dwyer, L. F. 2002. Destination price competitiveness: Exchange rate changes versus domestic inflation. Journal of Travel Research, 40(3): 328-336. DOI:
[8] Agiomirgianakis, G. D. S. 2014. Exchange Rate Volatility and Tourist Flows into Turkey. Journal of Economic Integration, 29(4): 700-725. DOI:
[9] Gerolimetto, M. 2010. ARIMA and SARIMA models.
[10] Hylleberg, S. E. 1990. Seasonal integration and cointegration. Journal of Econometrics, 44: 215-238. DOI:
[11] Jintanee Jintranun, S. S. 2011. Thailand’s International Tourism Demand: Seasonal Panel Unit Roots and the Related Cointegration Model. Review of Economics & Finance, 1: 63-76.
[12] Johansen, S. 1988. Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12: 231–254. DOI:
[13] Johnson, P. 1990. Modelling tourism demand: A summary review. Leisure Studies, 9(2), 145-161. DOI:
[14] Kritharas, P. 2013. Developing a SARIMAX model for monthly wind speed forecasting in the uk. Loughborough University's Institutional Repository. Petros Kritharas. Available at:
[15] Lee, C-L., Var, T., and Blaine, T.W. 1996. Determinants of inbound tourist expenditure’. Annals of Tourism Research, 23(3): 527–542. DOI:
[16] Song, H. and Li, G. 2008. Tourism Demand Modelling and Forecasting: A Review of Recent Research. Tourism Management, 29 (2): 203-220. DOI:
[17] Lim, C. 1997. Review of international tourism demand models. Annals of Tourism Research, 24(4): 835-849. DOI:
[18] Li, G., Song, H., and Witt, S. F. 2005. Recent developments in econometric modeling and forecasting. Journal of Travel Research, 44: 82-99. DOI:
[19] Luís F. M., Gan, Y., and Ferreira-Lopez, A.. 2017. An Empirical Analysis of the Infuence of Macroeconomic Determinants on World Tourism Demand. Tourism Management, 61: 248-260. DOI:
[20] Lundberg, D. E., Krishnamoorthy, M., and Stavenga, M.H. 1995. Tourism Economics. New York: Wiley.
[21] Aktar, M. A. Sadekin, N., and Saha, S.K. 2014. Relationship between Tourist Arrival and Foreign Exchange Earnings: The Case for Bangladesh. Mediterranean Journal of Social Sciences, 5(16): 162-165. DOI:10.5901/mjss.2014.v5n16p162
[22] Martin, C., and Witt, S. 1987. Tourism demand forecasting models: Choice of appropriate variable to represent tourists' cost of living. Tourism management, 8(3): 233-246. DOI:
[23] Martin C., and Witt, S. F. 1987. Econometric models for forecasting international tourism demand. Journal of Travel Research, 25(3): 23-30. DOI:
[24] Önder, A. C., Candemir, A., and Kumral, N. 2009. An empirical analysis of the determinants of international tourism demand: The case of Izmir. European Planning Studies, 17(10): 1525-1533. DOI:
[25] Patsouratis, V. F. 2005. Competition in tourism among the Mediterranean countries. Applied Economics, 37(18): 1865-1870.
[26] Peiris, H. R. 2016. A Seasonal ARIMA Model of Tourism Forecasting: The Case of Sri Lanka. Journal of Tourism, Hospitality and Sports, 22: 98-109.
[27] Ruane, MCM. 2014. Exchange Rates and Tourism: Evidence from the Island of GUAM. Journal of Economic and Economic Education Research, 15 (2): 165-186.
[28] Hylleberg, S., Engle, R. F., Granger, C. W. J. and Yoo, B. S. 1990. Seasonal integration and Cointegration. Journal of Econometrics, 44(1-2): 215-238.
[29] Song, H. and Li, G. 2008. Tourism Demand Modelling and Forecasting: A Review of Recent Research. Tourism Management, 29 (2): 203-220. DOI:
[30] Song, H. W., Witt, S. F., and Gang Li 2009. The advanced econometrics of tourism demand. NewYork & London: Routledge.
[31] Stata. (n.d.). arima — ARIMA, ARMAX, and other dynamic regression models. STATA. Available at:
[32] De Vita, G. 2014. The long-run impact of exchange rate regimes on international tourism flows. Tourism Management, 45: 226-233. DOI:
[33] WTTC. 2016. Exchange Rate Trends and Travel & Tourism Performance. Available at:
[34] Xiangli Meng, and Changeli He 2012. Testing Seasonal Unit Roots in Data at Any Frequency: an HEGY approach. Available at:
[35] Xiaosheng Li, Chunliu Ma, Haikei Lei, and Haixia, Li 2013. Applications of SARIMA Model in Forecasting Outpatient Amount. Chinese Medical Record English Edition, 1(3): 124-128. DOI:
[36] Gan, Y. 2015. An Empirical Analysis of The Influence of Exchange Rate and Prices on Tourism Demand. ISCTE Business School, Department of Quantitative. Available at:
[37] Yap, G. C. L. 2012. An Examination of the Effects of Exchange Rates on Australia's Inbound Tourism Growth: A Multivariate Conditional Volatility Approach. International Journal of Business Studies , 20(1): 111 - 132 . Available at:
[38] Quadri, D., Zheng, T. 2011. A Revisit to the Impact of Exchange Rates on Tourism Demand: The Case of Italy. Journal of Hospitality Financial Management, 18(2). Available at:
How to Cite
CHHORN, Theara. TOURISM DEMAND AND EXOGENOUS EXCHANGE RATE IN CAMBODIA: A STOCHASTIC SEASONAL ARIMAX APPROACH. Theoretical and Practical Research in Economic Fields, [S.l.], v. 9, n. 1, p. 5-16, june 2018. ISSN 2068-7710. Available at: <>. Date accessed: 22 may 2024. doi: