Modelling and forecasting international tourism demand in Puno-Peru
DOI:
https://doi.org/10.7784/rbtur.v14i1.1606Keywords:
Seasonality, Titicaca lake, Peru, ARIMA, CultureAbstract
The tourism industry in Peru generates about 1.1 million jobs and contributes 3.3% of GDP, which makes it one of its main economic activities, so tourism is no longer just a commercial activity and transforms into a tool for the development of the Peruvian population especially in regions with high poverty rate and with numerous tourist attractions as it is the case of the Puno region with a poverty rate of 24.2% that is located in the south of the country and that has numerous tourist attractions of natural, historical, cultural and gastronomic type. The objective of this research is to model and forecasting the demand of international tourists visiting Puno using the ARIMA methodology of Box-Jenkins, for this the study considers monthly arrival information of foreign tourists between the years 2003 to 2017. Finally, using the statistics MAPE, Z, r, Akaike Information Criterion (AIC) and Schwarz Criterion (SC) was identified to the SARIMA (6, 1, 24)(1, 0, 1)12 model as the most efficient for modeling and forecasting of the demand for international tourism in the Puno region.
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References
Akaike, H. (1974). A New Look at the Statistical Model Identification. IEEE Transactions on Automatic Control, 19(6), 716–723. https://doi.org/10.1109/TAC.1974.1100705
Akal, M. (2004). Forecasting Turkey’s tourism revenues by ARMAX model. Tourism Management, 25(5), 565–580. https://doi.org/10.1016/j.tourman.2003.08.001
Athanasopoulos, G., & Hyndman, R. J. (2008). Modelling and forecasting Australian domestic tourism. Tourism Management, 29 (October 2006), 19–31. https://doi.org/https://doi.org/10.1016/j.tourman.2007.04.009
Baillie, R. (1996). Long Memory Processes and Fractional Integration in Econometrics. Journal of Economet-rics, 73(1), 5–59. https://doi.org/10.1016/0304-4076(95)01732-1
Banco Central de Reserva del Perú - BCRP. Gerencia Central de Estudios Económicos (2018). Producto Bruto Interno por sectores productivos (millones S/ 2007). Retrieved March 26, 2019, from https://estadisticas.bcrp.gob.pe/estadisticas/series/anuales/resultados/PM05000AA/html
Banco Central de Reserva del Perú – BCRP. Sucursal Puno. (2018). Síntesis de Actividad Económica, varios meses. Retrieved January 20, 2018, from http://www.bcrp.gob.pe/51-sucursales/sede-regional-puno.html
Botti, L.; Peypoch, N.; Randriamboarison, R.; & Solonandrasana, B. (2007). An Econometric Model of Tourism Demand in France. Tourismos: An International Multidisciplinary Journal of Tourism, 2(1), 115–126. Retrieved from http://mpra.ub.uni-muenchen.de/25390/
Box, G., & Jenkins, G. M. (1976). Time Series Analysis: forecasting and control. Oakland, California.
CAMARA. (2018). Cámara de Comercio de Lima - Sector turismo representa 3.3% del PBI y genera 1.1 mil-lones de empleos. Retrieved from https://www.camaralima.org.pe/repositorioaps/0/0/par/r820_2/informe economico.pdf
Cayo, N., & Apaza, A. (2017). Evaluación de la ciudad de Puno como destino turístico - Perú. Comuni@cción, 8(2), 116–124. Retrieved from http://www.scielo.org.pe/scielo.php?script=sci_arttext&pid=S2219-71682017000200005
Chaitip, P., & Chaiboonsri, C. (2015). Forecasting with X-12-ARIMA y ARFIMA: International Tourist Arrivals to India. Annals of the University of Petroşani, Economics, 9(3), 147–162. Retrieved from http://repositorio.ana.gob.pe/handle/ANA/1564
Chan, F., Lim, C., & McAleer, M. (2005). Modelling multivariate international tourism demand and volatility. Tourism Management, 26(3), 459–471. https://doi.org/10.1016/j.tourman.2004.02.013
Chang, C., Sriboonchitta, S., & Wiboonpongse, A. (2009). Modelling and forecasting tourism from East Asia to Thailand under temporal and spatial aggregation, Mathematics and Computers in Simulation, 79, 1730–1744. https://doi.org/10.1016/j.matcom.2008.09.006
Chokethaworn, K., Wiboonponse, A., Sriboonchitta, S., Sriboonjit, J., Chaiboonsri, C., & Chaitip, P. (2010). In-ternational Tourists’ Expenditures in Thailand: A Modelling of the ARFIMA-FIGARCH Approach. The Thailand Econometrics Society, 10(January), 85–98.
Chow, G. (1960). Tests of Equality Between Sets of Coefficients in Two Linear Regressions. Econometrica, 28(3), 591–605. https://doi.org/10.2307/1913018
Chu, F. L. (2008). A Fractionally Integrated Autoregressive Moving Average Approach to Forecasting Tourism Demand. Tourism Management, 29(1), 79–88. https://doi.org/10.1016/j.tourman.2007.04.003
CORREO. (2017). Turismo y empleo en la región Puno. Retrieved March 26, 2019, from https://diariocorreo.pe/peru/turismo-en-la-region-puno-genera-90-mil-empl-7289/
Coshall, J. T. (2009). Combining volatility and smoothing forecasts of UK demand for international tourism. Tourism Management, 30(4), 495–511. https://doi.org/10.1016/j.tourman.2008.10.010
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of the American Statistical Association, 74(366), 427–431. https://doi.org/10.2307/2286348
du Preez, J., & Witt, S. F. (2003). Univariate versus multivariate time series forecasting: An application to inter-national tourism demand. International Journal of Forecasting, 19(3), 435–451. https://doi.org/10.1016/S0169-2070(02)00057-2
Durbin, J., & Watson, G. S. (1950). Testing for Serial Correlation in Least Squares Regression. I. Biometrika Trust, 58(1), 409–428. https://doi.org/10.2307/2332391
Durbin, J., & Watson, G. S. (1971). Testing for serial correlation in least squares regression. III. Biometrika, 58(1), 1–19. https://doi.org/10.1093/biomet/58.1.1
GESTION. (2017). Perú: Llegada de turistas por país. Retrieved March 25, 2019, from https://gestion.pe/economia/llegaran-4-8-millones-turistas-internacionales-peru-ano-10-2018-258028
Granger, C., & Joyeux, R. (1980). An Introduction to Long-Memory Time Series Models and Fractional Differenc-ing. Journal of Time Series Analysis, I(1), 15–29. https://doi.org/https://doi.org/10.1111/j.1467-9892.1980.tb00297.x
Greenidge, K. (2001). Forecasting Tourism Demand An STM Approach. Annals of Tourism Research, 28(1), 98–112. https://doi.org/https://10.1016/S0160-7383(00)00010-4
Hosking, J. R. M. (1981). Fractional differencing. Biometrika, 68(1), 165–176. https://doi.org/10.1093/biomet/68.1.165
Instituto Nacional de Estadística e Informática - INEI (2018a). Pobreza por departamentos del Perú. Retrieved February 4, 2019, from https://www.inei.gob.pe/estadisticas/indice-tematico/living-conditions-and-poverty/
Instituto Nacional de Estadística e Informática - INEI. (2018b). Peru, PBI por departamentos según actividades económicas. Retrieved March 26, 2019, from https://www.inei.gob.pe/estadisticas/indice-tematico/pbi-de-los-departamentos-segun-actividades-economicas-9110/
INRENA. (1995) Evaluacion de la contaminacion del lago titicaca. Retrieved from http://repositorio.ana.gob.pe/handle/ANA/1564
Jarque, C., & Bera, A. (1980). Efficient tests for normality, homoscedasticity and serial independence of re-gression residuals. Economics Letters, 6(4), 255–259. https://doi.org/10.1016/0165-1765(81)90035-5
Jarque, C., & Bera, A. (1981). Efficient tests for normality, homoscedasticity and serial independence of re-gression residuals Monte Carlo Evidence. Journal of the American Statistical Association, 7, 313–318. https://doi.org/doi:10.1016/0165-1765(81)90035-5
Jarque, C., & Bera, A. (1987). A test for Normality of observations and Regression Residuals. International Statistical Review, 55(2), 163–172. https://doi.org/10.2307/1403192
Kwiatkowski, D.; Phillips, P.; Schmidt, P.; & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54(1–3), 159–178. https://doi.org/10.1016/0304-4076(92)90104-Y
Laurente, L. & Poma, R. (2016). Introducción a la teoría de las probabilidades (Primera Ed). Puno, Perú.
Law, R., & Au, N. (1999). A neural network model to forecast Japanese demand for travel to Hong Kong. Tour-ism Management, 20(1), 89–97. https://doi.org/10.1016/S0261-5177(98)00094-6
Lee, C. K.; Song, H. J.; & Mjelde, J. W. (2008). The forecasting of International Expo tourism using quantitative and qualitative techniques. Tourism Management, 29(6), 1084–1098. https://doi.org/10.1016/j.tourman.2008.02.007
Lewis, C. D. (1982). Industrial and business forecasting methods. London: Butterworths. Retrieved from http://interstat.statjournals.net/YEAR/2008/articles/0810005.pdf
Lim, C., & Mcaleer, M. (1999). A seasonal analysis of Malaysian tourist arrivals to Australia. Mathematics and Computers in Simulation, 48(4), 573–583. https://doi.org/https://10.1016/S0378-4754(99)00038-5
Ljung, G., & Box, G. (1978). Biometrika Trust On a Measure of Lack of Fit in Time Series Models. Biometrika, 65(2), 297–303. https://doi.org/https://doi.org/10.1093/biomet/65.2.297
Loganathan, N., & Ibrahim, Y. (2010). Forecasting International Tourism Demand in Malaysia Using Box Jen-kins Sarima Application. South Asian Journal of Tourism and Heritage, 3(2), 50–60.
Mackinnon, J. (1996). Numerical Distribution Functions for Unit Root and Cointegration Tests. Journal of Ap-plied Econometrics, 11(6), 601–618. https://doi.org/https://doi.org/10.1002/(SICI)1099-1255(199611)11:6<601::AID-JAE417>3.0.CO;2-T
Mamani, L. (2016). Impacto socioeconómico del turismo rural comunitario de Karina-Chucuito. Universidad Nacional del Altiplano. Retrieved from http://repositorio.unap.edu.pe/bitstream/handle/UNAP/1802/Articulo.pdf?sequence=1&isAllowed=y
MINCETUR. (2017a). Perú: Arribo de visitantes extranjeros a establecimientos de hospedaje, según región. Serie estadística 2003-2017. Retrieved January 17, 2018, from http://datosturismo.mincetur.gob.pe/appdatosTurismo/Content3.html
MINCETUR. (2017b). Perú: Llegada de turistas internacionales según país de residencia permanente. Re-trieved March 25, 2019, from http://datosturismo.mincetur.gob.pe/appdatosTurismo/Content1.html
MiViaje. (2018). Descubre las islas de los uros en el lago Titicacaca - Panel fotográfico. Retrieved March 25, 2019, from https://miviaje.com/las-islas-de-los-uros-lago-titicaca/
Nanthakumar, L., Subramaniam, T., & Kogid, M. (2012). Is “Malaysia Truly Asia”? Forecasting tourism demand from ASEAN using SARIMA approach. Tourismos, 7(1), 367–381. Retrieved from http://www.chios.aegean.gr/tourism/VOLUME_7_No1_art20.pdf
Organización Mundial del Turismo - OMT. (2017). Panorama OMT del turismo internacional. Retrieved from http://www.e-unwto.org/doi/book/10.18111/9789284419043
Peiris, H. (2016). A Seasonal ARIMA Model of Tourism Forecasting: The Case of Sri Lanka. Journal of Tourism, Hospitality and Sports, 22, 98–109. Retrieved from https://www.iiste.org/Journals/index.php/JTHS/article/view/33831
Peiris, M. S., & Perera, B. J. C. (1988). On Prediction with Fractionally Differenced Arima Models. Journal of Time Series Analysis, 9(3), 215–220. https://doi.org/10.1111/j.1467-9892.1988.tb00465.x
Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. https://doi.org/10.1093/biomet/75.2.335
Psillakis, Z., Alkiviadis, P., & Kanellopoulos, D. (2009). Low cost inferential forecasting and tourism demand in accommodation industry. Tourismos: An International Multidisciplinary Journal of Tourism, 4(2), 47–68.
PUNO. (2017). Principales recursos turísticos em Puno. Retrieved from http://www.bcrp.gob.pe/docs/Sucursales/Puno/Puno-Atractivos.pdf
Ray, B. K. (1993). Modeling Long Memory Processes for Optimal Long Range Prediction. Journal of Time Series Analysis, 14(5), 511–525. https://doi.org/10.1111/j.1467-9892.1993.tb00161.x
Reisen, V. (1994). Estimation of the fractional difference parameter in the ARIMA (p,d,q) model using the smoothed periodogram. Journal of Time Series Analysis, 15(3), 335–350. https://doi.org/https://doi.org/10.1111/j.1467-9892.1994.tb00198.x
Schwarz, G. (1978). Estimating the Dimension of a Model. The Annals of Statistics, 6(2), 461–464. https://doi.org/10.1214/aos/1176344136
Shareef, R., & McAleer, M. (2005). Modelling International Tourism Demand and Volatility in Small Island Tour-ism Economies. International Journal of Tourism Research, 7(6), 313-333. https://doi.org/10.1002/jtr.538
Shitan, M. (2008). Time series modelling of tourist arrivals to Malaysia. Department of Mathemat-ics, Faculty of Science, and Applied & Computational Statistics Laboratory, Institute for Mathemati-cal Research, Universiti Putra Malaysia. Retrieved from http://interstat.statjournals.net/YEAR/2008/articles/0810005.pdf
Zhou, T., Bonham, C., & Gangnes, B. (2007). Modeling the supply and demand for tourism: a fully identified VECM approach. Department of Economics and University of Hawaii Economic Reserch Organization. Universi-ty of Hawaii at Manoa. Working Paper No. 07-17, July 20, 2007. https://doi.org/10.1001/archinte.165.8.854
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