Revista de Investigaciones Altoandinas - Journal of High Andean Research

Vol. 24 No. 1 (2022)
Original articles

Impact of COVID-19 on the international tourism demand in Peru. An application of the Box-Jenkins methodology

pdf (Spanish)
  • Juan Walter Tudela,
  • Grisell Aliaga-Melo,
  • Elias Cahui-Cahui
Juan Walter Tudela
Universidad Nacional de Altiplano de Puno
Grisell Aliaga-Melo
Universidad Nacional del Altiplano de Puno
Elias Cahui-Cahui
Universidad Nacional del Altiplano de Puno

Published 2022-02-21

Keywords

  • Tourism, time series, seasonal ARIMA, COVID-19

How to Cite

Tudela, J. W., Aliaga-Melo, G., & Cahui-Cahui, E. (2022). Impact of COVID-19 on the international tourism demand in Peru. An application of the Box-Jenkins methodology. Revista De Investigaciones Altoandinas - Journal of High Andean Research, 24(1), 27-36. https://doi.org/10.18271/ria.2022.317

Abstract

In recent years, tourism has taken on considerable importance as a factor of economic and social development in the world, contributing not only to the economic growth of developing countries, but also to the improvement of the quality of life of the people involved in the sector. However, given the global health crisis caused by the coronavirus (COVID-19), the tourism sector was one of the most affected sectors due to the various public safety policies adopted by different countries in the world, especially by European countries that account for more than 50% of international tourism in the Americas, Africa, and the Middle East. The objective of this research was to estimate and project international tourism demand in Peru with monthly time series data from January 2003 to December 2020 through a seasonal ARIMA process proposed by Box-Jenkins called SARIMA. The results show that the seasonal ARIMA model (1,1,1)(0,1,1,1)12 was appropriate for the projection given the Akaike (AIC) and Schwarz (SC) criteria. The model estimates a parsimonious cyclical recovery of international tourist arrivals to our country; however, the evolution of COVID-19 in public health maintains uncertainty about new challenges in the tourism sector that would allow its sustainability and resilience over time. Immediate fiscal and monetary measures are urgently needed to safeguard employment and survival mechanisms for businesses.  

pdf (Spanish)

References

  1. Ahmed, A., Amin, S. Bin, & Khan, A. M. (2020). Forecasting tourism revenue in Bangladesh using ARIMA approach : the case of Bangladesh. International Review of Business Research Papers, 16(1), 202–215. https://zantworldpress.com/wp-content/uploads/2020/03/11.-Adib-Ahmed.pdf
  2. 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
  3. Altmark, S., Mordecki, A., Risso, A., & Santiñaque, F. (2015). Proyección del número de turistas mediante modelo SARIMA. In Instituto de Economía. http://www.iesta.edu.uy/wp-content/uploads/2015/11/presentacion_sue_final_v3.pdf
  4. Baldigara, T., & Mamula, M. (2015). Modelling international tourism demand using seasonal ARIMA models. Tourism and Hospitality Management, 21(1), 19–31. https://hrcak.srce.hr/140166
  5. Bartlett, M. S. (1967). Some remarks on the analysis of time-series. Biometrika, 54((1/2)), 25–38. https://doi.org/10.2307/2333850
  6. Box, G. E. P., & Pierce, D. A. (1970). Distribution of residual in autoregressive-autocorrelations integrated moving average time series models. Journal of the American Statistical Association, 65(332), 1509–1526. https://doi.org/10.2307/2284333
  7. Box, G.E.P., & Jenkins, G.M. (1976). Time series analysis: forecasting and control. Oakland, California.
  8. Brooks, C. (2008). Introductory Econometrics for Finance (2nd Edition (ed.); Second edi). Cambridge University Press. https://www.cambridge.org/core/books/introductory-econometrics-for-finance/4F3AB9473A63F11982D6902D813BC521
  9. Casado, L. (2018). Turismo internacional : evolución global y análisis de las ciudades europeas [Universidad Pontificia Comillas]. https://repositorio.comillas.edu/jspui/bitstream/11531/19124/1/TFG-CasadoFernandez%2CLucas.pdf
  10. Chhorn, T., & Chaiboonsri, C. (2017). Modelling and forecasting tourist arrivals to Cambodia : an application of ARIMA-GARCH approach. Journal of Management, Economics, and Industrial Organization, 2(83942), 1–19. https://mpra.ub.uni-muenchen.de/83942/
  11. Choden, & Unhapipat, S. (2018). ARIMA model to forecast international tourist visit in Bumthang, Bhutan. Journal of Physics: Conference Series, 1039, 1–10. https://doi.org/10.1088/1742-6596/1039/1/012023
  12. Commandeur, J. J. F., & Koopman, S. J. (2007). Practical econometric an introduction to state space time series analysis (1st editio). Oxford University Press Inc. https://www.amazon.es/Introduction-State-Analysis-PRACTICAL-ECONOMETRICS/dp/0199228876
  13. 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
  14. Decreto Supremo N° 044-2020 [Presidencia del Consejo de Ministros]. Decreto Supremo que declara Estado de Emergencia Nacional por las graves circunstancias que afectan la vida de la Nación a consecuencia del brote del Covid-19. 15 de Marzo del 2020 en Lima, Perú.
  15. Fattah, J., Ezzine, L., Aman, Z., Moussami, H. El, & Lachhab, A. (2018). Forecasting of demand using ARIMA model. 10, 1–9. https://doi.org/10.1177/1847979018808673
  16. Fernández, R., Días, L., Alemán, J., & Barrio, O. (2020). Modelo de predicción de series temporales para la demanda turística de la cadena hotelera Cubanacán. Cooperativismo y Desarrollo, 8(3), 538–551. http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S2310-340X2020000300538&lng=es&nrm=iso&tlng=en
  17. Gujarati, D., & Porter, D. (2010). Econometía (5th ed.). Mc Graw Hill. https://fvela.files.wordpress.com/2012/10/econometria-damodar-n-gujarati-5ta-ed.pdf
  18. INEI. (2020). Producción nacional. https://www.inei.gob.pe/media/MenuRecursivo/boletines/07-informe-tecnico-n07_produccion-nacional-may. 2020.pdf
  19. Li, L., Wang, Y., & Li, X. (2020). Tourists forecast Lanzhou based on the Baolan high-speed railway by the Arima. Applied Mathematics and Nonlinear Sciences, 5(1), 55–60. https://doi.org/10.2478/AMNS.2020.1.00006
  20. Ljung, G. M., & Box, G. E. P. (1978). On a measure of lack of fit in time series models. Biometrika, 1(2), 297–303. https://doi.org/10.1093/biomet/65.2.297
  21. Makoni, T. (2018). Modelling and forecasting Zimbabwe’s tourist arrivals using time series method : a case study of Victoria Falls Rainforest. Southern African Business Review, 22(3791), 22. https://doi.org/10.25159/1998-8125/3791
  22. MINCETUR. (2020). Perú: Compendio de cifras de turismo. https://www.gob.pe/institucion/mincetur/informes-publicaciones/394689-compendio-de-cifras-de-turismo-ano-2019
  23. MINCETUR (2021). Sistema de Información Estadística de Turismo. Lima, Perú.
  24. ONU. (2020). Informe de políticas: la Covid-19 y la transformación del turismo. https://www.un.org/sites/un2.un.org/files/policy_brief_covid-19_and_transforming_tourism_spanish.pdf
  25. OTP. (2019). Información económica nacional. http://www.observatorioturisticodelperu.com/badatur/informacion-economica-nacional
  26. Paz, R. (2016). Proyección de la demanda de turismo internacional en Puno: un enfoque Sarima. Semestre Económico, 05(2), 33–51. https://doi.org/10.26867/seconomico.v5i2.134
  27. Peñaranda, C. (2018). Informe económico. https://apps.camaralima.org.pe/repositorioaps/0/0/par/r820_2/informe economico.pdf
  28. Pérez, C. (2006). Problemas resueltos de econometría (1st editio). Paraninfo, S.A.
  29. Petrevska, B. (2017). Predicting tourism demand by A.R.I.M.A. models. Economic Research-Ekonomska Istraživanja, 30(1), 939–950. https://doi.org/10.1080/1331677X.2017.1314822
  30. Phillips, P., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. https://doi.org/10.2307/2336182
  31. Rosales, R., Perdomo, J., Morales, C., & Urrego, J. (2013). Fundamentos de econometría intermedia, teoría y aplicaciones (1st editio). Uniandes. https://www.jstor.org/stable/2336182
  32. Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. https://doi.org/10.1214/aos/1176344136
  33. UNWTO. (2020). Impact assessment of the Covid-19 outbreak on international tourism. https://webunwto.s3.eu-west-1.amazonaws.com/s3fs-public/2020-03/24-03Coronavirus.pdf
  34. WTTC. (2020). Travel & tourism: economic impact 2020. https://wttc.org/Portals/0/Documents/Reports/2020/EIR 2020 Global Infographic.pd

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