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.

Highlights

  • In recent years, tourism has taken on considerable importance as a factor of economic and social development in the world, contributing to the economic growth of developing countries, and to the improvement of the quality of life of the people involved in the sector

  • El turismo en los últimos años ha tomado notable importancia como factor de desarrollo económico y social en el mundo, contribuyendo no solo en el crecimiento económico de los países en desarrollo, sino también en la mejora de la calidad de vida de las personas involucradas al sector

  • Journal of Management, Economics, http : / / www

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Summary

Materiales y métodos

Para el presente estudio de investigación, se utilizó información secundaria correspondiente al arribo mensual de turistas extranjeros al Perú para el periodo enero 2003 – diciembre 2020. Dentro de las etapas propias de la metodología Box y Jenkins dado una variable de serie temporal comprende: el análisis de estacionariedad (ruido blanco) de la variable en estudio, para ello se recurre a las pruebas gráficas ( correlogramas F AS y F ACP) o d e manera formal a las pruebas estadísticas de raíces unitarias ADF de Dickey Fuller (1979) y PP en honor a los autores Phillips y Perron (1988); identificación d el proceso generado de datos (AR, MA o ARIMA) de orden p,d,q a través de los correlogramas FAS y FACP de la serie estacionaria; especificación y e stimación d el modelo AR, MA, ARMA (variable integrada de orden cero), ARIMA (variable integrada de algún orden) o SARIMA. Finalmente, se realiza la validez de la predicción para la toma de decisiones

Análisis descriptivo
Con intercepto y tendencia
Estimación del modelo SARIMA
Validación del modelo SARIMA
Findings
Proyección de la demanda internacional de turistas en el Perú
Full Text
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