Factores determinantes de la demanda turística internacional en Sudamérica: modelos de panel data 2011-2019
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Date
2024
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Universidad Nacional de Trujillo
Abstract
El pronóstico de la demanda turística se debe a la necesidad de planear y tomar decisiones a tiempo, sin embargo, el uso de una metodología inadecuada provocaría estimaciones sesgadas e inconsistentes, llevando de esa manera a una asignación errónea de recursos o una mala gestión del destino. Es por ello que la presente investigación trató de esclarecer qué factores son determinantes para explicar la demanda turística internacional en Sudamérica, periodo 2011- 2019. Se consideró los modelos de data panel de regresión agrupada, efectos fijos y efectos aleatorios para la estimación. La investigación se centró en una muestra espacial de 9 países de Sudamérica, y en una muestra temporal de 9 años, obteniéndose 81 observaciones en total. Los resultados revelaron que tanto el PBI per cápita como el gasto promedio por turista internacional son determinantes para explicar la demanda turística. Además, se encontró que el modelo de efectos aleatorios es el más consistente y eficiente en comparación con los otros modelos, como se evidenció mediante la prueba de Hausman (valor-p = 0.133 > 0.05).
ABSTRACT The forecast of tourism demand is due to the need to plan and make decisions in time, however, the use of an inadequate methodology would cause biased and inconsistent estimates, thus leading to an erroneous allocation of resources or poor management of the destination. That is why this research tried to clarify which factors are determining factors in explaining international tourism demand in South America, period 2011-2019. Grouped regression data panel models, fixed effects and random effects were considered for the estimation. The research focused on a spatial sample of 9 South American countries, and on a temporal sample of 9 years, obtaining 81 observations in total. The results revealed that both GDP per capita and average spending per international tourist are determinants in explaining tourism demand. Furthermore, the random effects model was found to be the most consistent and efficient compared to the other models, as evidenced by the Hausman test (p-value = 0.133 > 0.05).
ABSTRACT The forecast of tourism demand is due to the need to plan and make decisions in time, however, the use of an inadequate methodology would cause biased and inconsistent estimates, thus leading to an erroneous allocation of resources or poor management of the destination. That is why this research tried to clarify which factors are determining factors in explaining international tourism demand in South America, period 2011-2019. Grouped regression data panel models, fixed effects and random effects were considered for the estimation. The research focused on a spatial sample of 9 South American countries, and on a temporal sample of 9 years, obtaining 81 observations in total. The results revealed that both GDP per capita and average spending per international tourist are determinants in explaining tourism demand. Furthermore, the random effects model was found to be the most consistent and efficient compared to the other models, as evidenced by the Hausman test (p-value = 0.133 > 0.05).
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Demanda turística