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Modelling Monthly International Tourist Arrivals and Its Risk in Nepal

Author

Listed:
  • Hari Sharma Neupane

    (Department of Agriculture, Government of Nepal.)

  • Chandra Lal Shrestha

    (Department of Rural Development, Tribhuvan University, Nepal)

  • Tara Prasad Upadhyaya

Abstract

The volume of international tourist arrivals is the prime concern for both the tourism entrepreneurs and policy makers, as the arrivals is directly associated with foreign exchange earnings or export benefits, and tourism induced economic activities. The overall average annual growth of international tourist arrivals in the country over the last 40 years is about 6.65 percent. The mean contribution of tourism sector as a percentage of GDP was 2.67 percent during the last 35 years. This paper explores the risk associated in the Nepalese tourism industry taking account of monthly international tourist arrivals. The symmetric and asymmetric conditional mean and volatility models, GARCH, GARCH-GJR and EGARCH with exogenous ARMA terms were applied for data analysis. The empirical results showed that the long run risk or volatility is persistence in monthly international tourist arrivals and estimated coefficients are statistically significant. The volatility can be inferred as risk or uncertainty as sociated with international tourist arrivals in Nepalese tourism industry. Therefore, this empirical study envisages sufficient room for intervening or amending the tourism policy to better attract international visitors and promote tourism as a business.

Suggested Citation

  • Hari Sharma Neupane & Chandra Lal Shrestha & Tara Prasad Upadhyaya, 2012. "Modelling Monthly International Tourist Arrivals and Its Risk in Nepal," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, vol. 24(1), pages 28-47, April.
    • Handle: RePEc:nrb:journl:v:24:y:2012:i:1:p:3
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    References listed on IDEAS

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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