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Forecasting the Monthly Tourist Arrival from India to Nepal: An Econometrics Modeling Approach

In: Leveraging Emerging Technologies and Analytics for Empowering Humanity, Vol. 1

Author

Listed:
  • Biplab Bhattacharjee

    (Jindal Global University)

  • Aayush Poudel

    (Kathmandu University)

  • Subin Panta

    (Kathmandu University)

  • Sashwat Sharma

    (Kathmandu University)

  • Samyak Pokharel

    (Kathmandu University)

Abstract

Tourism is a crucial component of the economy in developing countries like Nepal. Nepal is a popular tourist destination for India due to its proximity, shared cultural heritage, and affinities between the people and their respective religions. This study attempts to develop an econometric forecasting model to predict the monthly arrivals from India to Nepal. The COVID-19 pandemic significantly impacted the travel and tourism industry, causing a structural break in the time series arrival data. Using monthly data from 2004 to 2034, the study applies time series models to address complexities such as seasonality, non-stationarity, and structural breaks (due to COVID-19). The findings reveal that an ARIMAX model incorporating Google search trends data performs better than traditional models based on several evaluative measures such as RMSE, MAPE, AIC, and Theil’s U. The proposed forecasting model can assist policymakers, hotel management, and event planners in estimating the level of tourism demand and making better managerial decisions.

Suggested Citation

  • Biplab Bhattacharjee & Aayush Poudel & Subin Panta & Sashwat Sharma & Samyak Pokharel, 2025. "Forecasting the Monthly Tourist Arrival from India to Nepal: An Econometrics Modeling Approach," Springer Proceedings in Business and Economics, in: D P Goyal & Suprateek Sarker & Somnath Mukhopadhyay & Basav Roychoudhury & Parijat Upadhyay & Pradee (ed.), Leveraging Emerging Technologies and Analytics for Empowering Humanity, Vol. 1, chapter 8, pages 157-172, Springer.
    • Handle: RePEc:spr:prbchp:978-981-96-2548-2_8
    DOI: 10.1007/978-981-96-2548-2_8
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